Threat Of Cyber Attacks Research Articles

Improving Collaborative Intrusion Detection System Using Blockchain and Pluggable Authentication Modules for Sustainable Smart City

The threat of cyber-attacks is ever increasing in today’s society. There is a clear need for better and more effective defensive tools. Intrusion detection can be defined as the detection of anomalous behavior either in the host or in the network. An intrusion detection system can be used to identify the anomalous behavior of the system. The two major tasks of intrusion detection are to monitor data and raise an alert to the system administrators when an intrusion takes place. The current intrusion detection system is incapable of tackling sophisticated attacks which take place on the entire network containing large number of nodes while maintaining a low number of login attempts on each node in the system. A collaborative intrusion detection system (CIDS) was designed to remove the inefficiency of the current intrusion detection system which failed to detect coordinated distributed attacks. The main problem in the CIDS is the concept of trust. Hosts in the network need to trust the data sent by other peers in the network. To bring in the concept of trust and implement the proof-of-concept, blockchain was used. Pluggable authentication modules (PAM) were also used to track login activity securely before an intruder could modify the login activity. To implement blockchain, an Ethereum-based private blockchain was used.

Analysis of Attacks and Cybersecurity in the Health Sector During a Pandemic COVID-19: Scoping Review

COVID-19 as a global pandemic in March 2020 medical personnel and all types of patients with various chronic conditions is undeniably the largest group of users of digital technology during the pandemic. Increased exposure and massive use of the internet is certainly a potential security threat in itself, especially in the threat of cyber-attacks. The purpose of this study is to analyze cyber-attacks and security in the health sector during the COVID 19 pandemic. The scoping review was conducted by searching two main scientific databases (PubMed and Scopus) using the search formula “COVID 19, Pandemic and cyber-attack, cyber security.” Reports, news articles or websites are also included if they are directly related to previously published work, or if they are the only sources available at the time of writing. Only articles in English published in the last decade are included (i.e., 2009-2020) to focus on current problems, challenges, and solutions. In total, 34 papers were included in the review. We found information technology in the health sector that was used during the COVID 19 pandemic. The COVID-19 pandemic situation is a type of non-traditional security that has a broad impact on various aspects of human life, including the health sector. At a time when many countries have responded to the pandemic situation with various restrictive policies to the prohibition of mobilization, people are adapting by shifting to a new landscape of activity. The cyber world is then used by the community to continue to run productivity. This then has implications for the increase in internet users globally, including Indonesia. Some of the cyberattacks include the practice of phishing emails targeting individual and corporate entities, ransomware targeting healthcare facilities and companies. Further research is needed, especially exploring research on cyber-attacks during a pandemic from the point of view of implementation of cyber security.

Maritime autonomous surface ships (MASS) in Gulf of Suez: safety of navigation precautionary measures

The effects of automation on human safety and environmental protection are generally acknowledged. Maritime Autonomous Surface Ships (MASS) improvements may help eliminate human error and greatly increase overall safety, but they are also likely to pose new threats, particularly given the marine industry's growing interest in MASS. Using a questionnaire, we determined that "communication with human-operated ships" poses the greatest threat to the success of MASS operations, followed by "the threat of cyber-attacks," "the human factor," and "equipment failure." According to our findings, this study sheds light on the impact of MASS on education and training, as well as the most serious threats posed by MASS to the safety of navigation and the marine environment in the Gulf of Suez, and proposes a process, requirements, and legislation for MASS transit in the Gulf of Suez.

MACHINE LEARNING ALGORITHMS FOR DETECTION OF CYBER THREATS USING LOGISTIC REGRESSION

The threat of cyberattacks is expanding globally; thus, businesses are developing intelligent artificial intelligence systems that can analyze security and other infrastructure logs from their systems department and quickly and automatically identify cyberattacks. Security analytics based on machine learning the next big thing in cybersecurity is machine data, which aims to mine security data to show the high maintenance costs of static relationship rules and methods. But, choosing the appropriate machine learning technique for log analytics using ML continues to be a significant barrier to AI success in cyber security due to the possibility of a substantial number of false-positive detections in large-scale or global Security Operations Centre (SOC) settings, selecting the proper machine learning technique for security log analytics remains a substantial obstacle to AI success in cyber security. A machine learning technique for a cyber threat exposure system that can minimize false positives is required. Today's machine learning methods for identifying threats frequently use logistic regression. Logistic regression is the first of three machine learning subcategories—supervised, unsupervised, and reinforcement learning. Any machine learning enthusiast will encounter this supervised machine learning algorithm at the beginning of their machine learning career. It's an essential and often applied classification algorithm.

Access Control Application Prevention and Mitigation of Cyber Attacks

In the rapidly evolving landscape of cyber threats, safeguarding digital assets has become paramount for organizations worldwide. This paper presents a comprehensive analysis of access control applications as a frontline defense against cyber intrusions. We delve into the mechanics of contemporary access control systems, highlighting their role in preventing unauthorized access and ensuring data integrity. Drawing on real-world case studies, we demonstrate the efficacy of robust access control measures in thwarting cyber-attacks and mitigating their potential impacts. Further, we explore the challenges faced in implementing these systems, such as ensuring scalability, managing user privileges, and maintaining system resilience. Our findings underscore the indispensable nature of access control applications in today’s digital age. By offering actionable insights and best practices, this paper aims to guide organizations in fortifying their digital infrastructures against the ever-present threat of cyberattacks. To ensure the security of data, it’s essential to update automation processes periodically. This not only safeguards the transfer of information, ensuring its authenticity and confidentiality, but also prevents tampering or misinformation. Incorporating access control into the security strategy can address this concern. Access control restricts data access to designated individuals within the organization. However, there’s an inherent risk: permissions could inadvertently be granted to unintended parties. To mitigate this, we recommend several solutions, with multifactor authentication being a prominent option for future implementation.

An Review - Smartphone and Tablet Cyberattack Threat Detection

An Review - Smartphone and Tablet Cyberattack Threat Detection

Comparison of Personal Data Protection Laws Using Narrative Policy Framework Between Indonesia, Malaysia, and Japan

The era of information and communication technology continues to grow and shows a significant increase. is a type of offensive maneuver used by a state, individual, group, or organization that targets computer information systems, infrastructure, computer networks, and or personal computer devices using malicious acts which usually originate from anonymous sources who steal, modify or destroy the specified target by hacking a vulnerable system. Cyberattacks can happen in any part of the country. The increasing use of the internet has the risk of increasingly massive hacking threats. The National Cyber and Crypto Agency (BSSN) noted that until April 2022, cyber attacks in Indonesia reached 100 million cases. This research benchmarks the situation of cyber attacks and personal data protection regulations in Indonesia with countries that have better handling of cyber crimes. The method is to compare narrative elements in the form of heroes, villains, and victims in each country, using the Narrative Policy Framework (NPF) analysis method. The Narrative Policy Framework is an approach or research framework on the public policy process, it is identified that the hero character represented by comprehensive personal data protection regulations has long been used by Japan and Malaysia. The character of heroes in Indonesia seems not to be too dominant because there are villains who are present in the form of the absence of unified regulations for the protection of personal data from the threat of cyber attacks

Impact Evaluation of Cyberattacks on Connected and Automated Vehicles in Mixed Traffic Flow and Its Resilient and Robust Control Strategy.

Connected and automated vehicles (CAVs) present significant potential for improving road safety and mitigating traffic congestion for the future mobility system. However, cooperative driving vehicles are more vulnerable to cyberattacks when communicating with each other, which will introduce a new threat to the transportation system. In order to guarantee safety aspects, it is also necessary to ensure a high level of information quality for CAV. To the best of our knowledge, this is the first investigation on the impacts of cyberattacks on CAV in mixed traffic (large vehicles, medium vehicles, and small vehicles) from the perspective of vehicle dynamics. The paper aims to explore the influence of cyberattacks on the evolution of CAV mixed traffic flow and propose a resilient and robust control strategy (RRCS) to alleviate the threat of cyberattacks. First, we propose a CAV mixed traffic car-following model considering cyberattacks based on the Intelligent Driver Model (IDM). Furthermore, a RRCS for cyberattacks is developed by setting the acceleration control switch and its impacts on the mixed traffic flow are explored in different cyberattack types. Finally, sensitivity analyses are conducted in different platoon compositions, vehicle distributions, and cyberattack intensities. The results show that the proposed RRCS of cyberattacks is robust and can resist the negative threats of cyberattacks on the CAV platoon, thereby providing a theoretical basis for restoring the stability and improving the safety of the CAV.

A hybrid intelligently initialized particle swarm optimizer with weight factored binary gray wolf optimizer for mitigation of security issues in Internet of Things and sensor nodes

SummaryWith expanding nature of Internet of Things (IoT) based solutions in various application areas, the threat of cyber attacks is looming large. Often for resource constrained IoT nodes, implementation of machine learning based intrusion detection system is not practical, as the feature set to be processed is large in size. In this article, random forest based intelligently initialized hybrid binary particle swarm optimizer (PSO)‐gray wolf optimizer (GWO) is proposed to reduce the dimensions of dataset. The proposed algorithm exploits the concept of relative weights of the leader wolves of GWO to update the positions of particles in PSO. A novel fitness function is also introduced, that includes the key performance metrics for measuring the classification efficiency. Also, a new performance metric is proposed here for commensurate comparison with other related works, which renders the task of comparison effective. For experimental evaluation, the historical dataset NSL‐KDD and the more contemporary DS2OS dataset are both taken into consideration. The proposed work attains accuracy up to 99.61% for NSL‐KDD dataset and 99.79% for DS2OS dataset. The outcomes are better than majority of algorithms and recent related works. Most notably, for increasing the accuracy, the number of features are not compromised and are even reduced to 8 and 5 features, respectively, for NSL‐KDD and DS2OS.

Secure Data Transmission and Trustworthiness Judgement Approaches Against Cyber-Physical Attacks in an Integrated Data-Driven Framework

Threats of cyberattacks have penetrated from disclosing critical user information to destroying/manipulating industrial control systems. Study on data security during network transmission has raised increasing attention in the systems and control community, which is found very necessary and timely in the context of Industry 4.0. In most existing approaches, the protection of the transmitted data from eavesdropping attacks and the detection of malicious integrity attacks are usually carried out separately. In this study, an integrated data-driven framework applicable at the control level is proposed to deal with secure transmission and attack detection simultaneously. In the framework, a secure correlation-based encryption/decryption approach and a trustworthiness judgement approach are proposed. Comprehensive discussions are made regarding the analysis of the sensitivity to attacks, the introduced time delay, and the design degree-of-free. Executable algorithms are presented, corresponding to which hardware is modularized and can work standalone independent from the configuration of the monitoring and control systems or any third-party authentication agencies. Evaluation results on a simulated two-area frequency-load control power grid system are provided to show the effectiveness and performance of the proposed approaches.

Review: Environmental Politics of the Middle East, edited by Harry Verhoeven

Review: <i>Environmental Politics of the Middle East</i>, edited by Harry Verhoeven

CGFuzzer: A Fuzzing Approach Based on Coverage-Guided Generative Adversarial Networks for Industrial IoT Protocols

With the widespread application of the Industrial Internet of Things (IIoT), industrial control systems (ICSs) greatly improve industrial productivity, efficiency, and product quality. However, IIoT protocols as the bridge of different parts of ICSs are vulnerable to be attacked due to their vulnerabilities. To reduce cyberattack threats, we need to find the vulnerabilities of IIoT protocols by using efficient vulnerability mining methods, such as fuzzing. Fuzzing is often used to mine vulnerabilities for IIoT protocols. However, the traditional fuzzing methods for IIoT protocols have a low passing rate and low code coverage. To solve these problems, we propose a generative adversarial network (GAN), here referred to as coverage-guided GANs (CovGAN), which aims to generate test cases with a high passing rate and code coverage by learning IIoT protocol specifications. Based on the CovGAN, we construct a fuzzing framework (CGFuzzer) for IIoT protocols. Finally, we design a protocol simulator to verify the CovGAN performance. Experimental results show that the proposed methodology outperforms approximately 5%, 7%, and 39% of the passing rate of GANFuzz, SeqFuzzer, and Peach, respectively. In addition, CGFuzzer has a significant improvement in code coverage, which is about 17%, 24%, and 31% higher than GANFuzz, SeqFuzzer, and Peach, respectively.

Cyber-attacks on Space Activities: Revisiting the Responsibility Regime of Article VI of the Outer Space Treaty

Both international society and individual states are placing considerable emphasis on the imminent threats of cyber-attacks on space activities. States play a major role in combatting against cyber-attacks in the space; thus, their international responsibility regime requires re-examination within this unique context. This study analyzes the responsibility regime established by Article VI of the Outer Space Treaty (OST) aiming to adapt the time-honored provisions to the current challenges posed by space cyber-attacks. Simultaneously, it aims to focus on three aspects: attribution rules, the scope of obligations of States Parties and the specific measures that states should undertake. This study concludes that in situations of space cyber-attacks, a case-tailored method should be adopted to identify the responsible state. This may likely involve the broadening of states' obligations, invocation of Article 2(4) of the United Nations Charter, the due diligence obligations, and other lex specialis obligations, such as conducting space activities for peaceful purposes, due regard obligations and non-interference obligations. Furthermore, the conclusion suggests that states should act nationally as well as internationally to successfully combat against cyber-attacks on space activities.

Deployment of Honeypot and SIEM Tools for Cyber Security Education Model In UITM

Nowadays the threat of cyber-attacks is increasing as more organizations undergo digital transformation. Therefore, organizations need to take proactive measures to mitigate the cyber threat to avoid further loss to their business. To mitigate cyber risk effectively, organizations need to employ competent people in the IT security team to implement effective security controls. But there is a shortage of cyber security talent or professionals in the job market and to produce talents in the cyber security field requires extensive effort in education and training. A good cyber security education program should have to date curriculum and provide practical experience. To achieve this, the program must be supported by a cyber security lab equipped with various software, equipment, and tools used by a real professional in the industry. Therefore, this paper proposed a model of a cyber security lab equipped with honeypot and SIEM systems to enhance the quality of cyber security education. The cyber security lab based on the model was deployed at Universiti Teknologi MARA (UiTM) and used for teaching and learning activities. The honeypot will provide student experience analyzing the behaviour of hackers while the SIEM system will aggregate the logs data of the Campus Network Firewall in real-time. To evaluate the effectiveness of the proposed lab model, a functional test and a survey was conducted. The survey result shows that majority of the respondent agreed that the cyber security lab improve their teaching and learning experience while taking the cyber security subject.

Readiness for Radiation Treatment Continuity: Survey on Contingency Plans Against Cyberattacks

PurposeCyberattacks on health care systems have been on the rise over the past 5 years. Formulation and implementation of a robust postattack business continuity plan and/or contingency plan (CP) is essential for minimal disruption to patient care. The level of awareness and planning within the radiation oncology community for cyberattacks is not clear. This study was undertaken to survey and assess cyberattack CP awareness and preparedness. Methods and MaterialsA survey instrument comprising 5 questions on awareness and preparedness of cyberattack CPs was e-mailed to 150 radiation oncology departments. Recipients included 105 institutions with residency programs in therapeutic medical physics, as listed by the Commission on Accreditation of Medical Physics Education Program (usually either school-based or large institutional settings), and 45 additional smaller settings within the United States, representing community practices. ResultsForty-three responses were deemed evaluable for analysis. Forty-two percent (18 respondents) of respondents responded that they are well-aware of the concept of a cyberattack CP. A large discrepancy in awareness exists between larger hospitals (LH) that have 5 or more treatment machines and smaller hospitals (SH) that have 4 or fewer, 54% versus 24 % (P < .05). Fifty-eight percent of respondents considered it “essential” to have such a plan in place, and 28% considered it “desirable” to do so but not practical. Nine percent regarded a cyberattack CP as unnecessary. No significant differences in responses were noted among different types or sizes of institutions on this issue. Sixty-two percent of LH responded that they were either preparing or evaluating a CP, compared with only 29% of SH (P = .03). However, no respondents explicitly replied that they already had a CP in place in their practices. ConclusionsThe importance of cyberattack preparedness and implementation does not seem to be well-recognized in radiation oncology. Both the awareness and the preparedness of SH are substantially less than those of LH. Specific and ongoing education efforts in parallel with development of appropriate programs are needed to counter the increasingly pervasive and complex threat of cyberattacks.

Detection of Malicious Attacks in Autonomous Cyber-Physical Inverter-Based Microgrids

The distributed generation capabilities of microgrids (MGs) arise as essential assets in enhancing grid resilience. The integration of distributed energy sources, controllable loads, and prosumers necessitates the deployment of potent control and communication synergies. While those synergies transform MGs into cyber-physical systems through information technologies able to sense, control, and actuate local resources and loads, they inadvertently expose MGs to cyber-attack threats. Increasing the security of critical communication and control systems against “black swan” events, i.e., high-impact low-probability cyber-physical incidents, is a major priority for MG operations. Such incidents, if left unabated, can intensify and elicit system dynamics instability, eventually causing outages and system failures. In this article, we develop an integrated approach for multiagent MG systems able to perform the detection of malicious cyber-physical attacks based on subspace methods. We employ the small-signal model of an autonomous/islanded MG and consider different attack models targeting the MG’s secondary frequency control. The attack detector is constructed via identifying the stable kernel representation of the autonomous cyber-physical MG in the attack-free case. We illustrate the impact of the attack models as well as the feasibility of the developed detection method in simulation models of the Canadian urban benchmark distribution system.

The hidden threat of cyber-attacks – undermining public confidence in government

ABSTRACT This paper argues that the primary threat posed by cyber-attacks is not cataclysmic physical destruction - but rather more insidious societal risks such as reduced trust in government. To test this claim, we collect and analyze survey data in the immediate aftermath of a ransomware attack against a Düsseldorf hospital (n = 707). We find that exposure to cyber-attacks significantly diminishes public confidence among segments of the population who are exposed to the attack. Cyber-attacks exploit particular qualities of cyberspace that are directly tied to matters of public confidence, causing a precipitous drop in public trust. Second, we identify the psychological mechanism underpinning this effect, with anger and dread intervening in countervailing directions. Feelings of anger triggered by exposure to cyber-attacks amplify public confidence, while the more potent feeling of dread reduces confidence. Our findings verify that governments cannot rely on a unifying social-cohesion effect following cyber-attacks since the public is liable to perceive the authorities as incapable of defending against future threats. We conclude by discussing why escalating cyber-threats can cause severe social upheaval and reduce trust in democratic institutions, and discuss what constitutes exposure to the new generation of attacks in cyberspace.

Sociocultural Orientation and Perceived Utility of Base Rates in Self and Social Judgments of Cyber Risk

Despite ground-breaking technological advances, scientists still have difficulty patching one of the most threatening bugs in the cyber world: human error. Individuals constitute a unique vulnerability in cybersecurity because they systematically make errors when perceiving their own risk. Specifically, individuals underestimate their own susceptibility to cyber-attacks. Among the most common ways companies seek to improve security is presenting clients and employees with base rate information on the prevalence of cyber threats and the likelihood of the general population to succumb to them. This strategy is intended to increase the accuracy with which clients and employees assess their threat levels. However, outcomes typically fall short of this goal. We review the differential use of base rate information as a cognitive and motivational bias that contributes to forecasting errors and accuracy in self and social risk assessment. We also examine two dimensions of sociocultural orientation: individualism-collectivism and tightness-looseness-and their potential influence on the use of base rate information. We discuss implications for interventions that could mitigate the threat of cyber-attacks

Hospital cybersecurity risks and gaps: Review (for the non-cyber professional).

BackgroundHealthcare is facing a growing threat of cyberattacks. Myriad data sources illustrate the same trends that healthcare is one of the industries with the highest risk of cyber infiltration and is seeing a surge in security incidents within just a few years. The circumstances thus begged the question: are US hospitals prepared for the risks that accompany clinical medicine in cyberspace?ObjectiveThe study aimed to identify the major topics and concerns present in today's hospital cybersecurity field, intended for non-cyber professionals working in hospital settings.MethodsVia structured literature searches of the National Institutes of Health's PubMed and Tel Aviv University's DaTa databases, 35 journal articles were identified to form the core of the study. Databases were chosen for accessibility and academic rigor. Eighty-seven additional sources were examined to supplement the findings.ResultsThe review revealed a basic landscape of hospital cybersecurity, including primary reasons hospitals are frequent targets, top attack methods, and consequences hospitals face following attacks. Cyber technologies common in healthcare and their risks were examined, including medical devices, telemedicine software, and electronic data. By infiltrating any of these components of clinical care, attackers can access mounds of information and manipulate, steal, ransom, or otherwise compromise the records, or can use the access to catapult themselves to deeper parts of a hospital's network. Issues that can increase healthcare cyber risks, like interoperability and constant accessibility, were also identified. Finally, strategies that hospitals tend to employ to combat these risks, including technical, financial, and regulatory, were explored and found to be weak. There exist serious vulnerabilities within hospitals' technologies that many hospitals presently fail to address. The COVID-19 pandemic was used to further illustrate this issue.ConclusionsComparison of the risks, strategies, and gaps revealed that many US hospitals are unprepared for cyberattacks. Efforts are largely misdirected, with external—often governmental—efforts negligible. Policy changes, e.g., training employees in cyber protocols, adding advanced technical protections, and collaborating with several experts, are necessary. Overall, hospitals must recognize that, in cyber incidents, the real victims are the patients. They are at risk physically and digitally when medical devices or treatments are compromised.

A Novel Decentralized Blockchain Architecture for the Preservation of Privacy and Data Security against Cyberattacks in Healthcare.

Nowadays, in a world full of uncertainties and the threat of digital and cyber-attacks, blockchain technology is one of the major critical developments playing a vital role in the creative professional world. Along with energy, finance, governance, etc., the healthcare sector is one of the most prominent areas where blockchain technology is being used. We all are aware that data constitute our wealth and our currency; vulnerability and security become even more significant and a vital point of concern for healthcare. Recent cyberattacks have raised the questions of planning, requirement, and implementation to develop more cyber-secure models. This paper is based on a blockchain that classifies network participants into clusters and preserves a single copy of the blockchain for every cluster. The paper introduces a novel blockchain mechanism for secure healthcare sector data management, which reduces the communicational and computational overhead costs compared to the existing bitcoin network and the lightweight blockchain architecture. The paper also discusses how the proposed design can be utilized to address the recognized threats. The experimental results show that, as the number of nodes rises, the suggested architecture speeds up ledger updates by 63% and reduces network traffic by 10 times.