A Review of Hybrid Cyber Threats Modelling and Detection Using Artificial Intelligence in IIoT

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.

Survey on Video Security:Examining Threats,Challenges,and Future Trends

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.

Classification of Cybersecurity Threats, Vulnerabilities and Countermeasures in Database Systems

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.

Assessment of Meteorological Threats to the Coordinated Search and Rescue of Unmanned/Manned Aircraft

The architecture and working principle of coordinated search and rescue system of unmanned/manned aircraft,which is composed of manned/unmanned aircraft and manned aircraft,were first introduced,and they can cooperate with each other to complete a search and rescue task.Secondly,a threat assessment method based on meteorological data was proposed,and potential meteorological threats,such as storms and rainfall,can be predicted by collecting and analyzing meteorological data.Finally,an experiment was carried out to evaluate the performance of the proposed method in different scenarios.The experimental results show that the coordinated search and rescue system of unmanned/manned aircraft can be used to effectively assess meteorological threats and provide accurate search and rescue guidance.

Resurvey After 20 Years:Updating the Distribution,Population,and Potential Threats of the Chinting Alpine Toad

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.

Tackling the Existential Threats from Quantum Computers and AI

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.

Systematic Literature Review on Cloud Computing Security: Threats and Mitigation Strategies

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.

Developing an Abstraction Framework for Managing and Controlling Saudi Banks’ Cybersecurity Threats Based on the NIST Cybersecurity Framework and ISO/IEC 27001

Saudi Arabian banks are deeply concerned about how to effectively monitor and control security threats. In recent years, the country has taken several steps towards restructuring its organizational security and, consequently, protecting financial institutions and their clients. However, there are still several challenges left to be addressed. Accordingly, this article aims to address this problem by proposing an abstract framework based on the National Institute of Standards and Technology (NIST) Cybersecurity Framework and International Organization for Standardization/International Electrotechnical Commission (ISO/IEC 27001). The framework proposed in this paper considers the following factors involved in the security policy of Saudi banks: safety, Saudi information bank, operations and security of Saudi banks, Saudi banks’ supplier relationships, risk assessment, risk mitigation, monitoring and detection, incident response, Saudi banks’ business continuity, compliance, education, and awareness about all factors contributing to the framework implementation. This way, the proposed framework provides a comprehensive, unified approach to managing bank security threats. Not only does the proposed framework provide effective guidance on how to identify, assess, and mitigate security threats, but it also instructs how to develop policy and procedure documents relating to security issues.

Blockchain Security Threats and Collaborative Defense:A Literature Review

As a distributed database,the system security of the blockchain is of great significance to prevent tampering,protect privacy,prevent double spending,and improve credibility.Due to the decentralized and trustless nature of blockchain,the security defense of the blockchain system has become one of the most important measures.This paper comprehensively reviews the research progress of blockchain security threats and collaborative defense,and we first introduce the overview,classification,and threat assessment process of blockchain security threats.Then,we investigate the research status of single-node defense technology and multi-node collaborative defense technology and summarize the blockchain security evaluation indicators and evaluation methods.Finally,we discuss the challenges of blockchain security and future research directions,such as parallel detection and federated learning.This paper aims to stimulate further research and discussion on blockchain security,providing more reliable security guarantees for the use and development of blockchain technology to face changing threats and challenges through continuous updating and improvement of defense technologies.

Multiclass Classification for Cyber Threats Detection on Twitter

The advances in technology increase the number of internet systems usage.As a result,cybersecurity issues have become more common.Cyber threats are one of the main problems in the area of cybersecurity.However,detecting cybersecurity threats is not a trivial task and thus is the center of focus for many researchers due to its importance.This study aims to analyze Twitter data to detect cyber threats using a multiclass classification approach.The data is passed through different tasks to prepare it for the analysis.Term Frequency and Inverse Document Frequency(TFIDF)features are extracted to vectorize the cleaned data and several machine learning algorithms are used to classify the Twitter posts into multiple classes of cyber threats.The results are evaluated using different metrics including precision,recall,F-score,and accuracy.This work contributes to the cyber security research area.The experiments revealed the promised results of the analysis using the Random Forest(RF)algorithm with(F-score=81%).This result outperformed the existing studies in the field of cyber threat detection and showed the importance of detecting cyber threats in social media posts.There is a need for more investigation in the field of multiclass classification to achieve more accurate results.In the future,this study suggests applying different data representations for the feature extraction other than TF-IDF such as Word2Vec,and adding a new phase for feature selection to select the optimum features subset to achieve higher accuracy of the detection process.

A Novel IoT Architecture, Assessment of Threats and Their Classification withMachine Learning Solutions

The Internet of Things(IoT)will significantly impact our social and economic lives in the near future.Many Internet of Things(IoT)applications aim to automate multiple tasks so inactive physical objects can behave independently of others.IoT devices,however,are also vulnerable,mostly because they lack the essential built-in security to thwart attackers.It is essential to perform the necessary adjustments in the structure of the IoT systems in order to create an end-to-end secure IoT environment.As a result,the IoT designs that are now in use do not completely support all of the advancements that have been made to include sophisticated features in IoT,such as Cloud computing,machine learning techniques,and lightweight encryption techniques.This paper presents a detailed analysis of the security requirements,attack surfaces,and security solutions available for IoT networks and suggests an innovative IoT architecture.The Seven-Layer Architecture in IoT provides decent attack detection accuracy.According to the level of risk they pose,the security threats in each of these layers have been properly categorized,and the essential evaluation criteria have been developed to evaluate the various threats.Also,Machine Learning algorithms like Random Forest and Support Vector Machines,etc.,and Deep Learning algorithms like Artificial Neural Networks,Q Learning models,etc.,are implemented to overcome the most damaging threats posing security breaches to the different IoT architecture layers.

Analysis on Opportunities and Threats for Agricultural Sustainable Development of Yunnan Province in the Context of the 13th Five-year Plan

The research studied opportunities and potential threats confronted by agricultural sustainable development, laying foundation for optimization of agricultural structure, transformation of agricultural development mode, and accomplishment of agricultural modernization. On basis of development target, development theory and route of the 13^th Five-year Plan, the research analysis the opportunities and potential threats of Yunnan agriculture and proposed policy suggestions on sustainable development of agriculture from the perspectives of ecological and competitive advantage, as well as sustainable development division in order to provide references for scientific formulation and decision-making of relevant regional planning.

Different coding characteristics between flight and freezing in dorsal periaqueductal gray of mice during exposure to innate threats

Background:Flight and freezing are two vital defensive behaviors that mice display to avoid natural enemies.When they are exposed to innate threats,visual cues are processed and transmitted by the visual system into the emotional nuclei and finally transmitted to the periaqueductal gray(PAG)to induce defensive behaviors.However,how the dorsal PAG(dPAG)encodes the two defensive behaviors is unclear.Methods:Multi-array electrodes were implanted in the dPAG nuclei of C57BL/6 mice.Two kinds of visual stimuli(looming and sweeping)were used to induce defensive behaviors in mice.Neural signals under different defense behaviors were recorded,and the encoding characteristics of the two behaviors were extracted and analyzed from spike firing and frequency oscillations.Finally,synchronization of neural activity during the defense process was analyzed.Results:The neural activity between flight and freezing behaviors showed different firing patterns,and the differences in the inter-spike interval distribution were mainly reflected in the 2–10 ms period.The frequency band activities under both defensive behaviors were concentrated in the theta band;the active frequency of flight was~8to 10 Hz,whereas that of freezing behavior was~6 to 8 Hz.The network connection density under both defense behaviors was significantly higher than the period before and after defensive behavior occurred,indicating that there was a high synchronization of neural activity during the defense process.Conclusions:The dPAG nuclei of mice have different coding features between flight and freezing behaviors;during strong looming stimulation,fast neuro-i nstinctive decision making is required while encountering weak sweeping stimulation,and computable planning late behavior is predicted in the early stage.The frequency band activities under both defensive behaviors were concentrated in the theta band.There was a high synchronization of neural activity during the defense process,which may be a key factor triggering different defensive behaviors.

Analyzing Security Threats to Virtual Machines Monitor in Cloud Computing Environment

The data and applications in cloud computing reside in cyberspace, that allowing to users access data through any connection device, when you need to transfer information over the cloud, you will lose control of it. There are multi types of security challenge must be understood and countermeasures. One of the major security challenges is resources of the cloud computing infrastructures are provided as services over the Internet, and entire data in the cloud computing are reside over network resources, that enables the data to be access through VMs. In this work, we describe security techniques for securing a VCCI, VMMs such as Encryption and Key Management (EKM), Access Control Mechanisms (ACMs), Virtual Trusted Platform Module (vTPM), Virtual Firewall (VF), and Trusted Virtual Domains (TVDs). In this paper we focus on security of virtual resources in Virtualized Cloud Computing Infrastructure (VCCI), Virtual Machine Monitor (VMM) by describing types of attacks on VCCI, and vulnerabilities of VMMs and we describe the techniques for securing a VCCI.

Smart Grid Cyber Security： An Overview of Threats and Countermeasures

The smart grid is the next generation of power and distribution systems. The integration of advanced network, communications, and computing techniques allows for the enhancement of efficiency and reliability. The smart grid interconnects the flow of information via the power line, intelligent metering, renewable and distributed energy systems, and a monitoring and controlling infrastructure. For all the advantages that these components come with, they remain at risk to a spectrum of physical and digital attacks. This paper will focus on digital vulnerabilities within the smart grid and how they may be exploited to form full fledged attacks on the system. A number of countermeasures and solutions from the literature will also be reported, to give an overview of the options for dealing with such problems. This paper serves as a triggering point for future research into smart grid cyber security.

Genomic Tools for the Impact Assessment of 'Hotspots' for Early Warning of MDR Threats

INTRODUCTION Antimicrobial resistance （AMR） has been a low-priority area of research in most developing countries even though it has much significant therapeutic value. The management of serious infections should include not only the treatment of patients but also the measures to ensure that microorganisms do not spread through hospital premises. Controlling the transfer of organisms among staff, patients, and the environment is important. Research related to antimicrobial use and resistance, regional variation, and intervention policies.

Assessment of Containment Structures Against Missile Impact Threats

In order to ensure the highest safety requirements, nuclear power plant structures (the containment structures, the fuel storages and transportation systems) should be assessed against all possible internal and external impact threats. The internal impact threats include kinetic missiles generated by the failure of high pressure vessels and pipes, the failure of high speed rotating machineries and accidental drops. The external impact threats may come from airborne missiles, aircraft impact, explosion blast and fragments. The impact effects of these threats on concrete and steel structures in a nuclear power plant are discussed. Methods and procedures for the impact assessment of nuclear power plants are introduced. Recent studies on penetration and perforation mechanics as well as progresses on dynamic properties of concrete-like materials are presented to increase the understanding of the impact effects on concrete containment structures.

Wireless Application Protocol for Potential Threats to Mobile Agent Network Security

The wireless application protocol （WAP） protocol is now the leading standard for information services on wireless terminals like digital mobile phones. By the use of WAP, wireless devices, like mobile phones, are possibly infected with virus and worms. Though up to now there is no such attack, as the usage of script languages increases, there is a chance of malicious code injection. This paper discusses the threats with current WAP protocol, and how changes in the protocol and the increase in its usage will enable entry of real viruses. Future threat scenarios are presented along with suggestions to avoid these problems.

Emerging Threats to Forests: Resilience and Strategies at System Scale

Forests provide multiple ecosystem services that are critical to sustain societies and ecosystems. Protecting the forest systems become imperative as human demand for forest products and services increase. In addition to current stressors, several emerging threats pose serious implications on the survival and sustainability of forest ecosystems. These include climatic change, invasive species, natural disasters, land use change, and pest/diseases that can severally impact the ability of forest to sustain ecosystem services. There is a need for using a systems-based framework to increase resilience of forest systems to cope with these threats. We review literature on these threats and propose a systems-framework for forest resilience. While strategies for each threat are often easier, comprehensive strategies that can handle multiple threats and specific to forest type is required. There is also a need for further research into forest resilience and landscape-scale response and resilience.

Climate Change and Biodiversity Threats on Pachypodium Species in South Africa

The genus Pachypodium are succulent shrubs and small trees found in Southern Africa. Climate change is identified as one the most important threat impacting plant and animal species in the South Africa today, and in this case study, we examined the Pachypodium bispinosum and Pachypodium succulentum species in South Africa, which are becoming more vulnerable due to climate change impacts as well as human threats. This study investigates the climate change impacts on the two Pachypodium species, as well as the biodiversity threats facing the Pachypodium species today, and provides evidence regarding the importance of the study to understanding the climate change impacts on the Pachypodium species by showing the underlying variables affecting the changes.