Multi-Zone-Wise Blockchain Based Intrusion Detection and Prevention System for IoT Environment

Blockchain merges technology with the Internet of Things(IoT)for addressing security and privacy-related issues.However,conventional blockchain suffers from scalability issues due to its linear structure,which increases the storage overhead,and Intrusion detection performed was limited with attack severity,leading to performance degradation.To overcome these issues,we proposed MZWB(Multi-Zone-Wise Blockchain)model.Initially,all the authenticated IoT nodes in the network ensure their legitimacy by using the Enhanced Blowfish Algorithm(EBA),considering several metrics.Then,the legitimately considered nodes for network construction for managing the network using Bayesian-Direct Acyclic Graph(B-DAG),which considers several metrics.The intrusion detection is performed based on two tiers.In the first tier,a Deep Convolution Neural Network(DCNN)analyzes the data packets by extracting packet flow features to classify the packets as normal,malicious,and suspicious.In the second tier,the suspicious packets are classified as normal or malicious using the Generative Adversarial Network(GAN).Finally,intrusion scenario performed reconstruction to reduce the severity of attacks in which Improved Monkey Optimization(IMO)is used for attack path discovery by considering several metrics,and the Graph cut utilized algorithm for attack scenario reconstruction(ASR).UNSW-NB15 and BoT-IoT utilized datasets for the MZWB method simulated using a Network simulator(NS-3.26).Compared with previous performance metrics such as energy consumption,storage overhead accuracy,response time,attack detection rate,precision,recall,and F-measure.The simulation result shows that the proposed MZWB method achieves high performance than existing works.

Real-Time Network Intrusion Prevention System Using Incremental Feature Generation

Security measures are urgently required to mitigate the recent rapid increase in network security attacks.Although methods employing machine learning have been researched and developed to detect various network attacks effectively,these are passive approaches that cannot protect the network from attacks,but detect them after the end of the session.Since such passive approaches cannot provide fundamental security solutions,we propose an active approach that can prevent further damage by detecting and blocking attacks in real time before the session ends.The proposed technology uses a two-level classifier structure:the first-stage classifier supports real-time classification,and the second-stage classifier supports accurate classification.Thus,the proposed approach can be used to determine whether an attack has occurred with high accuracy,even under heavy traffic.Through extensive evaluation,we confirm that our approach can provide a high detection rate in real time.Furthermore,because the proposed approach is fast,light,and easy to implement,it can be adopted in most existing network security equipment.Finally,we hope to mitigate the limitations of existing security systems,and expect to keep networks faster and safer from the increasing number of cyber-attacks.

A Comparative Study of Related Technologies of Intrusion Detection &Prevention Systems

The rapid growth of computer networks has changed the prospect of network security. An easy accessibility condition causes computer networks to be vulnerable against numerous and potentially devastating threats from hackers. Up to the moment, researchers have developed Intrusion Detection Systems (IDS) capable of detecting attacks in several available environments. A boundlessness of methods for misuse detection as well as anomaly detection has been applied. Intrusion Prevention Systems (IPS) evolved after that to resolve am-biguities in passive network monitoring by placing detection systems on the line of attack. IPS in other words is IDS that are able to give prevention commands to firewalls and access control changes to routers. IPS can be seen as an improvement upon firewall technologies. It can make access control decisions based on application content, rather than IP address or ports as traditional firewalls do. The next innovation is the combination of IDS and IPS known as Intrusion Detection and Prevention Systems (IDPS) capable of de-tecting and preventing attacks from happening. This paper presents an overview of IDPS followed by their classifications and applications. A new signature based IDPS architecture named HawkEye Solutions has been proposed by the authors. Authors have presented the basic building blocks of the IDS, which include mechanisms for carrying out TCP port scans, Traceroute scan, ping scan and packet sniffing to monitor net-work health detect various types of attacks. Real time implementation results of the system have been pre-sented. Finally a comparative analysis of various existing IDS/IPS solutions with HawkEye Solutions em-phasizes its significance.

Evaluation of the Capacity of Comprehensive Earthquake Prevention System in a Region and Its Countermeasures

A model for evaluating the capacity of the comprehensive prevention system in a region in terms of economic losses is established in this paper by using fuzzy mathematics.The authors have explored the weak links of the system mentioned above and suggested an effective procedure of increasing the capacity of earthquake resistance and disaster prevention in a region.Through taking suitable means of decision making,the mathematical model presented in this paper can be used for reference during establishing the comprehensive prevention system in a region to reduce the earthquake disasters.

Hardware Realization of Artificial Neural Network Based Intrusion Detection &Prevention System

In the 21st century with the exponential growth of the Internet, the vulnerability of the network which connects us is on the rise at a very fast pace. Today organizations are spending millions of dollars to protect their sensitive data from different vulnerabilities that they face every day. In this paper, a new methodology towards implementing an Intrusion Detection & Prevention System (IDPS) based on Artificial Neural Network (ANN) onto Field Programmable Gate Array (FPGA) is proposed. This system not only detects different network attacks but also prevents them from being propagated. The parallel structure of an ANN makes it potentially fast for the computation of certain tasks. FPGA platforms are the optimum and best choice for the modern digital systems nowadays. The same feature makes ANN well suited for implementation in FPGA technology. Hardware realization of ANN to a large extent depends on the efficient implementation of a single neuron. However FPGA realization of ANNs with a large number of neurons is still a challenging task. The proposed multilayer ANN based IDPS uses multiple neurons for higher performance and greater accuracy. Simulation of the design in MATLAB SIMULINK 2010b by using Knowledge Discovery and Data Mining (KDD) CUP dataset shows a very good performance. Subsequently MATLAB HDL coder was used to generate VHDL code for the proposed design that produced Intellectual Property (IP) cores for Xilinx Targeted Design Platforms. For evaluation purposes the proposed design was synthesized, implemented and tested onto Xilinx Virtex-7 2000T FPGA device.

Integration of Energy and Fire Prevention Systems in Green Building

Green buildings should be sustainable, efficient, economical, and to improve the quality of life of users and nearby residents. Unfortunately, some architecture features fostered by energy and environmental certifications do not comply with fire prevention codes. Several factors can influence a building＇s energy efficiency and fire safety, such as bigger or smaller glass areas, building material thermal inertia, and the use of sustainable solutions such as green roofs. In this work, a methodology for integrating energy efficiency and fire prevention in green buildings is presented. A case study comparing a full glass skin and a building with 40% window size is considered. Also, the methodology permits modifications for obtaining a safe and energy efficient building.

Comprehensive Strategic Planning and Enhancement of China CDC Contributes to High-Quality Development of the National Disease Control and Prevention System

The Chinese government has always attached great importance to disease control and prevention efforts.Recently,the general office of China’s State Council issued the“Guidelines for High-Quality Development of Disease Prevention and Control”(hereinafter referred to as the“Guidelines”)(1).The Guidelines focus on promoting high-quality development of disease control and prevention and the strategic goal of“Healthy China,”providing specific implementation pathways for the development of national disease control and prevention in the new era,including overall planning,restructuring of governance,enhancing core capabilities,strengthening talent development,and improving organizational support.

Unraveling colorectal cancer prevention:The vitamin D-gut flora-immune system nexus

Colorectal cancer(CRC)is one of the most common cancers diagnosed in the world.Although environmental and genetic factors play a major role in the pathogenesis of CRC,extensive research has suggested that vitamin D may play a pivotal role in the development of CRC.Vitamin D,primarily obtained through sunlight exposure,dietary sources,and supplements,has long been recognized for its essential functions in maintaining health,including immune regulation.This article delves into the intricate relationship between vitamin D,the immune system,gut flora,and the prevention of CRC.It presents a synthesis of epidemiological data,experimental studies,and clinical trials,highlighting the mechanisms by which vitamin D influences immune cell function,cytokine production,and inflammation.By enhancing the immune system’s surveillance and antitumor activity,vitamin D may offer a promising avenue for CRC prevention.Furthermore,this comprehensive review delves into the prospective clinical applications of vitamin D supplementation and delineates the forthcoming avenues of research in this dynamic domain.Additionally,the paper tentatively outlines a spectrum of prophylactic impacts of vitamin D on CRC,emphasizing its significant potential in reducing CRC risk through shedding light on its mechanisms,encompassing antineoplastic mechanisms,influences on the immune system,and modulation of the gut microbiome.

Advanced Optimized Anomaly Detection System for IoT Cyberattacks Using Artificial Intelligence

While emerging technologies such as the Internet of Things(IoT)have many benefits,they also pose considerable security challenges that require innovative solutions,including those based on artificial intelligence(AI),given that these techniques are increasingly being used by malicious actors to compromise IoT systems.Although an ample body of research focusing on conventional AI methods exists,there is a paucity of studies related to advanced statistical and optimization approaches aimed at enhancing security measures.To contribute to this nascent research stream,a novel AI-driven security system denoted as“AI2AI”is presented in this work.AI2AI employs AI techniques to enhance the performance and optimize security mechanisms within the IoT framework.We also introduce the Genetic Algorithm Anomaly Detection and Prevention Deep Neural Networks(GAADPSDNN)sys-tem that can be implemented to effectively identify,detect,and prevent cyberattacks targeting IoT devices.Notably,this system demonstrates adaptability to both federated and centralized learning environments,accommodating a wide array of IoT devices.Our evaluation of the GAADPSDNN system using the recently complied WUSTL-IIoT and Edge-IIoT datasets underscores its efficacy.Achieving an impressive overall accuracy of 98.18%on the Edge-IIoT dataset,the GAADPSDNN outperforms the standard deep neural network(DNN)classifier with 94.11%accuracy.Furthermore,with the proposed enhancements,the accuracy of the unoptimized random forest classifier(80.89%)is improved to 93.51%,while the overall accuracy(98.18%)surpasses the results(93.91%,94.67%,94.94%,and 94.96%)achieved when alternative systems based on diverse optimization techniques and the same dataset are employed.The proposed optimization techniques increase the effectiveness of the anomaly detection system by efficiently achieving high accuracy and reducing the computational load on IoT devices through the adaptive selection of active features.

Optimization of Stealthwatch Network Security System for the Detection and Mitigation of Distributed Denial of Service (DDoS) Attack: Application to Smart Grid System

The Smart Grid is an enhancement of the traditional grid system and employs new technologies and sophisticated communication techniques for electrical power transmission and distribution. The Smart Grid’s communication network shares information about status of its several integrated IEDs (Intelligent Electronic Devices). However, the IEDs connected throughout the Smart Grid, open opportunities for attackers to interfere with the communications and utilities resources or take clients’ private data. This development has introduced new cyber-security challenges for the Smart Grid and is a very concerning issue because of emerging cyber-threats and security incidents that have occurred recently all over the world. The purpose of this research is to detect and mitigate Distributed Denial of Service [DDoS] with application to the Electrical Smart Grid System by deploying an optimized Stealthwatch Secure Network analytics tool. In this paper, the DDoS attack in the Smart Grid communication networks was modeled using Stealthwatch tool. The simulated network consisted of Secure Network Analytic tools virtual machines (VMs), electrical Grid network communication topology, attackers and Target VMs. Finally, the experiments and simulations were performed, and the research results showed that Stealthwatch analytic tool is very effective in detecting and mitigating DDoS attacks in the Smart Grid System without causing any blackout or shutdown of any internal systems as compared to other tools such as GNS3, NeSSi2, NISST Framework, OMNeT++, INET Framework, ReaSE, NS2, NS3, M5 Simulator, OPNET, PLC & TIA Portal management Software which do not have the capability to do so. Also, using Stealthwatch tool to create a security baseline for Smart Grid environment, contributes to risk mitigation and sound security hygiene.

Adolescent suicide risk factors and the integration of socialemotional skills in school-based prevention programs

Adolescents are considered one of the most vulnerable groups affected by suicide.Rapid changes in adolescents’physical and mental states,as well as in their lives,significantly and undeniably increase the risk of suicide.Psychological,social,family,individual,and environmental factors are important risk factors for suicidal behavior among teenagers and may contribute to suicide risk through various direct,indirect,or combined pathways.Social-emotional learning is considered a powerful intervention measure for addressing the crisis of adolescent suicide.When deliberately cultivated,fostered,and enhanced,selfawareness,self-management,social awareness,interpersonal skills,and responsible decision-making,as the five core competencies of social-emotional learning,can be used to effectively target various risk factors for adolescent suicide and provide necessary mental and interpersonal support.Among numerous suicide intervention methods,school-based interventions based on social-emotional competence have shown great potential in preventing and addressing suicide risk factors in adolescents.The characteristics of school-based interventions based on social-emotional competence,including their appropriateness,necessity,cost-effectiveness,comprehensiveness,and effectiveness,make these interventions an important means of addressing the crisis of adolescent suicide.To further determine the potential of school-based interventions based on social-emotional competence and better address the issue of adolescent suicide,additional financial support should be provided,the combination of socialemotional learning and other suicide prevention programs within schools should be fully leveraged,and cooperation between schools and families,society,and other environments should be maximized.These efforts should be considered future research directions.

Cervical cancer prevention in China: where are we now, and what's next?

Cervical cancer(CC) epidemiology CC, the fourth most frequently diagnosed malignancy in women worldwide, is a major global health challenge, particularly in low-resource regions. Approximately 88.1% of the 604,000 CC new cases occurred in low-and middle-income countries in 2020, and more than 90% of the 342,000 CC deaths occurred in low-and middle-income countries in 2020~1.

A systematic investigation of radiation collapse for disruption avoidance and prevention on JET tokamak

To produce fusion reactions efficiently,thermonuclear plasmas have to reach extremely high temperatures,which is incompatible with their coming into contact with material surfaces.Confinement of plasmas using magnetic fields has progressed significantly in the last years,particularly in the tokamak configuration.Unfortunately,all tokamak devices,and particularly metallic ones,are plagued by catastrophic events called disruptions.Many disruptions are preceded by anomalies in the radiation patterns,particularly in ITER-relevant scenarios.These specific forms of radiation emission either directly cause or reveal the approaching collapse of the configuration.Detecting the localization of these radiation anomalies in real time requires an innovative and specific elaboration of bolometric measurements,confirmed by visible cameras and the inversion of sophisticated tomographic algorithms.The information derived from these measurements can be interpreted in terms of local power balances,which suggest a new quantity,the radiated power divided by the plasma internal energy,to determine the criticality of the plasma state.Combined with robust indicators of the temperature profile shape,the identified anomalous radiation patterns allow determination of the sequence of macroscopic events leading to disruptions.A systematic analysis of JET campaigns at high power in deuterium,full tritium,and DT,for a total of almost 2000 discharges,proves the effectiveness of the approach.The warning times are such that,depending on the radiation anomaly and the available actuators,the control system of future devices is expected to provide enough notice to enable deployment of effective prevention and avoidance strategies.

Prevention of malignant digestive system tumors should focus on the control of chronic inflammation

Chronic inflammation,through a variety of mechanisms,plays a key role in the occurrence and development of digestive system malignant tumors(DSMTs).In this study,we feature and provide a comprehensive understanding of DSMT prevention strategies based on preventing or controlling chronic inflammation.The development and evaluation of cancer prevention strategies is a longstanding process.Cancer prevention,especially in the early stage of life,should be emphasized throughout the whole life course.Issues such as the time interval for colon cancer screening,the development of direct-acting antiviral drugs for liver cancer,and the Helicobacter pylori vaccine all need to be explored in long-term,large-scale experiments in the future.

Traditional Chinese medicine for acute mountain sickness prevention: A systematic review and meta-analysis of randomized controlled trials

Objective: To evaluate the efficacy of traditional Chinese medicine(TCM) for preventing acute mountain sickness(AMS).Methods: We included randomized controlled trials(RCTs) which evalueded the effect of TCM for preventing AMS, compared with a placebo, no treatment or acetazolamide. The literature was searched in 6major databases. RevMan 5.4 software was used for the meta-analysis. The relative risk for discrete variables and the mean difference for continuous variables with 95% confidence intervals(CIs) were applied to express the effect size. The risk of bias in the included studies was evaluated using the Cochrane risk assessment tool 2.0(RoB 2.0), and the evidence certainty was assessed using the Grading of Recommendations Assessment and the Development and Evaluation(GRADE) approach.Results: Twenty RCTs involving 3015 participants and 16 TCM patent drugs were included. The overall risk of bias in the majority of studies(15/20) was of some concerns. In terms of the AMS incidence,Rhodiola rosea(R. rosea, Hong Jing Tian) and Ginkgo biloba(G. biloba, Yin Xing Ye) were equivalent to the placebo/no treatment [RR(95% CI): 0.66(0.43-1.01), 0.82(0.63-1.06), respectively]. The AMS incidence in the G. biloba group was higher than that in the acetazolamide group [RR(95% CI): 2.92(1.69-5.06)]. In terms of improving the AMS symptom score on days 1 and 3 in the plateau, R. rosea and G. biloba were superior to the placebo or no treatment [MD(95% CI):-0.98(-1.71,-0.25),-2.05(-3.14,-0.95), respectively]. The other 14 Chinese patent medicines were evaluated in a single trial, and the majority of the results were negative. The subgroup analysis showed that the effect of R. rosea was related to the intervention time, way of ascending, and altitude.Conclusion: R. rosea and G. biloba were effective in improving AMS symptoms but had no effect in reducing the AMS incidence. There was insufficient evidence to support the use of other TCM patent drugs to prevent AMS. More randomized double-blind placebo-controlled trials are warranted to evaluate and screen effective Chinese patent medicines for AMS prevention.

Navigating nephrotoxic waters:A comprehensive overview of contrast-induced acute kidney injury prevention

Contrast-induced acute kidney injury(CI-AKI)is the third leading cause of acute kidney injury deriving from the intravascular administration of contrast media in diagnostic and therapeutic procedures and leading to longer in-hospital stay and increased short and long-term mortality.Its pathophysiology,although not well-established,revolves around medullary hypoxia paired with the direct toxicity of the substance to the kidney.Critically ill patients,as well as those with pre-existing renal disease and cardiovascular comorbidities,are more susceptible to CI-AKI.Despite the continuous research in the field of CI-AKI prevention,clinical practice is based mostly on periprocedural hydration.In this review,all the investigated methods of prevention are presented,with an emphasis on the latest evidence regarding the potential of RenalGuard and contrast removal systems for CI-AKI prevention in high-risk individuals.

Unlocking the potential-vitamin D in prostate cancer prevention

Prostate cancer poses a significant health challenge globally,demanding proactive prevention strategies.This editorial explores the emerging role of vitamin D in prostate cancer prevention.While traditionally associated with bone health,vitamin D is increasingly recognized for its broader impact on immune function,cellular signaling,and cancer prevention.Epidemiological studies suggest an intriguing link between vitamin D deficiency and elevated prostate cancer risk,particularly in regions with limited sunlight exposure.Mechanistically,vitamin D regulates cellular processes,inhibiting unchecked cancer cell growth and bols-tering immune surveillance.Personalized prevention strategies,considering individual factors,are deemed essential for harnessing the full potential of vitamin D.To unlock this potential,the future calls for robust research,public awareness campaigns,dietary improvements,and vigilant medical guidance.Collaborative efforts are poised to pave the way toward a future where vitamin D stands as a sentinel in prostate cancer prevention,ushering in hope and improved health for men worldwide.

A tendon system to re-center steel moment frames with weak stories

A wide open bottom story of a frame building is often expected by owners for use as a garage or shops.However,this leads to weak stories due to abrupt changes in lateral stiffness and often results in unexpected story collapse as observed in many previous earthquakes.To retrofit frame buildings that have experienced weak story damage,a tendon system is proposed in this study,which consists of a set of swaying columns and tendons.The swaying columns are used to uniformly redistribute the lateral deformation along the height,while the tendons provide extra lateral stiffness and renders the entire structural system a re-centering capability.To avoid unnecessary forces to swaying columns,pin-connections are used at the bottom.Tendons are placed over the entire story to gain large elastic displacements.Parametric analysis reveals that the swaying column,with a stiffness of about 0.9 times that of the weak story,and the tendons attached at the roof,with a stiffness of 0.04 times that of the weak story,can provide the optimal performance with a maximum residual story drift angle of less than 0.5%.Online hybrid tests were carried out,which demonstrated that uniformly distributed story drifts and acceptable residual deformation could be achieved by the proposed tendon system.

Trade-offs and synergies between ecosystem services in Yutian County along the Keriya River Basin,Northwest China

The Keriya River Basin is located in an extremely arid climate zone on the southern edge of the Tarim Basin of Northwest China,exhibiting typical mountain-oasis-desert distribution characteristics.In recent decades,climate change and human activities have exerted significant impacts on the service functions of watershed ecosystems.However,the trade-offs and synergies between ecosystem services(ESs)have not been thoroughly examined.This study aims to reveal the spatiotemporal changes in ESs within the Keriya River Basin from 1995 to 2020 as well as the trade-offs and synergies between ESs.Leveraging the Integrated Valuation of Ecosystem Services and Trade-offs(InVEST)and Revised Wind Erosion Equation(RWEQ)using land use/land cover(LULC),climate,vegetation,soil,and hydrological data,we quantified the spatiotemporal changes in the five principal ESs(carbon storage,water yield,food production,wind and sand prevention,and habitat quality)of the watershed from 1995 to 2020.Spearman correlation coefficients were used to analyze the trade-offs and synergies between ES pairs.The findings reveal that water yield,carbon storage,and habitat quality exhibited relatively high levels in the upstream,while food production and wind and sand prevention dominated the midstream and downstream,respectively.Furthermore,carbon storage,food production,wind and sand prevention,and habitat quality demonstrated an increase at the watershed scale while water yield exhibited a decline from 1995 to 2020.Specifically,carbon storage,wind and sand prevention,and habitat quality presented an upward trend in the upstream but downward trend in the midstream and downstream.Food production in the midstream showed a continuously increasing trend during the study period.Trade-off relationships were identified between water yield and wind and sand prevention,water yield and carbon storage,food production and water yield,and habitat quality and wind and sand prevention.Prominent temporal and spatial synergistic relationships were observed between different ESs,notably between carbon storage and habitat quality,carbon storage and food production,food production and wind and sand prevention,and food production and habitat quality.Water resources emerged as a decisive factor for the sustainable development of the basin,thus highlighting the intricate trade-offs and synergies between water yield and the other four services,particularly the relationship with food production,which warrants further attention.This research is of great significance for the protection and sustainable development of river basins in arid areas.

Overview on Mangrove Forest Disaster Prevention and Mitigation Functions

This paper provides a comprehensive overview on coastal protection and hazard mitigation by mangroves.Previous stud-ies have made great strides to understand the mechanisms and influencing factors of mangroves’protection function,including wave energy dissipation,storm surge damping,tsunami mitigation,adjustment to sea level rise and wind speed reduction,which are sys-tematically summarized in this study.Moreover,the study analyzes the extensive physical models,based on indoor flume experi-ments and numerical models,that consider the interaction between mangroves and hydrodynamics,to help our understanding of mangrove-hydrodynamic interactions.Additionally,quantitative approaches for valuing coastal protection services provided by man-groves,including index-based and process-resolving approaches,are introduced in detail.Finally,we point out the limitations of previous studies,indicating that efforts are still required for obtaining more long-term field observations during extreme weather events,to create more real mangrove models for physical experiments,and to develop numerical models that consider the flexible properties of mangroves to better predict wave propagation in mangroves having complex morphology and structures.