The Industrial Internet of Things(IIoT)has brought numerous benefits,such as improved efficiency,smart analytics,and increased automation.However,it also exposes connected devices,users,applications,and data generated...The Industrial Internet of Things(IIoT)has brought numerous benefits,such as improved efficiency,smart analytics,and increased automation.However,it also exposes connected devices,users,applications,and data generated to cyber security threats that need to be addressed.This work investigates hybrid cyber threats(HCTs),which are now working on an entirely new level with the increasingly adopted IIoT.This work focuses on emerging methods to model,detect,and defend against hybrid cyber attacks using machine learning(ML)techniques.Specifically,a novel ML-based HCT modelling and analysis framework was proposed,in which L1 regularisation and Random Forest were used to cluster features and analyse the importance and impact of each feature in both individual threats and HCTs.A grey relation analysis-based model was employed to construct the correlation between IIoT components and different threats.展开更多
This paper examines how cybersecurity is developing and how it relates to more conventional information security. Although information security and cyber security are sometimes used synonymously, this study contends t...This paper examines how cybersecurity is developing and how it relates to more conventional information security. Although information security and cyber security are sometimes used synonymously, this study contends that they are not the same. The concept of cyber security is explored, which goes beyond protecting information resources to include a wider variety of assets, including people [1]. Protecting information assets is the main goal of traditional information security, with consideration to the human element and how people fit into the security process. On the other hand, cyber security adds a new level of complexity, as people might unintentionally contribute to or become targets of cyberattacks. This aspect presents moral questions since it is becoming more widely accepted that society has a duty to protect weaker members of society, including children [1]. The study emphasizes how important cyber security is on a larger scale, with many countries creating plans and laws to counteract cyberattacks. Nevertheless, a lot of these sources frequently neglect to define the differences or the relationship between information security and cyber security [1]. The paper focus on differentiating between cybersecurity and information security on a larger scale. The study also highlights other areas of cybersecurity which includes defending people, social norms, and vital infrastructure from threats that arise from online in addition to information and technology protection. It contends that ethical issues and the human factor are becoming more and more important in protecting assets in the digital age, and that cyber security is a paradigm shift in this regard [1].展开更多
Objective:To assess the psychometric properties of the Thai version of the Self-Care Self-Efficacy Scale version 3.0(SCSES-v3.0)in individuals with chronic illnesses.Although originally developed and tested in a Weste...Objective:To assess the psychometric properties of the Thai version of the Self-Care Self-Efficacy Scale version 3.0(SCSES-v3.0)in individuals with chronic illnesses.Although originally developed and tested in a Western context,its applicability in Asian populations,including Thailand,remains inadequately explored.Methods:Psychometric tests were guided by COSMIN principles.This included the translation of the English version into Thai based on the ISPOR framework.Nine nursing experts evaluated the content validity.Data were obtained from a multicenter cross-sectional study conducted between July and November 2022.This study included individuals with chronic conditions from 16 primary care centers in Thailand.We tested the structural validity using exploratory factor analysis(EFA)and confirmatory factor analysis(CFA),and concurrent validity in relation to the Self-Care of Chronic Illness Inventory version 4.c(SC-CII-v4.c).We tested the scale’s reliability with McDonald’s u,Cronbach’s a,and the intraclass correlation coefficient(ICC).Results:The Thai SCSES-v3.0 demonstrated excellent content validity(k¼1.00).Thefinal analysis included a total of 385 participants.The EFA with thefirst split-half subsample(n¼193)extracted a twofactor structure.One reflected SCSES for maintenance and monitoring behaviors and another captured SCSES for management behaviors(item 6e10).CFA with the second split-half subsample(n¼192)and the overall sample(n¼385)supported the scale’s two-factor model with high factor loadings.Each dimension and the overall SCSES-v3.0 positively correlated with each scale and the overall SC-CII-v4.c.McDonald’s u and Cronbach’s a(both ranged 0.91e0.94)and ICC(ranged 0.95e0.96),indicated excellent internal reliability and test-retest reliability,respectively.Conclusions:The identification of a valid and reliable two-factor model for the Thai SCSES-v3.0 renders it a valuable tool for clinicians and investigators,facilitating the assessment of self-efficacy in self-care across diverse contexts.展开更多
Videos represent the most prevailing form of digital media for communication,information dissemination,and monitoring.However,theirwidespread use has increased the risks of unauthorised access andmanipulation,posing s...Videos represent the most prevailing form of digital media for communication,information dissemination,and monitoring.However,theirwidespread use has increased the risks of unauthorised access andmanipulation,posing significant challenges.In response,various protection approaches have been developed to secure,authenticate,and ensure the integrity of digital videos.This study provides a comprehensive survey of the challenges associated with maintaining the confidentiality,integrity,and availability of video content,and examining how it can be manipulated.It then investigates current developments in the field of video security by exploring two critical research questions.First,it examine the techniques used by adversaries to compromise video data and evaluate their impact.Understanding these attack methodologies is crucial for developing effective defense mechanisms.Second,it explores the various security approaches that can be employed to protect video data,enhancing its transparency,integrity,and trustworthiness.It compares the effectiveness of these approaches across different use cases,including surveillance,video on demand(VoD),and medical videos related to disease diagnostics.Finally,it identifies potential research opportunities to enhance video data protection in response to the evolving threat landscape.Through this investigation,this study aims to contribute to the ongoing efforts in securing video data,providing insights that are vital for researchers,practitioners,and policymakers dedicated to enhancing the safety and reliability of video content in our digital world.展开更多
Database systems have consistently been prime targets for cyber-attacks and threats due to the critical nature of the data they store.Despite the increasing reliance on database management systems,this field continues...Database systems have consistently been prime targets for cyber-attacks and threats due to the critical nature of the data they store.Despite the increasing reliance on database management systems,this field continues to face numerous cyber-attacks.Database management systems serve as the foundation of any information system or application.Any cyber-attack can result in significant damage to the database system and loss of sensitive data.Consequently,cyber risk classifications and assessments play a crucial role in risk management and establish an essential framework for identifying and responding to cyber threats.Risk assessment aids in understanding the impact of cyber threats and developing appropriate security controls to mitigate risks.The primary objective of this study is to conduct a comprehensive analysis of cyber risks in database management systems,including classifying threats,vulnerabilities,impacts,and countermeasures.This classification helps to identify suitable security controls to mitigate cyber risks for each type of threat.Additionally,this research aims to explore technical countermeasures to protect database systems from cyber threats.This study employs the content analysis method to collect,analyze,and classify data in terms of types of threats,vulnerabilities,and countermeasures.The results indicate that SQL injection attacks and Denial of Service(DoS)attacks were the most prevalent technical threats in database systems,each accounting for 9%of incidents.Vulnerable audit trails,intrusion attempts,and ransomware attacks were classified as the second level of technical threats in database systems,comprising 7%and 5%of incidents,respectively.Furthermore,the findings reveal that insider threats were the most common non-technical threats in database systems,accounting for 5%of incidents.Moreover,the results indicate that weak authentication,unpatched databases,weak audit trails,and multiple usage of an account were the most common technical vulnerabilities in database systems,each accounting for 9%of vulnerabilities.Additionally,software bugs,insecure coding practices,weak security controls,insecure networks,password misuse,weak encryption practices,and weak data masking were classified as the second level of security vulnerabilities in database systems,each accounting for 4%of vulnerabilities.The findings from this work can assist organizations in understanding the types of cyber threats and developing robust strategies against cyber-attacks.展开更多
The increase in number of people using the Internet leads to increased cyberattack opportunities.Advanced Persistent Threats,or APTs,are among the most dangerous targeted cyberattacks.APT attacks utilize various advan...The increase in number of people using the Internet leads to increased cyberattack opportunities.Advanced Persistent Threats,or APTs,are among the most dangerous targeted cyberattacks.APT attacks utilize various advanced tools and techniques for attacking targets with specific goals.Even countries with advanced technologies,like the US,Russia,the UK,and India,are susceptible to this targeted attack.APT is a sophisticated attack that involves multiple stages and specific strategies.Besides,TTP(Tools,Techniques,and Procedures)involved in the APT attack are commonly new and developed by an attacker to evade the security system.However,APTs are generally implemented in multiple stages.If one of the stages is detected,we may apply a defense mechanism for subsequent stages,leading to the entire APT attack failure.The detection at the early stage of APT and the prediction of the next step in the APT kill chain are ongoing challenges.This survey paper will provide knowledge about APT attacks and their essential steps.This follows the case study of known APT attacks,which will give clear information about the APT attack process—in later sections,highlighting the various detection methods defined by different researchers along with the limitations of the work.Data used in this article comes from the various annual reports published by security experts and blogs and information released by the enterprise networks targeted by the attack.展开更多
Unmanned autonomous helicopter(UAH)path planning problem is an important component of the UAH mission planning system.Aiming to reduce the influence of non-complete ground threat information on UAH path planning,a gro...Unmanned autonomous helicopter(UAH)path planning problem is an important component of the UAH mission planning system.Aiming to reduce the influence of non-complete ground threat information on UAH path planning,a ground threat prediction-based path planning method is proposed based on artificial bee colony(ABC)algorithm by collaborative thinking strategy.Firstly,a dynamic threat distribution probability model is developed based on the characteristics of typical ground threats.The dynamic no-fly zone of the UAH is simulated and established by calculating the distribution probability of ground threats in real time.Then,a dynamic path planning method for UAH is designed in complex environment based on the real-time prediction of ground threats.By adding the collision warning mechanism to the path planning model,the flight path could be dynamically adjusted according to changing no-fly zones.Furthermore,a hybrid enhanced ABC algorithm is proposed based on collaborative thinking strategy.The proposed algorithm applies the leader-member thinking mechanism to guide the direction of population evolution,and reduces the negative impact of local optimal solutions caused by collaborative learning update strategy,which makes the optimization performance of ABC algorithm more controllable and efficient.Finally,simulation results verify the feasibility and effectiveness of the proposed ground threat prediction path planning method.展开更多
In the tobacco industry,insider employee attack is a thorny problem that is difficult to detect.To solve this issue,this paper proposes an insider threat detection method based on heterogeneous graph embedding.First,t...In the tobacco industry,insider employee attack is a thorny problem that is difficult to detect.To solve this issue,this paper proposes an insider threat detection method based on heterogeneous graph embedding.First,the interrelationships between logs are fully considered,and log entries are converted into heterogeneous graphs based on these relationships.Second,the heterogeneous graph embedding is adopted and each log entry is represented as a low-dimensional feature vector.Then,normal logs and malicious logs are classified into different clusters by clustering algorithm to identify malicious logs.Finally,the effectiveness and superiority of the method is verified through experiments on the CERT dataset.The experimental results show that this method has better performance compared to some baseline methods.展开更多
Considering the increased anthropogenic impacts,species with a limited range and low detectability often lack fundamental information and conservation actions,placing them at a high risk of endangerment.The Chinting a...Considering the increased anthropogenic impacts,species with a limited range and low detectability often lack fundamental information and conservation actions,placing them at a high risk of endangerment.The Chinting alpine toad Scutiger chintingensis is a rare mountain amphibian endemic to the eastern margin of the Qinghai-Xizang Plateau in China.Within its whole distribution range,only three known populations(Wolong,Emei,and Wawu)exist and no recent population status report has been documented for this species over the past two decades.From 2020 to 2023,we investigated the species distribution,and assessed the risk factors for the main populations.We recorded this species in all distribution areas,and updated a new distribution site with a lower elevation limit.The relative population density was 0.024±0.012 ind./m^(2)on Mount Emei,whereas only 0.008±0.017 ind./m^(2)on Mount Wawu.No significant difference was observed in the number of individuals between the two populations;however,the relative population density was significantly different.Sewage and waste discharge resulting from the construction of scenic areas,as well as disturbances from tourism,were the primary anthropogenic factors that influenced the survival of this species.Our results provide the updated information on the distribution and population status of the Chinting alpine toad,and suggest that unrecorded populations,as well as a wider elevation range,may exist for this species.Our findings emphasise the importance of timely updates of species distribution and population information and offer a basis for the future conservation of endangered amphibians.展开更多
Information technology is critical in coordinating patient records, smart devices, operations, and critical infrastructure in healthcare organizations, and their constantly changing digital environment, including supp...Information technology is critical in coordinating patient records, smart devices, operations, and critical infrastructure in healthcare organizations, and their constantly changing digital environment, including suppliers, doctors, insurance providers, and regulatory agencies. This dependence on interdependent systems makes this sector vulnerable to various information technology risks. Such threats include common cybersecurity risks such as data breaches and malware attacks, unique problems occurring in healthcare settings such as unauthorized access to patient records, disruptions in services provided at medical facilities, and potential harm caused to patients due to the compromise of medical devices. The threat taxonomies, such as the Open Threat Taxonomy, NIST, or ENISA, are foundational frameworks for grasping and categorizing IT threats. However, these taxonomies were not specifically designed to deal with the complexities of the healthcare industry. The problem arises from the gap between these taxonomies’ general nature and the industry-specific threats and vulnerabilities that affect healthcare organizations. As a result, many healthcare institutions fail to holistically address and eliminate the unique risks related to confidentiality, integrity, and availability of patients’ data as well as critical systems used in healthcare. This paper aims to narrow this gap by carefully assessing these taxonomies to determine the frame-work best suited for addressing the threat environment in the healthcare sector.展开更多
Background:Coping self-efficacy can help individuals mitigate the adverse emotional impacts of stress,anxiety,and other negative emotions,and it also influences individuals’academic performance,including school adjus...Background:Coping self-efficacy can help individuals mitigate the adverse emotional impacts of stress,anxiety,and other negative emotions,and it also influences individuals’academic performance,including school adjustment and academic burnout.It is an important factor affecting the mental health of adolescents.However,there is no measurement tool specifically designed for adolescent populations in China.Therefore,the purpose of this study is to assess the applicability of the Coping Self-Efficacy Scale(CSES)among Chinese adolescents.Methods:In September 2023,this study collected data through online questionnaires and ultimately conducted item analysis,exploratory factor analysis,confirmatory factor analysis(CFA),measurement invariance analysis,reliability analysis,and criterion-related validity analysis on a sample of 1157 adolescents.Results:The results of item analysis showed that the items of CSES were significantly different between the high and low groups.Further factor analysis results showed the existence of a factor solution that explained 59.09%of the total variation,with factor loadings ranging from 0.52–0.78.CFA supported the three-factor model of Chinese adolescent version of the CSES(CFI=0.923,TLI=0.914,IFI=0.923,RMSEA=0.068).Measurement invariance analysis indicates that the scale satisfies gender measurement invariance(ΔCFI=-0.002,-0.001>-0.01,ΔRMSEA=-0.001,0<0.02,ΔSRMR=0.005,0.007<0.01).The Chinese adolescent version of the CSES was positively correlated with the Social Support Appraisal Scale(SS-A)and the Life Orientation Test-Revised(LOT-R,r=0.670,0.673,both p<0.01),and negatively correlated with the Chinese Perceived Stress Scale(CPSS),the State-Trait Anxiety Inventory(STAI)and the Adolescent Student Burnout Inventory(ASBI,r=-0.694,-0.233,-0.680,both p<0.01).The Cronbach’sα,McDonald’sω,split-half reliability and test-retest reliability of the Chinese adolescent version of the CSES were 0.953,0.955,0.933 and 0.894,respectively.Conclusion:The results indicate that the three-factor model of the Chinese adolescent version of the CSES is acceptable and demonstrates high reliability and validity,establishing it as a precise tool for measuring and assessing coping self-efficacy among Chinese adolescents.展开更多
Although AI and quantum computing (QC) are fast emerging as key enablers of the future Internet, experts believe they pose an existential threat to humanity. Responding to the frenzied release of ChatGPT/GPT-4, thousa...Although AI and quantum computing (QC) are fast emerging as key enablers of the future Internet, experts believe they pose an existential threat to humanity. Responding to the frenzied release of ChatGPT/GPT-4, thousands of alarmed tech leaders recently signed an open letter to pause AI research to prepare for the catastrophic threats to humanity from uncontrolled AGI (Artificial General Intelligence). Perceived as an “epistemological nightmare”, AGI is believed to be on the anvil with GPT-5. Two computing rules appear responsible for these risks. 1) Mandatory third-party permissions that allow computers to run applications at the expense of introducing vulnerabilities. 2) The Halting Problem of Turing-complete AI programming languages potentially renders AGI unstoppable. The double whammy of these inherent weaknesses remains invincible under the legacy systems. A recent cybersecurity breakthrough shows that banning all permissions reduces the computer attack surface to zero, delivering a new zero vulnerability computing (ZVC) paradigm. Deploying ZVC and blockchain, this paper formulates and supports a hypothesis: “Safe, secure, ethical, controllable AGI/QC is possible by conquering the two unassailable rules of computability.” Pursued by a European consortium, testing/proving the proposed hypothesis will have a groundbreaking impact on the future digital infrastructure when AGI/QC starts powering the 75 billion internet devices by 2025.展开更多
Estimated at more than 2.2 million cases worldwide,most breast cancer cases and deaths from breast cancer occur in low and middle-income countries.In Cameroon,many studies have underlined the effect of knowledge of br...Estimated at more than 2.2 million cases worldwide,most breast cancer cases and deaths from breast cancer occur in low and middle-income countries.In Cameroon,many studies have underlined the effect of knowledge of breast cancer on screening measures such as self-examination and,to a lesser extent,the perception of the threat of this disease.This research aims to assess according to the Health Belief Model(HBM),the moderating effect of perceived threat of breast cancer on the relation between knowledge and breast self-examination.A questionnaire survey was conducted among 517 Cameroonian women to assess their general knowledge about breast cancer(risk factors and screening measures),their level of the perceived threat of breast cancer through Perceived susceptibility and severity,and the prevalence of breast self-examination amongst them.A regression analysis using the Macro Process for moderation indicates the main effect of Perceived threat(b=0,29;t(517)=2,36;p=0,02)of breast cancer and knowledge(b=0,02;t(517)=4,29;p<0,001)on breast self-examination.Results also confirm that the perceived threat of breast cancer moderates the effect of knowledge on breast self-examination.While the low level of perceived threat highlights the effect of knowledge on breast self-examination(b=0,02;t(517)=3,49;p<0,001),the high level of perceived threat cancels that effect(b=0,01;t(517)=1,97;p=0,01).A woman who perceives severity and susceptibility to breast cancer is more inclined to perform breast self-examination.This result suggests the importance of taking into account,in a context where knowledge of breast cancer is limited,relevant factors of the health belief model in preventive measures against breast cancer in general and the practice of breast self-examination in particular.展开更多
As the Internet of Things(IoT)continues to expand,incorporating a vast array of devices into a digital ecosystem also increases the risk of cyber threats,necessitating robust defense mechanisms.This paper presents an ...As the Internet of Things(IoT)continues to expand,incorporating a vast array of devices into a digital ecosystem also increases the risk of cyber threats,necessitating robust defense mechanisms.This paper presents an innovative hybrid deep learning architecture that excels at detecting IoT threats in real-world settings.Our proposed model combines Convolutional Neural Networks(CNN),Bidirectional Long Short-Term Memory(BLSTM),Gated Recurrent Units(GRU),and Attention mechanisms into a cohesive framework.This integrated structure aims to enhance the detection and classification of complex cyber threats while accommodating the operational constraints of diverse IoT systems.We evaluated our model using the RT-IoT2022 dataset,which includes various devices,standard operations,and simulated attacks.Our research’s significance lies in the comprehensive evaluation metrics,including Cohen Kappa and Matthews Correlation Coefficient(MCC),which underscore the model’s reliability and predictive quality.Our model surpassed traditional machine learning algorithms and the state-of-the-art,achieving over 99.6%precision,recall,F1-score,False Positive Rate(FPR),Detection Time,and accuracy,effectively identifying specific threats such as Message Queuing Telemetry Transport(MQTT)Publish,Denial of Service Synchronize network packet crafting tool(DOS SYN Hping),and Network Mapper Operating System Detection(NMAP OS DETECTION).The experimental analysis reveals a significant improvement over existing detection systems,significantly enhancing IoT security paradigms.Through our experimental analysis,we have demonstrated a remarkable enhancement in comparison to existing detection systems,which significantly strength-ens the security standards of IoT.Our model effectively addresses the need for advanced,dependable,and adaptable security solutions,serving as a symbol of the power of deep learning in strengthening IoT ecosystems amidst the constantly evolving cyber threat landscape.This achievement marks a significant stride towards protecting the integrity of IoT infrastructure,ensuring operational resilience,and building privacy in this groundbreaking technology.展开更多
Aerial threat assessment is a crucial link in modern air combat, whose result counts a great deal for commanders to make decisions. With the consideration that the existing threat assessment methods have difficulties ...Aerial threat assessment is a crucial link in modern air combat, whose result counts a great deal for commanders to make decisions. With the consideration that the existing threat assessment methods have difficulties in dealing with high dimensional time series target data, a threat assessment method based on self-attention mechanism and gated recurrent unit(SAGRU) is proposed. Firstly, a threat feature system including air combat situations and capability features is established. Moreover, a data augmentation process based on fractional Fourier transform(FRFT) is applied to extract more valuable information from time series situation features. Furthermore, aiming to capture key characteristics of battlefield evolution, a bidirectional GRU and SA mechanisms are designed for enhanced features.Subsequently, after the concatenation of the processed air combat situation and capability features, the target threat level will be predicted by fully connected neural layers and the softmax classifier. Finally, in order to validate this model, an air combat dataset generated by a combat simulation system is introduced for model training and testing. The comparison experiments show the proposed model has structural rationality and can perform threat assessment faster and more accurately than the other existing models based on deep learning.展开更多
The Unintentional Insider Threat (UIT) concept highlights that insider threats might not always stem from malicious intent and can occur across various domains. This research examines how individuals with medical or p...The Unintentional Insider Threat (UIT) concept highlights that insider threats might not always stem from malicious intent and can occur across various domains. This research examines how individuals with medical or psychological issues might unintentionally become insider threats due to their perception of being targeted. Insights from the survey A Survey of Unintentional Medical Insider Threat Category indicate that such perceptions can be linked to underlying health conditions. The study Emotion Analysis Based on Belief of Targeted Individual Supporting Insider Threat Detection reveals that anger is a common emotion among these individuals. The findings suggest that UITs are often linked to medical or psychological issues, with anger being prevalent. To mitigate these risks, it is recommended that Insider Threat programs integrate expertise from medicine, psychology, and cybersecurity. Additionally, handwriting analysis is proposed as a potential tool for detecting insider threats, reflecting the evolving nature of threat assessment methodologies.展开更多
Self-efficacy plays an important role in the management of type 2 diabetes mellitus (T2DM) patients, and it runs through the whole process of diabetes treatment, which is conducive to controlling and delaying the occu...Self-efficacy plays an important role in the management of type 2 diabetes mellitus (T2DM) patients, and it runs through the whole process of diabetes treatment, which is conducive to controlling and delaying the occurrence and development of complications, as well as improving the quality of life of patients. This paper mainly describes the concept of self-efficacy, the current situation of self-efficacy of diabetic patients at home and abroad, the functional aspects and their influencing factors, so as to take relevant measures on how to improve self-efficacy. It aims to provide a theoretical basis for the development of self-efficacy interventions for patients with type 2 diabetes mellitus.展开更多
This literature review primarily aims to explore and synthesise the previous studies in simulation education research conducted over the past five years related to the effects of simulation training on the self-effica...This literature review primarily aims to explore and synthesise the previous studies in simulation education research conducted over the past five years related to the effects of simulation training on the self-efficacy of undergraduate pre-registration nursing students. The second aim of this study is to explore additional outcome variables that were examined in the previous studies. Five electronic databases were searched systematically. These databases were MEDLINE, CINAHL Plus, Scopus, Embase and PsycINFO. The PICO model was employed to identify the search terms, with a thesaurus being used to provide synonyms. Reference lists of relevant articles were examined and hand searches of journals were also undertaken. The quality of each study was assessed using the Simulation Research Rubric (SRR). A total of 11 studies were included. All studies explored the impact of simulation education on undergraduate pre-registration nursing. Six studies explored nursing students’ competence and performance and two papers examined their critical thinking. Problem solving, learning motivation, communication skills and knowledge acquisition were examined once. The majority of studies indicated that simulation training has a positive impact on pre-registration nursing students’ self-efficacy and other outcome variables. Furthermore, the study results indicate that simulation training is more dependable than traditional training, and students were extremely satisfied with the simulation training. However, most of the studies included in this review had several gaps, including study design, sample size and dissimilarities between the scales used. Further research with large samples, reliable and valid instruments, and outcomes measures (such as critical thinking and transferability of skills) is required to provide better insight into the effectiveness of simulation in undergraduate nursing education. .展开更多
Cloud computing plays a significant role in modern information technology, providing organizations with numerous benefits, including flexibility, scalability, and cost-efficiency. However, it has become essential for ...Cloud computing plays a significant role in modern information technology, providing organizations with numerous benefits, including flexibility, scalability, and cost-efficiency. However, it has become essential for organizations to ensure the security of their applications, data, and cloud-based networks to use cloud services effectively. This systematic literature review aims to determine the latest information regarding cloud computing security, with a specific emphasis on threats and mitigation strategies. Additionally, it highlights some common threats related to cloud computing security, such as distributed denial-of-service (DDoS) attacks, account hijacking, malware attacks, and data breaches. This research also explores some mitigation strategies, including security awareness training, vulnerability management, security information and event management (SIEM), identity and access management (IAM), and encryption techniques. It discusses emerging trends in cloud security, such as integrating artificial intelligence (AI) and machine learning (ML), serverless computing, and containerization, as well as the effectiveness of the shared responsibility model and its related challenges. The importance of user awareness and the impact of emerging technologies on cloud security have also been discussed in detail to mitigate security risks. A literature review of previous research and scholarly articles has also been conducted to provide insights regarding cloud computing security. It shows the need for continuous research and innovation to address emerging threats and maintain a security-conscious culture in the company.展开更多
As cyber threats keep changing and business environments adapt, a comprehensive approach to disaster recovery involves more than just defensive measures. This research delves deep into the strategies required to respo...As cyber threats keep changing and business environments adapt, a comprehensive approach to disaster recovery involves more than just defensive measures. This research delves deep into the strategies required to respond to threats and anticipate and mitigate them proactively. Beginning with understanding the critical need for a layered defense and the intricacies of the attacker’s journey, the research offers insights into specialized defense techniques, emphasizing the importance of timely and strategic responses during incidents. Risk management is brought to the forefront, underscoring businesses’ need to adopt mature risk assessment practices and understand the potential risk impact areas. Additionally, the value of threat intelligence is explored, shedding light on the importance of active engagement within sharing communities and the vigilant observation of adversary motivations. “Beyond Defense: Proactive Approaches to Disaster Recovery and Threat Intelligence in Modern Enterprises” is a comprehensive guide for organizations aiming to fortify their cybersecurity posture, marrying best practices in proactive and reactive measures in the ever-challenging digital realm.展开更多
文摘The Industrial Internet of Things(IIoT)has brought numerous benefits,such as improved efficiency,smart analytics,and increased automation.However,it also exposes connected devices,users,applications,and data generated to cyber security threats that need to be addressed.This work investigates hybrid cyber threats(HCTs),which are now working on an entirely new level with the increasingly adopted IIoT.This work focuses on emerging methods to model,detect,and defend against hybrid cyber attacks using machine learning(ML)techniques.Specifically,a novel ML-based HCT modelling and analysis framework was proposed,in which L1 regularisation and Random Forest were used to cluster features and analyse the importance and impact of each feature in both individual threats and HCTs.A grey relation analysis-based model was employed to construct the correlation between IIoT components and different threats.
文摘This paper examines how cybersecurity is developing and how it relates to more conventional information security. Although information security and cyber security are sometimes used synonymously, this study contends that they are not the same. The concept of cyber security is explored, which goes beyond protecting information resources to include a wider variety of assets, including people [1]. Protecting information assets is the main goal of traditional information security, with consideration to the human element and how people fit into the security process. On the other hand, cyber security adds a new level of complexity, as people might unintentionally contribute to or become targets of cyberattacks. This aspect presents moral questions since it is becoming more widely accepted that society has a duty to protect weaker members of society, including children [1]. The study emphasizes how important cyber security is on a larger scale, with many countries creating plans and laws to counteract cyberattacks. Nevertheless, a lot of these sources frequently neglect to define the differences or the relationship between information security and cyber security [1]. The paper focus on differentiating between cybersecurity and information security on a larger scale. The study also highlights other areas of cybersecurity which includes defending people, social norms, and vital infrastructure from threats that arise from online in addition to information and technology protection. It contends that ethical issues and the human factor are becoming more and more important in protecting assets in the digital age, and that cyber security is a paradigm shift in this regard [1].
基金The original study wasfinancially supported by Walailak University(grant number:WU65240,Year 2022).
文摘Objective:To assess the psychometric properties of the Thai version of the Self-Care Self-Efficacy Scale version 3.0(SCSES-v3.0)in individuals with chronic illnesses.Although originally developed and tested in a Western context,its applicability in Asian populations,including Thailand,remains inadequately explored.Methods:Psychometric tests were guided by COSMIN principles.This included the translation of the English version into Thai based on the ISPOR framework.Nine nursing experts evaluated the content validity.Data were obtained from a multicenter cross-sectional study conducted between July and November 2022.This study included individuals with chronic conditions from 16 primary care centers in Thailand.We tested the structural validity using exploratory factor analysis(EFA)and confirmatory factor analysis(CFA),and concurrent validity in relation to the Self-Care of Chronic Illness Inventory version 4.c(SC-CII-v4.c).We tested the scale’s reliability with McDonald’s u,Cronbach’s a,and the intraclass correlation coefficient(ICC).Results:The Thai SCSES-v3.0 demonstrated excellent content validity(k¼1.00).Thefinal analysis included a total of 385 participants.The EFA with thefirst split-half subsample(n¼193)extracted a twofactor structure.One reflected SCSES for maintenance and monitoring behaviors and another captured SCSES for management behaviors(item 6e10).CFA with the second split-half subsample(n¼192)and the overall sample(n¼385)supported the scale’s two-factor model with high factor loadings.Each dimension and the overall SCSES-v3.0 positively correlated with each scale and the overall SC-CII-v4.c.McDonald’s u and Cronbach’s a(both ranged 0.91e0.94)and ICC(ranged 0.95e0.96),indicated excellent internal reliability and test-retest reliability,respectively.Conclusions:The identification of a valid and reliable two-factor model for the Thai SCSES-v3.0 renders it a valuable tool for clinicians and investigators,facilitating the assessment of self-efficacy in self-care across diverse contexts.
基金funded by the European Union’s Horizon 2020 Research and Innovation Programme under the Marie Skłodowska-Curie Action(MSCA)grant agreement No.101109961.
文摘Videos represent the most prevailing form of digital media for communication,information dissemination,and monitoring.However,theirwidespread use has increased the risks of unauthorised access andmanipulation,posing significant challenges.In response,various protection approaches have been developed to secure,authenticate,and ensure the integrity of digital videos.This study provides a comprehensive survey of the challenges associated with maintaining the confidentiality,integrity,and availability of video content,and examining how it can be manipulated.It then investigates current developments in the field of video security by exploring two critical research questions.First,it examine the techniques used by adversaries to compromise video data and evaluate their impact.Understanding these attack methodologies is crucial for developing effective defense mechanisms.Second,it explores the various security approaches that can be employed to protect video data,enhancing its transparency,integrity,and trustworthiness.It compares the effectiveness of these approaches across different use cases,including surveillance,video on demand(VoD),and medical videos related to disease diagnostics.Finally,it identifies potential research opportunities to enhance video data protection in response to the evolving threat landscape.Through this investigation,this study aims to contribute to the ongoing efforts in securing video data,providing insights that are vital for researchers,practitioners,and policymakers dedicated to enhancing the safety and reliability of video content in our digital world.
基金supported by the Deanship of Scientific Research,Vice Presidency for Graduate Studies and Scientific Research,King Faisal University,Saudi Arabia(Grant No.KFU242068).
文摘Database systems have consistently been prime targets for cyber-attacks and threats due to the critical nature of the data they store.Despite the increasing reliance on database management systems,this field continues to face numerous cyber-attacks.Database management systems serve as the foundation of any information system or application.Any cyber-attack can result in significant damage to the database system and loss of sensitive data.Consequently,cyber risk classifications and assessments play a crucial role in risk management and establish an essential framework for identifying and responding to cyber threats.Risk assessment aids in understanding the impact of cyber threats and developing appropriate security controls to mitigate risks.The primary objective of this study is to conduct a comprehensive analysis of cyber risks in database management systems,including classifying threats,vulnerabilities,impacts,and countermeasures.This classification helps to identify suitable security controls to mitigate cyber risks for each type of threat.Additionally,this research aims to explore technical countermeasures to protect database systems from cyber threats.This study employs the content analysis method to collect,analyze,and classify data in terms of types of threats,vulnerabilities,and countermeasures.The results indicate that SQL injection attacks and Denial of Service(DoS)attacks were the most prevalent technical threats in database systems,each accounting for 9%of incidents.Vulnerable audit trails,intrusion attempts,and ransomware attacks were classified as the second level of technical threats in database systems,comprising 7%and 5%of incidents,respectively.Furthermore,the findings reveal that insider threats were the most common non-technical threats in database systems,accounting for 5%of incidents.Moreover,the results indicate that weak authentication,unpatched databases,weak audit trails,and multiple usage of an account were the most common technical vulnerabilities in database systems,each accounting for 9%of vulnerabilities.Additionally,software bugs,insecure coding practices,weak security controls,insecure networks,password misuse,weak encryption practices,and weak data masking were classified as the second level of security vulnerabilities in database systems,each accounting for 4%of vulnerabilities.The findings from this work can assist organizations in understanding the types of cyber threats and developing robust strategies against cyber-attacks.
文摘The increase in number of people using the Internet leads to increased cyberattack opportunities.Advanced Persistent Threats,or APTs,are among the most dangerous targeted cyberattacks.APT attacks utilize various advanced tools and techniques for attacking targets with specific goals.Even countries with advanced technologies,like the US,Russia,the UK,and India,are susceptible to this targeted attack.APT is a sophisticated attack that involves multiple stages and specific strategies.Besides,TTP(Tools,Techniques,and Procedures)involved in the APT attack are commonly new and developed by an attacker to evade the security system.However,APTs are generally implemented in multiple stages.If one of the stages is detected,we may apply a defense mechanism for subsequent stages,leading to the entire APT attack failure.The detection at the early stage of APT and the prediction of the next step in the APT kill chain are ongoing challenges.This survey paper will provide knowledge about APT attacks and their essential steps.This follows the case study of known APT attacks,which will give clear information about the APT attack process—in later sections,highlighting the various detection methods defined by different researchers along with the limitations of the work.Data used in this article comes from the various annual reports published by security experts and blogs and information released by the enterprise networks targeted by the attack.
文摘Unmanned autonomous helicopter(UAH)path planning problem is an important component of the UAH mission planning system.Aiming to reduce the influence of non-complete ground threat information on UAH path planning,a ground threat prediction-based path planning method is proposed based on artificial bee colony(ABC)algorithm by collaborative thinking strategy.Firstly,a dynamic threat distribution probability model is developed based on the characteristics of typical ground threats.The dynamic no-fly zone of the UAH is simulated and established by calculating the distribution probability of ground threats in real time.Then,a dynamic path planning method for UAH is designed in complex environment based on the real-time prediction of ground threats.By adding the collision warning mechanism to the path planning model,the flight path could be dynamically adjusted according to changing no-fly zones.Furthermore,a hybrid enhanced ABC algorithm is proposed based on collaborative thinking strategy.The proposed algorithm applies the leader-member thinking mechanism to guide the direction of population evolution,and reduces the negative impact of local optimal solutions caused by collaborative learning update strategy,which makes the optimization performance of ABC algorithm more controllable and efficient.Finally,simulation results verify the feasibility and effectiveness of the proposed ground threat prediction path planning method.
基金Supported by the National Natural Science Foundation of China(No.62203390)the Science and Technology Project of China TobaccoZhejiang Industrial Co.,Ltd(No.ZJZY2022E004)。
文摘In the tobacco industry,insider employee attack is a thorny problem that is difficult to detect.To solve this issue,this paper proposes an insider threat detection method based on heterogeneous graph embedding.First,the interrelationships between logs are fully considered,and log entries are converted into heterogeneous graphs based on these relationships.Second,the heterogeneous graph embedding is adopted and each log entry is represented as a low-dimensional feature vector.Then,normal logs and malicious logs are classified into different clusters by clustering algorithm to identify malicious logs.Finally,the effectiveness and superiority of the method is verified through experiments on the CERT dataset.The experimental results show that this method has better performance compared to some baseline methods.
基金supported by the National Natural Science Foundation of China(32271737,32071544)the Interdisciplinary Innovation Team of the Chinese Academy of Sciences(CAS)“Light of West China”Program(xbzg-zdsys-202207)+1 种基金the Shenzhen Zhilan Foundation(2021070451A)Nature Science Foundation of Sichuan Province(2022NSFSC0125).
文摘Considering the increased anthropogenic impacts,species with a limited range and low detectability often lack fundamental information and conservation actions,placing them at a high risk of endangerment.The Chinting alpine toad Scutiger chintingensis is a rare mountain amphibian endemic to the eastern margin of the Qinghai-Xizang Plateau in China.Within its whole distribution range,only three known populations(Wolong,Emei,and Wawu)exist and no recent population status report has been documented for this species over the past two decades.From 2020 to 2023,we investigated the species distribution,and assessed the risk factors for the main populations.We recorded this species in all distribution areas,and updated a new distribution site with a lower elevation limit.The relative population density was 0.024±0.012 ind./m^(2)on Mount Emei,whereas only 0.008±0.017 ind./m^(2)on Mount Wawu.No significant difference was observed in the number of individuals between the two populations;however,the relative population density was significantly different.Sewage and waste discharge resulting from the construction of scenic areas,as well as disturbances from tourism,were the primary anthropogenic factors that influenced the survival of this species.Our results provide the updated information on the distribution and population status of the Chinting alpine toad,and suggest that unrecorded populations,as well as a wider elevation range,may exist for this species.Our findings emphasise the importance of timely updates of species distribution and population information and offer a basis for the future conservation of endangered amphibians.
文摘Information technology is critical in coordinating patient records, smart devices, operations, and critical infrastructure in healthcare organizations, and their constantly changing digital environment, including suppliers, doctors, insurance providers, and regulatory agencies. This dependence on interdependent systems makes this sector vulnerable to various information technology risks. Such threats include common cybersecurity risks such as data breaches and malware attacks, unique problems occurring in healthcare settings such as unauthorized access to patient records, disruptions in services provided at medical facilities, and potential harm caused to patients due to the compromise of medical devices. The threat taxonomies, such as the Open Threat Taxonomy, NIST, or ENISA, are foundational frameworks for grasping and categorizing IT threats. However, these taxonomies were not specifically designed to deal with the complexities of the healthcare industry. The problem arises from the gap between these taxonomies’ general nature and the industry-specific threats and vulnerabilities that affect healthcare organizations. As a result, many healthcare institutions fail to holistically address and eliminate the unique risks related to confidentiality, integrity, and availability of patients’ data as well as critical systems used in healthcare. This paper aims to narrow this gap by carefully assessing these taxonomies to determine the frame-work best suited for addressing the threat environment in the healthcare sector.
基金supported by the National Natural Science Foundation of China,Grant No.31800913(to Kaiyun Li),Grant No.32100856(to Fanlu Jia)Youth Innovation Team of Shandong Provincial Higher Education Institutions,Grant No.2022RW019(to Fanlu Jia).
文摘Background:Coping self-efficacy can help individuals mitigate the adverse emotional impacts of stress,anxiety,and other negative emotions,and it also influences individuals’academic performance,including school adjustment and academic burnout.It is an important factor affecting the mental health of adolescents.However,there is no measurement tool specifically designed for adolescent populations in China.Therefore,the purpose of this study is to assess the applicability of the Coping Self-Efficacy Scale(CSES)among Chinese adolescents.Methods:In September 2023,this study collected data through online questionnaires and ultimately conducted item analysis,exploratory factor analysis,confirmatory factor analysis(CFA),measurement invariance analysis,reliability analysis,and criterion-related validity analysis on a sample of 1157 adolescents.Results:The results of item analysis showed that the items of CSES were significantly different between the high and low groups.Further factor analysis results showed the existence of a factor solution that explained 59.09%of the total variation,with factor loadings ranging from 0.52–0.78.CFA supported the three-factor model of Chinese adolescent version of the CSES(CFI=0.923,TLI=0.914,IFI=0.923,RMSEA=0.068).Measurement invariance analysis indicates that the scale satisfies gender measurement invariance(ΔCFI=-0.002,-0.001>-0.01,ΔRMSEA=-0.001,0<0.02,ΔSRMR=0.005,0.007<0.01).The Chinese adolescent version of the CSES was positively correlated with the Social Support Appraisal Scale(SS-A)and the Life Orientation Test-Revised(LOT-R,r=0.670,0.673,both p<0.01),and negatively correlated with the Chinese Perceived Stress Scale(CPSS),the State-Trait Anxiety Inventory(STAI)and the Adolescent Student Burnout Inventory(ASBI,r=-0.694,-0.233,-0.680,both p<0.01).The Cronbach’sα,McDonald’sω,split-half reliability and test-retest reliability of the Chinese adolescent version of the CSES were 0.953,0.955,0.933 and 0.894,respectively.Conclusion:The results indicate that the three-factor model of the Chinese adolescent version of the CSES is acceptable and demonstrates high reliability and validity,establishing it as a precise tool for measuring and assessing coping self-efficacy among Chinese adolescents.
文摘Although AI and quantum computing (QC) are fast emerging as key enablers of the future Internet, experts believe they pose an existential threat to humanity. Responding to the frenzied release of ChatGPT/GPT-4, thousands of alarmed tech leaders recently signed an open letter to pause AI research to prepare for the catastrophic threats to humanity from uncontrolled AGI (Artificial General Intelligence). Perceived as an “epistemological nightmare”, AGI is believed to be on the anvil with GPT-5. Two computing rules appear responsible for these risks. 1) Mandatory third-party permissions that allow computers to run applications at the expense of introducing vulnerabilities. 2) The Halting Problem of Turing-complete AI programming languages potentially renders AGI unstoppable. The double whammy of these inherent weaknesses remains invincible under the legacy systems. A recent cybersecurity breakthrough shows that banning all permissions reduces the computer attack surface to zero, delivering a new zero vulnerability computing (ZVC) paradigm. Deploying ZVC and blockchain, this paper formulates and supports a hypothesis: “Safe, secure, ethical, controllable AGI/QC is possible by conquering the two unassailable rules of computability.” Pursued by a European consortium, testing/proving the proposed hypothesis will have a groundbreaking impact on the future digital infrastructure when AGI/QC starts powering the 75 billion internet devices by 2025.
文摘Estimated at more than 2.2 million cases worldwide,most breast cancer cases and deaths from breast cancer occur in low and middle-income countries.In Cameroon,many studies have underlined the effect of knowledge of breast cancer on screening measures such as self-examination and,to a lesser extent,the perception of the threat of this disease.This research aims to assess according to the Health Belief Model(HBM),the moderating effect of perceived threat of breast cancer on the relation between knowledge and breast self-examination.A questionnaire survey was conducted among 517 Cameroonian women to assess their general knowledge about breast cancer(risk factors and screening measures),their level of the perceived threat of breast cancer through Perceived susceptibility and severity,and the prevalence of breast self-examination amongst them.A regression analysis using the Macro Process for moderation indicates the main effect of Perceived threat(b=0,29;t(517)=2,36;p=0,02)of breast cancer and knowledge(b=0,02;t(517)=4,29;p<0,001)on breast self-examination.Results also confirm that the perceived threat of breast cancer moderates the effect of knowledge on breast self-examination.While the low level of perceived threat highlights the effect of knowledge on breast self-examination(b=0,02;t(517)=3,49;p<0,001),the high level of perceived threat cancels that effect(b=0,01;t(517)=1,97;p=0,01).A woman who perceives severity and susceptibility to breast cancer is more inclined to perform breast self-examination.This result suggests the importance of taking into account,in a context where knowledge of breast cancer is limited,relevant factors of the health belief model in preventive measures against breast cancer in general and the practice of breast self-examination in particular.
基金funding from Deanship of Scientific Research in King Faisal University with Grant Number KFU241648.
文摘As the Internet of Things(IoT)continues to expand,incorporating a vast array of devices into a digital ecosystem also increases the risk of cyber threats,necessitating robust defense mechanisms.This paper presents an innovative hybrid deep learning architecture that excels at detecting IoT threats in real-world settings.Our proposed model combines Convolutional Neural Networks(CNN),Bidirectional Long Short-Term Memory(BLSTM),Gated Recurrent Units(GRU),and Attention mechanisms into a cohesive framework.This integrated structure aims to enhance the detection and classification of complex cyber threats while accommodating the operational constraints of diverse IoT systems.We evaluated our model using the RT-IoT2022 dataset,which includes various devices,standard operations,and simulated attacks.Our research’s significance lies in the comprehensive evaluation metrics,including Cohen Kappa and Matthews Correlation Coefficient(MCC),which underscore the model’s reliability and predictive quality.Our model surpassed traditional machine learning algorithms and the state-of-the-art,achieving over 99.6%precision,recall,F1-score,False Positive Rate(FPR),Detection Time,and accuracy,effectively identifying specific threats such as Message Queuing Telemetry Transport(MQTT)Publish,Denial of Service Synchronize network packet crafting tool(DOS SYN Hping),and Network Mapper Operating System Detection(NMAP OS DETECTION).The experimental analysis reveals a significant improvement over existing detection systems,significantly enhancing IoT security paradigms.Through our experimental analysis,we have demonstrated a remarkable enhancement in comparison to existing detection systems,which significantly strength-ens the security standards of IoT.Our model effectively addresses the need for advanced,dependable,and adaptable security solutions,serving as a symbol of the power of deep learning in strengthening IoT ecosystems amidst the constantly evolving cyber threat landscape.This achievement marks a significant stride towards protecting the integrity of IoT infrastructure,ensuring operational resilience,and building privacy in this groundbreaking technology.
基金supported by the National Natural Science Foundation of China (6202201562088101)+1 种基金Shanghai Municipal Science and Technology Major Project (2021SHZDZX0100)Shanghai Municip al Commission of Science and Technology Project (19511132101)。
文摘Aerial threat assessment is a crucial link in modern air combat, whose result counts a great deal for commanders to make decisions. With the consideration that the existing threat assessment methods have difficulties in dealing with high dimensional time series target data, a threat assessment method based on self-attention mechanism and gated recurrent unit(SAGRU) is proposed. Firstly, a threat feature system including air combat situations and capability features is established. Moreover, a data augmentation process based on fractional Fourier transform(FRFT) is applied to extract more valuable information from time series situation features. Furthermore, aiming to capture key characteristics of battlefield evolution, a bidirectional GRU and SA mechanisms are designed for enhanced features.Subsequently, after the concatenation of the processed air combat situation and capability features, the target threat level will be predicted by fully connected neural layers and the softmax classifier. Finally, in order to validate this model, an air combat dataset generated by a combat simulation system is introduced for model training and testing. The comparison experiments show the proposed model has structural rationality and can perform threat assessment faster and more accurately than the other existing models based on deep learning.
文摘The Unintentional Insider Threat (UIT) concept highlights that insider threats might not always stem from malicious intent and can occur across various domains. This research examines how individuals with medical or psychological issues might unintentionally become insider threats due to their perception of being targeted. Insights from the survey A Survey of Unintentional Medical Insider Threat Category indicate that such perceptions can be linked to underlying health conditions. The study Emotion Analysis Based on Belief of Targeted Individual Supporting Insider Threat Detection reveals that anger is a common emotion among these individuals. The findings suggest that UITs are often linked to medical or psychological issues, with anger being prevalent. To mitigate these risks, it is recommended that Insider Threat programs integrate expertise from medicine, psychology, and cybersecurity. Additionally, handwriting analysis is proposed as a potential tool for detecting insider threats, reflecting the evolving nature of threat assessment methodologies.
文摘Self-efficacy plays an important role in the management of type 2 diabetes mellitus (T2DM) patients, and it runs through the whole process of diabetes treatment, which is conducive to controlling and delaying the occurrence and development of complications, as well as improving the quality of life of patients. This paper mainly describes the concept of self-efficacy, the current situation of self-efficacy of diabetic patients at home and abroad, the functional aspects and their influencing factors, so as to take relevant measures on how to improve self-efficacy. It aims to provide a theoretical basis for the development of self-efficacy interventions for patients with type 2 diabetes mellitus.
文摘This literature review primarily aims to explore and synthesise the previous studies in simulation education research conducted over the past five years related to the effects of simulation training on the self-efficacy of undergraduate pre-registration nursing students. The second aim of this study is to explore additional outcome variables that were examined in the previous studies. Five electronic databases were searched systematically. These databases were MEDLINE, CINAHL Plus, Scopus, Embase and PsycINFO. The PICO model was employed to identify the search terms, with a thesaurus being used to provide synonyms. Reference lists of relevant articles were examined and hand searches of journals were also undertaken. The quality of each study was assessed using the Simulation Research Rubric (SRR). A total of 11 studies were included. All studies explored the impact of simulation education on undergraduate pre-registration nursing. Six studies explored nursing students’ competence and performance and two papers examined their critical thinking. Problem solving, learning motivation, communication skills and knowledge acquisition were examined once. The majority of studies indicated that simulation training has a positive impact on pre-registration nursing students’ self-efficacy and other outcome variables. Furthermore, the study results indicate that simulation training is more dependable than traditional training, and students were extremely satisfied with the simulation training. However, most of the studies included in this review had several gaps, including study design, sample size and dissimilarities between the scales used. Further research with large samples, reliable and valid instruments, and outcomes measures (such as critical thinking and transferability of skills) is required to provide better insight into the effectiveness of simulation in undergraduate nursing education. .
文摘Cloud computing plays a significant role in modern information technology, providing organizations with numerous benefits, including flexibility, scalability, and cost-efficiency. However, it has become essential for organizations to ensure the security of their applications, data, and cloud-based networks to use cloud services effectively. This systematic literature review aims to determine the latest information regarding cloud computing security, with a specific emphasis on threats and mitigation strategies. Additionally, it highlights some common threats related to cloud computing security, such as distributed denial-of-service (DDoS) attacks, account hijacking, malware attacks, and data breaches. This research also explores some mitigation strategies, including security awareness training, vulnerability management, security information and event management (SIEM), identity and access management (IAM), and encryption techniques. It discusses emerging trends in cloud security, such as integrating artificial intelligence (AI) and machine learning (ML), serverless computing, and containerization, as well as the effectiveness of the shared responsibility model and its related challenges. The importance of user awareness and the impact of emerging technologies on cloud security have also been discussed in detail to mitigate security risks. A literature review of previous research and scholarly articles has also been conducted to provide insights regarding cloud computing security. It shows the need for continuous research and innovation to address emerging threats and maintain a security-conscious culture in the company.
文摘As cyber threats keep changing and business environments adapt, a comprehensive approach to disaster recovery involves more than just defensive measures. This research delves deep into the strategies required to respond to threats and anticipate and mitigate them proactively. Beginning with understanding the critical need for a layered defense and the intricacies of the attacker’s journey, the research offers insights into specialized defense techniques, emphasizing the importance of timely and strategic responses during incidents. Risk management is brought to the forefront, underscoring businesses’ need to adopt mature risk assessment practices and understand the potential risk impact areas. Additionally, the value of threat intelligence is explored, shedding light on the importance of active engagement within sharing communities and the vigilant observation of adversary motivations. “Beyond Defense: Proactive Approaches to Disaster Recovery and Threat Intelligence in Modern Enterprises” is a comprehensive guide for organizations aiming to fortify their cybersecurity posture, marrying best practices in proactive and reactive measures in the ever-challenging digital realm.