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As the physical power information system undergoes continual advancement, mobile energy storage has become a pivotal component in the planning and orchestration of multi-component distribution networks. Furthermore, the evolution and enhancement of big data technologies have significantly contributed to enhancing the rationality and efficacy of various distribution network planning and layout approaches. At the same time, multi-distribution networks have also confronted numerous network attacks with increasing probability and severity. In this study, a Petri net is initially employed as a modeling technique to delineate the network attack flow within the distribution network. Subsequently, the data from prior network attacks are consolidated and scrutinized to evaluate the vulnerability of the cyber-physical system (CPS), thereby identifying the most critical network attack pattern for a multi-component distribution network. Following this, the defender-attacker-defender planning methodology is applied for scale modeling, incorporating rapidly evolving mobile energy storage into the prelayout, aiming to mitigate the detrimental impact of network attacks on the power grid. Ultimately, the column and constraint generation (C&CG) algorithm is utilized to simulate and validate the proposed planning strategy in a 33-node system with multiple control groups established to demonstrate the viability and merits of the proposed strategy. [ABSTRACT FROM AUTHOR]

The development of microgrid automation depends on information and communication technologies, which are vulnerable to cyber-attacks. Recent advancements in MGs enhance power systems' efficacy and reliability, but cybersecurity remains a significant concern, especially with false data injection attacks (FDIAs) posing serious threats. FDIAs can compromise measurement devices and tamper with State Estimation (SE), risking the seamless operation of MGs. To address this, this paper proposes an efficient Iterative Free Detection of False Data (IFDFD) scheme for detecting FDIAs in microgrid state estimation. The IFDFD scheme uses complex Micro Phasor Measurement Unit (μPMU) measurements and computes nodal power injections to detect FDIAs. Furthermore, the proposed scheme integrates an S-Estimator to eliminate noise errors caused by environmental factors and the component lifespan, making IFDFD robust against sophisticated attackers. The proposed IFDFD scheme has been tested and validated on the modified IEEE 14 bus test system, integrating Distributed Generations (DGs). False data was injected into the measurements to test the scheme's effectiveness. The efficacy of proposed IFDFD scheme has been validated by comparing it to existing method of FDIAs. The obtained result clearly validates the efficacy of the proposed IFDFD scheme. • Addresses cybersecurity concerns in MG automation dependent on Information and Communication Technology. • Proposed IFDFD scheme detects FDIAs using μPMU measurements and nodal power injections. • IFDFD integrates S-Estimator to eliminate noise errors from environmental factors. [ABSTRACT FROM AUTHOR]

In the evolving landscape of cybersecurity threats, permanent denial-of-service (PDoS) attacks have emerged as a particularly damaging form of cyber aggression. Unlike the more well-known denial-of-service (DoS) attacks, which disrupt services temporarily, PDoS attacks aim to inflict irreversible damage to systems, often resulting in significant system overhauls and requiring hardware replacement. To enable the development of effective security measures, but also to address the knowledge gaps, this paper presents an in-depth exploration of PDoS attacks, emphasizing their distinguishing characteristics, underlying mechanisms, and potential further development. Through a comprehensive case study, this research highlights diverse tactics and strategies employed by attackers, from targeting IoT devices to manipulating boot processes and exploiting firmware vulnerabilities. A novel classification of PDoS attack vectors is proposed that also explains the ways in which the systems can be compromised. The findings confirm the pressing need for adaptive and robust defense mechanisms to mitigate the threats posed by PDoS attacks in our interconnected digital world.

Cyber–physical systems (CPSs), which combine computer science, control systems, and physical elements, have become essential in modern industrial and societal contexts. However, their extensive integration presents increasing security challenges, particularly due to recurring cyber attacks. Therefore, it is crucial to explore CPS security control. In this review, we systematically examine the prevalent cyber attacks affecting CPSs, such as denial of service, false data injection, and replay attacks, explaining their impacts on CPSs' operation and integrity, as well as summarizing classic attack detection methods. Regarding CPSs' security control approaches, we comprehensively outline protective strategies and technologies, including event-triggered control, switching control, predictive control, and optimal control. These approaches aim to effectively counter various cyber threats and strengthen CPSs' security and resilience. Lastly, we anticipate future advancements in CPS security control, envisioning strategies to address emerging cyber risks and innovations in intelligent security control techniques. [ABSTRACT FROM AUTHOR]

The article reveals the problem of mitigating an insider threat by creating a timebalanced security system in an organization. Based on Markov chain, the authors propose a basic model of interaction in an "organization - insider" system. The article analytically defines a ratio between the time of an insider attack and the time during which the organization's security system can neutralize it. The authors propose a concept of a multi-level system of organization protection, which takes into account the involved resources and practical skills of employees, as well as security services. At the end of the article, it is concluded that the proposed concept of the organization's protection system will be effective against potential insider attacks. [ABSTRACT FROM AUTHOR]

Among automated driving technologies, adaptive cruise control (ACC), which controls the distance between vehicles and their relative speed, is becoming popular. Cooperative ACC (CACC) uses vehicle-to-vehicle communication and sensors to control the distance between vehicles. Recently, cyber attacks against automated driving systems have been a focus, in which information on pedestrians or preceding vehicles obtained from LiDAR and sensors is disguised. Such cyber attacks enable attackers to obtain accurate information on preceding vehicles and pedestrians. This can result in accidents. The purpose of this study is to develop a filtering function to reduce the impact of cyber attacks using available information. The contribution lies in proposing a filtering function for situations in which sensor offsets and communication delays arise owing to cyber attacks. [ABSTRACT FROM AUTHOR]

In the evolving landscape of cybersecurity threats, permanent denial-of-service (PDoS) attacks have emerged as a particularly damaging form of cyber aggression. Unlike the more well-known denial-of-service (DoS) attacks, which disrupt services temporarily, PDoS attacks aim to inflict irreversible damage to systems, often resulting in significant system overhauls and requiring hardware replacement. To enable the development of effective security measures, but also to address the knowledge gaps, this paper presents an in-depth exploration of PDoS attacks, emphasizing their distinguishing characteristics, underlying mechanisms, and potential further development. Through a comprehensive case study, this research highlights diverse tactics and strategies employed by attackers, from targeting IoT devices to manipulating boot processes and exploiting firmware vulnerabilities. A novel classification of PDoS attack vectors is proposed that also explains the ways in which the systems can be compromised. The findings confirm the pressing need for adaptive and robust defense mechanisms to mitigate the threats posed by PDoS attacks in our interconnected digital world. [ABSTRACT FROM AUTHOR]

Cyber attacks have a significant business impact, with the potential to escalate into crises if poorly managed. A recurring pattern is strategic dilemmas that cannot be resolved satisfactorily. Some dilemmas are more pronounced, others less so, and therefore often catch decision-makers unprepared, leaving only bad options for decision-making. Something that all dilemmas have in common is that the associated decisions can have a lasting impact on relationships with stakeholders. This paper introduces four recurring dilemmas; shows the typical considerations; lists options for mitigating these dilemmas; and describes the basic requirements for implementing mitigations. The dilemmas and options, in turn, are rooted in the organisation-specific design of: cyber security incident management and response; IT service continuity and disaster recovery management; business continuity management; and crisis management and communication. [ABSTRACT FROM AUTHOR]

Copyright of Integrated Intelligent Energy is the property of Editorial Department of Integrated Intelligent Energy and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Integrated Intelligent Energy is the property of Editorial Department of Integrated Intelligent Energy and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

With the advancement of regulations regarding the reduction in carbon emissions, renewable energy communities have come into the picture. However, many implications come with the installation of these communities from a cybersecurity point of view. The software platforms responsible for managing and controlling them handle a lot of crucial information, and therefore, tampering with these data can lead to several impacts on the operation of these communities and, in turn, the power grid as well. This paper examines the plausible impacts that can be caused by altering certain parameters of the system that make it a potential cyber attack target. The analysis is done by observing how the grid responds to these manipulations for both low-voltage as well as medium-voltage systems. These systems are designed along with integrated energy communities and are implemented in MATLAB/Simulink R2022b software. The observations are made by plotting the grid voltage and power profiles in normal as well as attacked conditions. [ABSTRACT FROM AUTHOR]

The study sought to investigate the prevalence of cyberbullying incidents among learners in institutions of higher learning in Gaborone, Botswana. The study explored the prevalence of cyberbullying, cyber stalking, impersonation and the use of technology. The mixed methods explanatory research design was adopted in this study. This design involved the use of qualitative and quantitative data collection and analysis techniques to establish the extent of cyberbullying in institutions of higher learning in Gaborone. Questionnaires were distributed to 150 learners at the institutions of higher learning in Gaborone main campuses. Both institutions of learning were selected because of their intensive use of technology for teaching and learning. Of the 150 questionnaires that were distributed, 115 were completed and returned culminating in a 77% response rate. The research findings revealed the prevalence of cyberbullying in institutions of learning. The results also demonstrated that technological platforms through the use of the internet facilitated cyberbullying in learning institutions. The findings of the study are significant as they will enable the leaders of the institutions to promulgate effective policies that will help curb the prevalence cyberbullying incidences. To augment knowledge sharing in the education fraternity, the study makes a recommendation to the Ministry of Education, together with other institutions of learning, that a specific cyberbullying policy should be promulgated and implemented. [ABSTRACT FROM AUTHOR]

This paper studies the security control problem of semi-Markov jump systems. First, the parameter uncertainty, the time-varying delay, the nonlinear function and the cyber attack are considered in the system. Second, the nonlinear function is linearized by the fuzzy logic rule. A sliding mode surface is designed to obtain an equivalent controller and get a sliding mode dynamic system. By constructing Lyapunov functions of the mode dependence, a sufficient condition for H∞ asymptotic stability of the system is obtained. Then, an adaptive sliding mode controller is established, and the original system reaches the sliding mode surface in a finite time. Finally, two examples verify the correctness and practicality of the proposed theory. [ABSTRACT FROM AUTHOR]

As the physical power information system undergoes continual advancement, mobile energy storage has become a pivotal component in the planning and orchestration of multi-component distribution networks. Furthermore, the evolution and enhancement of big data technologies have significantly contributed to enhancing the rationality and efficacy of various distribution network planning and layout approaches. At the same time, multi-distribution networks have also confronted numerous network attacks with increasing probability and severity. In this study, a Petri net is initially employed as a modeling technique to delineate the network attack flow within the distribution network. Subsequently, the data from prior network attacks are consolidated and scrutinized to evaluate the vulnerability of the cyber-physical system (CPS), thereby identifying the most critical network attack pattern for a multi-component distribution network. Following this, the defender–attacker–defender planning methodology is applied for scale modeling, incorporating rapidly evolving mobile energy storage into the pre-layout, aiming to mitigate the detrimental impact of network attacks on the power grid. Ultimately, the column and constraint generation (C&CG) algorithm is utilized to simulate and validate the proposed planning strategy in a 33-node system with multiple control groups established to demonstrate the viability and merits of the proposed strategy.

Vulnerability assessment forms the foundation for remediation activities that an organization develops as a part of risk assessment and mitigation. This paper presents a synchrophasor measurement device-specific cyber security vulnerability assessment at the network level. A synchrophasor network is essential for a wide-area measurement system (WAMS) that assembles time-synchronized data from multiple power network components and facilitates the processing and transferring of these data. Attackers can leverage their knowledge of firmware and protocols to disrupt or critically damage the functioning of the power system stealthily. Nevertheless, the exploitation can be curbed or controlled if the operator is aware of the vulnerabilities associated with the field devices. The authors detail their analysis on the following aspects: 1) classification of attacks in synchrophasor network; 2) type of resources and reconnaissance sufficient to launch an attack on field devices; and 3) identification, demonstration, and exploitation of synchrophasor device vulnerabilities. The work showcases exploitable vulnerabilities to understand the breadth and scope of a synchrophasor measurement device’s exposure to a possible cyber attack. The reverse-engineered attack focuses on capturing essential features of packets and consuming the bandwidth during the three-way handshake among legitimate entities. The latency in packet transmission is gradually increased, which results in retransmission; thus, the legitimate connection gets terminated. Thus, the paper provides situational awareness at the device level and credible information regarding loopholes and weak links in field devices.

The popularity of Internet of Things (IoT) devices in smart homes has raised significant concerns regarding data security and privacy. Traditional machine learning (ML) methods for anomaly detection often require sharing sensitive IoT data with a central server, posing security and efficiency challenges. In response, this paper introduces FedGroup, a novel Federated Learning (FL) method inspired by FedAvg. FedGroup revolutionizes the central model’s learning process by updating it based on the learning patterns of distinct groups of IoT devices. Our experimental results demonstrate that FedGroup consistently achieves comparable or superior accuracy in anomaly detection when compared to both federated and non-federated learning methods. Additionally, Ensemble Learning (EL) collects intelligence from numerous contributing models, leading to enhanced prediction performance. Furthermore, FedGroup significantly improves the detection of attack types and their details, contributing to a more robust security framework for smart homes. Our approach demonstrates exceptional performance, achieving an accuracy rate of 99.64% with a minimal false positive rate (FPR) of 0.02% in attack type detection, and an impressive 99.89% accuracy in attack type detail detection. [ABSTRACT FROM AUTHOR]

Cyber Defense is becoming a major issue for every organization to keep business continuity intact. The presented paper explores the effectiveness of a meta-heuristic optimization algorithm-Artificial Bees Colony Algorithm (ABC) as an Nature Inspired Cyber Security mechanism to achieve adaptive defense. It experiments on the Denial- Of-Service attack scenarios which involves limiting the traffic flow for each node. Businesses today have adapted their service distribution models to include the use of the Internet, allowing them to effectively manage and interact with their customer data. This shift has created an increased reliance on online services to store vast amounts of confidential customer data, meaning any disruption or outage of these services could be disastrous for the business, leaving them without the knowledge to serve their customers. Adversaries can exploit such an event to gain unauthorized access to the confidential data of the customers. The proposed algorithm utilizes an Adaptive Defense approach to continuously select nodes that could present characteristics of a probable malicious entity. For any changes in network parameters, the cluster of nodes is selected in the prepared solution set as a probable malicious node and the traffic rate with the ratio of packet delivery is managed with respect to the properties of normal nodes to deliver a disaster recovery plan for potential businesses. [ABSTRACT FROM AUTHOR]

Cyber attacks are a genuine threat that has emerged due to the evolution of a more dynamic and complex global strategic environment. In Indonesia, several cyber attacks target various government infrastructure sectors. The National Cyber and Crypto Agency (BSSN) predicts Indonesia will face approximately 370.02 million cyber attacks in 2022. The majority of cyber attacks target the government administration sector. The National Cyber and Crypto Agency (BSSN) officially formed a Computer Security Incident Response Team (CSIRT) to tackle the rampant cybercrime cases. CSIRT is an organisation or team that provides services and support to prevent, handle, and respond to computer security incidents. The current CSIRT does not have a data storage process and forensic preparation. CSIRT will repeat the procedure, and so on. This is a repeating procedure; the attack will occur once, and only a technical problem will arise. Therefore, the research entitled "Analysis of Knowledge Management Strategies for Handling Cyber Attacks with the Computer Security Incident Response Team (CSIRT)" is expected to implement this Knowledge Management Strategy to manage existing knowledge so that it can make it easier for the CSIRT team to handle cyber attacks that occur. [ABSTRACT FROM AUTHOR]

The explosive growth of cyber attacks today, such as malware, spam, and intrusions, has caused severe consequences on society. Securing cyberspace has become a great concern for organizations and governments. Traditional machine learning based methods are extensively used in detecting cyber threats, but they hardly model the correlations between real-world cyber entities. In recent years, with the proliferation of graph mining techniques, many researchers have investigated these techniques for capturing correlations between cyber entities and achieving high performance. It is imperative to summarize existing graph-based cybersecurity solutions to provide a guide for future studies. Therefore, as a key contribution of this work, we provide a comprehensive review of graph mining for cybersecurity, including an overview of cybersecurity tasks, the typical graph mining techniques, and the general process of applying them to cybersecurity, as well as various solutions for different cybersecurity tasks. For each task, we probe into relevant methods and highlight the graph types, graph approaches, and task levels in their modeling. Furthermore, we collect open datasets and toolkits for graph-based cybersecurity. Finally, we present an outlook on the potential directions of this field for future research. [ABSTRACT FROM AUTHOR]

As wind turbine generator systems become more common in the modern power grid, the question of how to adequately protect them from cyber criminals has become a major theme in the development of new control systems. As such, artificial intelligence (AI) and machine learning (ML) algorithms have become major contributors to preventing, detecting, and mitigating cyber-attacks in the power system. In their current state, wind turbine generator systems are woefully unprepared for a coordinated and sophisticated cyber attack. With the implementation of the internet-of-things (IoT) devices in the power control network, cyber risks have increased exponentially. The literature shows the impact analysis and exploring detection techniques for cyber attacks on the wind turbine generator systems; however, almost no work on the mitigation of the adverse effects of cyber attacks on the wind turbine control systems has been reported. To overcome these limitations, this paper proposes implementing an AI-based converter controller, i.e., a multi-agent deep deterministic policy gradient (DDPG) method that can mitigate any adverse effects that communication delays or bad data could have on a grid-connected doubly fed induction generator (DFIG)-based wind turbine generator or wind farm. The performance of the proposed DDPG controller has been compared with that of a variable proportional–integral (VPI) control-based mitigation method. The proposed technique has been simulated and validated utilizing the MATLAB/Simulink software, version R2023A, to demonstrate the effectiveness of the proposed method. Also, the performance of the proposed DDPG method is better than that of the VPI method in mitigating the adverse impacts of cyber attacks on wind generator systems, which is validated by the plots and the root mean square error table found in the results section. [ABSTRACT FROM AUTHOR]

Copyright of Strategic Universe Journal / Univers Strategic is the property of Dimitrie Cantemir Christian University, Institute for Security Studies and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The problems of protecting information resources from cyberattacks of public and private enterprises are considered based on the analysis of data in the USA for 2022, taking into account the type of cyberattack and estimates of the damage caused. The analysis of cyberattacks allows us to conclude that the security of information resources depends on the human factor for more than 90 percent and it is in this direction that maximum efforts should be made. Improving the protection of information resources is not possible without the use of artificial intelligence (AI). The possibilities of the influence of AI on the cyber defense of the energy industry are considered and areas that require attention in the development of systems of protection against cyber attacks, which are "doomed" to attract the achievements of AI, are proposed. At the same time, it is taken into account that AI not only allows you to increase protection against cyber attacks, but can also make computer networks less secure. And the extraordinary capabilities of neural networks require the urgent creation of agreed international protocols for their developers. [ABSTRACT FROM AUTHOR]

Copyright of Ankara Hacı Bayram Veli Üniversitesi Hukuk Fakültesi Dergisi is the property of Ankara Haci Bayram Veli Universitesi Hukuk Fakultesi and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The expanding information and communication technology landscape has led to complex security challenges, marked by dynamic and evolving cyber threats including hacking, malware, phishing, data theft, fraud, and Distributed Denial of Service (DDoS). Notably, the United States has faced the highest incidence of cybercrime cases from 2017 to 2021, affecting 2.9 billion victims and resulting in a cumulative material loss of US$18.7 billion during this period. This research centers on the United States, acknowledged as the primary target for global cybercriminals, comprising 38% of cybercrime targets. This research aims to find out the strategic efforts of the United States in overcoming cybercrime that befell its country so that it becomes the best country in cases of alleviating and controlling cases of cyberattacks even though it is also the country with the highest cases of cyberattacks in the world. Utilizing a qualitative research method, the study demonstrates that the United States collaborates systematically and synergistically with state governments, employing a centralized approach to delegate specific tasks and authorities. The study concludes that the United States has implemented the National Cybersecurity Strategy (NCS) 2023 program, aiming to establish a strategic environment and ecosystem by maintaining vital infrastructure and centralized integration.

The challenges and threats from cyber security are increasing every day in the world. All this has a significant impact on international relations. When we are dealing with such a revolutionary development of technology as in the 21st century, it is already necessary for all states to have high-standard cyber security systems. This is not an easy issue to solve, because cyber security requires quite a lot of finances, human resources, and also specially trained professionals. Threats emanating from cyberspace need a proper response, in this case we have no choice, the whole world is facing danger. Cybercrime and the damage caused by it are increasing year by year. Also, all this affects a person psychologically and leaves a feeling of insecurity. The biggest problem is that aggressive states, terrorist organizations, non-state groups, large corporations, etc. are mostly involved in this virtual war (as in the real one). As an example, we can cite such an aggressor state as Russia, which carries out major cyber attacks against Ukraine, Georgia and other states whose cyber security systems are less protected. The transition of political, military, social or criminal processes into cyberspace has made cyber security one of the main segments of state security. Countries with developed cyber-offensive potential, primarily Russia, successfully use cyberspace both during war and conflict, as well as in peacetime, to gain geopolitical advantage. This article discusses the challenges and threats associated with the development of modern cyber and information technologies, analyzes the threats associated with the new information security capabilities of modern states, including cybersecurity. The aim of the paper is to present the role of cyber security in the Russia-Ukraine war and the threats arising from it. The following methods are used in the paper: methods of historical-descriptive, policy research and comparative analysis. The paper uses the theories of balance of power and securitization.

Abstract Owing to their flexibility and rapid response, grid-connected distributed energy resources (DERs) are wielding growing influence in frequency regulation markets (FRMs). Nevertheless, compared with conventional large-scale generators, small-scale DERs are usually weakly shielded by cyber security measures. This offers attackers the opportunity of disrupting the clearing and settlement of FRMs by manipulating the bid information of DERs. In this paper, the frequency regulation market equilibrium is studied considering the dynamic gaming between attackers and defenders, both of which need the knowledge of FRMs for their interventions. Specifically, a tri-level programming model characterizing the attacker–defender–operator (ADO) interdiction problem in FRMs is developed and then analyzed using a column and constraint generation algorithm, thereby achieving market equilibrium representing the defender's best response to the attacker. The defense strategy in the market equilibrium can attenuate the negative influence of cyber attacks upon the FRMs to the maximum extent. Finally, based on the operating rules of the California Independent System Operator, the FRM process considering the ADO interdiction is simulated and the numerical equilibrium results are presented.

Owing to their flexibility and rapid response, grid-connected distributed energy resources (DERs) are wielding growing influence in frequency regulation markets (FRMs). Nevertheless, compared with conventional large-scale generators, small-scale DERs are usually weakly shielded by cyber security measures. This offers attackers the opportunity of disrupting the clearing and settlement of FRMs by manipulating the bid information of DERs. In this paper, the frequency regulation market equilibrium is studied considering the dynamic gaming between attackers and defenders, both of which need the knowledge of FRMs for their interventions. Specifically, a tri-level programming model characterizing the attacker–defender–operator (ADO) interdiction problem in FRMs is developed and then analyzed using a column and constraint generation algorithm, thereby achieving market equilibrium representing the defender's best response to the attacker. The defense strategy in the market equilibrium can attenuate the negative influence of cyber attacks upon the FRMs to the maximum extent. Finally, based on the operating rules of the California Independent System Operator, the FRM process considering the ADO interdiction is simulated and the numerical equilibrium results are presented. [ABSTRACT FROM AUTHOR]

In a smart grid (SG) system with load uncertainties and the integration of variable solar and wind energies, an effective frequency control strategy is necessary for generation and load balancing. Cyberattacks are emerging threats, and SG systems are typical cyber-attack targets. This work suggests an improved gorilla troops optimizer (iGTO)-based fuzzy PD-(1+PI) (FPD-(1+PI)) structure for the frequency control of an SG system. The SG contains a diesel engine generator (DEG), renewable sources like wind turbine generators(WTGs), solar photovoltaic (PV), and storage elements such as flywheel energy storage systems (FESSs) and battery energy storage systems (BESSs) in conjunction with electric vehicles (EVs). Initially, the dominance of the projected iGTO over the gorilla troops optimizer (GTO) and some recently suggested optimization algorithms are demonstrated by considering benchmark test functions. In the next step, a traditional PID controller is used, and the efficacy of the GTO method is compared with that of the GTO, particle swarm optimization (PSO), and genetic algorithm (GA) methods. In the next stage, the superiority of the proposed FPD-(1+PI) structure over fuzzy PID (FPID) and PID structures is demonstrated under various symmetry operating conditions as well as under different cyberattacks, leading to a denial of service (DoS) and delay in signal transmission. [ABSTRACT FROM AUTHOR]

Although there have already been many works on the model predictive control (MPC) for load frequency control (LFC) of modern power systems, limited works can be found in the literature related to the output feedback MPC. This article studies an N‐step synthesis approach of output feedback MPC for LFC systems considering the problems of communication efficiency and network security. First, to improve the communication efficiency, an adaptive event‐triggering (AET) scheme involving two adaptive laws is designed to reduce the number of transmitted data packages which offers more flexible compared with existing event‐triggering schemes; Second, to handle the network security, a new model of LFC power system combining the AET scheme and random deception attack under an unified framework is established; Moreover, a synthesis approach of output feedback MPC with N‐step strategy is addressed for LFC of power system by parameterizing the infinite control moves into a series of output feedback laws. Compared with the existing predictive load frequency control methods, the present technique is shown as an useful way to improve the control performance since more degrees freedom is introduced by the N‐step strategy. Finally, the simulation experiment is carried out to verify our technique. [ABSTRACT FROM AUTHOR]

This study examines how external auditors respond to the disclosure of cyber exposures by commercial banks and how the COVID-19 pandemic period accentuates the effect of voluntary cyber risk disclosures (CRDs) on audit fees. Our study is a preliminary study analysing the CRD of the financial industry in emerging economies in the Association of Southeast Asian Nations (ASEAN). It extends Calderon and Gao's (2021) study one step further with respect to the COVID-19 pandemic and identifies items by using manually collected keywords to extract CRDs. During the period 2015-2020, our samples are 63 listed banks in four ASEAN members (Indonesia, Malaysia, Thailand, and the Philippines -- ASEAN-4) and the one-step generalized method of moments (GMM) is used. The study found that audit fees are significantly associated with CRD, including risk causes and impacts. Meanwhile, cyber risk governance disclosures affect audit fees after a one-year lag. This indicates that voluntary CRD is informative. Audit fees are also significantly affected by the interaction between CRD and COVID-19. It suggests that auditors incorporate the nature and content of client CRDs into their fee structure and directly support regulatory reporting requirements in emerging ASEAN countries to include cyber risk factors in annual bank statements. [ABSTRACT FROM AUTHOR]

The popularity of cloud computing, with its incredible scalability and accessibility, has already welcomed a new era of innovation. Consumers who subscribe to a cloud-based service and use the associated pay-as-you-go features have unlimited access to the applications mentioned above and technologies. In addition to lowering prices, this notion also increased the reliability and accessibility of the offerings. One of the most crucial aspects of cloud technology is the on-demand viewing of personal services, which is also one of its most significant advantages. Apps that are cloud-based are available on demand from anywhere in the world at a reduced cost. Although it causes its users pain with safety concerns, cloud computing can thrive because of its fantastic instantaneous services. There are various violations, but they all accomplish something similar, taking the systems offline. Distributed denial of service attacks are among the most harmful forms of online assault. For fast and accurate DDoS (Distributed Denial of Service, distributed denial of service) attack detection. This research introduced the DDOS attack and a method to defend against it, making the system more resistant to such attacks. In this scenario, numerous hosts are used to carrying out a distributed denial of service assault against cloud-based web pages, sending possibly millions or even trillions of packets. It uses an OS like ParrotSec to pave the way for the attack and make it possible. In the last phase, the most effective algorithms, such as Naive Bayes and Random Forest, are used for detection and mitigation. Another major topic was studying the many cyber attacks that can be launched against cloud computing.

Machine learning technique which uses artificial neural networks to learn representations. Phishing is a form of fraud in which the attacker tries to learn credential information from the websites. Web phishing is to steal sensitive information such as usernames, passwords and credit card details by way of impersonating a authorized entity. The Hybrid Ensemble Feature Selection is a new feature selection method for machine learning-based phishing detection systems (HEFS). The first step of HEFS involves using a novel Cumulative Distribution Function gradient (CDF-g) algorithm to generate primary feature subsets, which are then fed into a data perturbation ensemble to generate secondary feature subsets. We present the results of our approach and compare them to a few previous studies, with the paper focusing primarily on phishing urls for detecting the unauthorised one by using phishing detection method.

The idea of networked personal medical devices is a component of contemporary Smart Health Systems (SHS). These gadgets offer remote observing and the exchange of wellbeing information, which enormously further develop the patient's personal satisfaction while at the same time reducing treatment expenses for both the patient and the medical care suppliers (telemedicine). For individuals' wellbeing, a cutting edge individual wellbeing record framework is fundamental. Here, there are still difficulties with information mix from different EHRs, information interoperability, and guaranteeing that admittance to information is totally under the power of the patient. Some security issues are caused by the Network. To settle these issues, we propose a novel profound learning-based framework that circuits state of the art decentralized innovations like IPFS and blockchain with wellbeing information interoperability principles and advances like FHIR's APIs. In this review, we show that correspondence between private clinical gadgets is as a matter of fact powerless to different cyber attacks. We show how an outer assailant could involve man-in-the-center, replay, bogus information infusion, and refusal of-administration assaults to block delicate wellbeing information stream by capturing the correspondence of the individual clinical gadget. We likewise suggest an Interruption Recognition Framework (IDS), GAN, to additional screen traffic on private clinical gear and spot attacks against them. Our extensive investigation shows that GAN, with an F1-score of 98 % and an accuracy of 98.7 %, can successfully and accurately recognise numerous assaults on personal medical equipment.