A Comprehensive Survey: Evaluating the Efficiency of Artificial Intelligence and Machine Learning Techniques on Cyber Security Solutions

IEEE Access, Год журнала: 2024, Номер 12, С. 12229 - 12256

Опубликована: Янв. 1, 2024

Given the continually rising frequency of cyberattacks, adoption artificial intelligence methods, particularly Machine Learning (ML), Deep (DL), and Reinforcement (RL), has become essential in realm cybersecurity. These techniques have proven to be effective detecting mitigating which can cause significant harm individuals, organizations, even countries. learning algorithms use statistical methods identify patterns anomalies large datasets, enabling security analysts detect previously unknown threats. learning, a subfield ML, shown great potential improving accuracy efficiency cybersecurity systems, image speech recognition. On other hand, RL is again machine that trains learn through trial error, making it dynamic environments. We also evaluated usage ChatGPT-like AI tools cyber-related problem domains on both sides, positive negative. This article provides an overview how DL, are applied cybersecurity, including their malware detection, intrusion vulnerability assessment, areas. The state-of-the-art studies using models each section based main idea, techniques, important findings. It discusses these techniques' challenges limitations, data quality, interpretability, adversarial attacks. Overall, holds promise for effectiveness systems enhancing our ability protect against cyberattacks. However, continue developing refining address ever-evolving nature cyber Besides, some promising solutions rely deep reinforcement susceptible attacks, underscoring importance factoring this when devising countermeasures sophisticated concluded ChatGPT valuable tool but should noted manipulated threaten integrity, confidentiality, availability data.

Язык: Английский

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CYBERSECURITY AWARENESS AND EDUCATION PROGRAMS: A REVIEW OF EMPLOYEE ENGAGEMENT AND ACCOUNTABILITY

Computer Science & IT Research Journal, Год журнала: 2024, Номер 5(1), С. 100 - 119

Опубликована: Янв. 11, 2024

As organizations continue to grapple with the escalating threat landscape of cyber-attacks, imperative fortify their cybersecurity defenses becomes increasingly paramount. This review delves into critical realm awareness and education programs, focusing on pivotal factors employee engagement accountability. The effectiveness these programs in cultivating a cyber-resilient workforce is scrutinized through an extensive examination existing literature, empirical studies, industry practices. begins by exploring foundational elements elucidating significance imparting knowledge instilling culture vigilance among employees. It examines diverse methodologies employed ranging from interactive workshops simulated phishing exercises online modules gamified learning platforms. A comparative analysis approaches sheds light respective strengths limitations. central theme this revolves around nexus between resilience. psychological behavioral aspects engagement, assessing how motivational tailored experiences contribute heightened awareness. impact organizational leadership support fostering sense responsibility employees also explored, emphasizing need for holistic approach that transcends mere compliance. Furthermore, investigates role accountability sustaining efficacy initiatives. mechanisms enforce adherence security policies protocols, robust monitoring systems, clear communication channels, consequence management. Case studies real-world examples are integrated illustrate instances successful frameworks influence overall posture. synthesizes key findings identifies emerging trends particular focus optimizing insights gleaned provide roadmap seeking against evolving cyber threats vigilant proactive workforce. Keywords: Cybersecurity, Education, Cyber threat, Employee Accountability.

Язык: Английский

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The intersection of Artificial Intelligence and cybersecurity: Challenges and opportunities

World Journal of Advanced Research and Reviews, Год журнала: 2024, Номер 21(2), С. 1720 - 1736

Опубликована: Фев. 28, 2024

The fusion of artificial intelligence (AI) with cybersecurity represents a paradigm shift in our efforts to safeguard digital assets against dynamic threat landscape. This manuscript comprehensively analyses AI's transformative role cybersecurity, covering foundational principles, advanced methodologies, and ethical considerations. article begins exploring fundamental AI techniques such as machine learning natural language processing. delineates their applications bolstering detection, vulnerability analysis, incident response. Traditional approaches analysis are juxtaposed AI-driven highlighting the efficacy automated scanning, prioritization, adaptive risk assessment. Moreover, delves into pivotal automation expediting response, minimizing human error, fortifying overall security postures. Ethical privacy concerns surrounding deployment carefully examined, emphasizing importance responsible decision-making, protection, transparency. Looking ahead, emerging trends adversarial zero trust present promising avenues for further exploration, offering opportunities enhance resilience evolving threats.

Язык: Английский

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Artificial intelligence (AI) cybersecurity dimensions: a comprehensive framework for understanding adversarial and offensive AI

AI and Ethics, Год журнала: 2024, Номер unknown

Опубликована: Фев. 15, 2024

Abstract As Artificial Intelligence (AI) rapidly advances and integrates into various domains, cybersecurity emerges as a critical field grappling with both the benefits pitfalls of AI technologies. This paper explores multifaceted dimensions AI-driven cyberattacks, offering insights their implications, mitigation strategies, underlying motivations, profound societal impacts. The research centres on developing presenting Cybersecurity Dimensions (AICD) Framework, comprehensive, multidimensional schema designed to guide academics, policymakers, industry professionals in understanding combating evolving challenges posed by cyber threats. unveils complex dynamics offensive AI, stressing need for adaptive defences ethical considerations. Concurrently, study highlights adversarial threats, calling proactive measures address potential ramifications. Through rigorous textual analyses extensive literature reviews, underscores urgency interdisciplinary approaches bridge technology-humanity chasm traditionally observed discussions. By synthesising these diverse elements, AICD Framework an instrumental tool holistic practical interventions AI-infused landscape. concludes urgent call collaborative efforts practice navigate intricate capitalise opportunities borne from convergence cybersecurity.

Язык: Английский

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THEORETICAL INSIGHTS INTO SECURING REMOTE MONITORING SYSTEMS IN WATER DISTRIBUTION NETWORKS: LESSONS LEARNED FROM AFRICA-US PROJECTS

Engineering Science & Technology Journal, Год журнала: 2024, Номер 5(3), С. 995 - 1007

Опубликована: Март 24, 2024

This review paper delves into the critical realm of securing remote monitoring systems within water distribution networks, illuminating theoretical insights and practical lessons gleaned from collaborative projects between Africa United States. Given pivotal role networks in public health safety, integrating offers substantial benefits operational efficiency resource management. However, this integration also introduces significant security vulnerabilities that pose risks to infrastructure data's integrity, availability, confidentiality. Through a comprehensive analysis, explores multifaceted challenges inherent these systems, underscores importance robust frameworks for cybersecurity, highlights effective practices derived international collaboration projects. It proposes principles designing, implementing, managing secure emphasizing necessity defence-in-depth strategies, principle least privilege, continuous adaptive response mechanisms. Furthermore, it identifies ongoing future directions research, stressing dynamic nature cybersecurity threats potential emerging technologies fortify measures. The advocates sustained efforts research navigate evolving landscape ensuring their resilience against threats. Keywords: Remote Monitoring Systems, Water Distribution Security, Cybersecurity Frameworks.

Язык: Английский

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GRACE: Empowering LLM-based software vulnerability detection with graph structure and in-context learning

Journal of Systems and Software, Год журнала: 2024, Номер 212, С. 112031 - 112031

Опубликована: Март 21, 2024

Язык: Английский

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Cyber Resilience Framework: Strengthening Defenses and Enhancing Continuity in Business Security

International Journal of Computing and Digital Systems, Год журнала: 2024, Номер 15(1), С. 1315 - 1331

Опубликована: Март 10, 2024

This study presents a comprehensive Cybersecurity Resilience Framework designed to fortify organizational defenses against the evolving landscape of cyber threats while enhancing business continuity.The aim is provide businesses with robust and adaptive strategy that extends beyond traditional cybersecurity paradigms.This employs methodology grounded in an extensive literature review inform conceptualization iterative development resilient framework, integrating key elements from established sources aligning industry wisdom.By governance leadership principles, collaboration external stakeholders, continuous monitoring, framework fosters holistic approach resilience.Leveraging behavioral perspective, explores human factors, user awareness, decision-making processes, recognizing critical role culture fostering cybersecurity-aware ethos.Findings reveal roadmap includes technology resilience, regular audits, assessments, emphasizing evidence-based improvements.The addresses resource constraints, regulatory variability, dynamic threat landscape, promoting adaptability face diverse contexts.The significance this lies its contribution ongoing evolution resilience strategies, offering organizations practical guide navigate complexities digital realm.As increasingly rely on interconnected technologies, stands as vital tool for security, safeguarding assets, ensuring continuity ever-changing landscape.

Язык: Английский

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SYNTHESIZING AI'S IMPACT ON CYBERSECURITY IN TELECOMMUNICATIONS: A CONCEPTUAL FRAMEWORK

Computer Science & IT Research Journal, Год журнала: 2024, Номер 5(3), С. 594 - 605

Опубликована: Март 18, 2024

As the telecommunications sector increasingly relies on interconnected digital infrastructure, proliferation of cyber threats poses significant challenges to security and operational integrity. This review presents a conceptual framework for understanding harnessing potential artificial intelligence (AI) in fortifying cybersecurity within industry. The integrates transformative capabilities AI with unique demands telecommunications, aiming enhance threat detection, mitigation, response strategies. It encompasses multidimensional approach that both technical organizational facets, recognizing interconnectedness technology, human factors, regulatory environments. Firstly, delves into application bolstering proactive gathering analysis. Through advanced algorithms machine learning techniques, empowers telecom operators identify anomalous patterns, predict vulnerabilities, pre-emptively adapt defensive measures. Secondly, it explores AI-driven solutions dynamic risk assessment adaptive protocols. By leveraging real-time data analytics automated decision-making, networks can swiftly evolving ensure continuous protection against intrusions or breaches. Furthermore, emphasizes role augmenting through intelligent automation cognitive assistance. offloading routine tasks providing context-aware insights, enables professionals focus strategic initiatives complex scenarios. Lastly, addresses imperative ethical considerations, accountability, transparency deploying telecommunications. advocates responsible governance frameworks prioritize privacy, fairness, bias mitigation while fostering collaboration across industry stakeholders. In summary, this provides roadmap AI's fortify resilience thereby safeguarding critical infrastructure ensuring integrity global communication networks. Keywords: AI, Cybersecurity, Telecommunication, Framework, Conceptual, Impact, Review.

Язык: Английский

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Evolving Access Control Paradigms: A Comprehensive Multi-Dimensional Analysis of Security Risks and System Assurance in Cyber Engineering

Asian Journal of Research in Computer Science, Год журнала: 2024, Номер 17(5), С. 108 - 124

Опубликована: Март 8, 2024

This study evaluates the effectiveness of traditional access control paradigms—Role-Based Access Control (RBAC), Policy-Based (PBAC), and Attribute-Based (ABAC)—against ransomware threats in critical infrastructures examines potential benefits integrating machine learning (ML) artificial intelligence (AI) technologies. Utilizing a quantitative research design, investigation collected data from 383 cybersecurity professionals across various sectors through systematically structured questionnaire. The questionnaire, which demonstrated excellent internal consistency with reliability score 0.81, featured Likert scale questions aimed at assessing perceptions experiences concerning efficacy different models combating ransomware. Employing multiple regression analysis, explored relationship between paradigms their capability to mitigate risks, while also considering impact awareness among employees. findings indicate that methods are less effective against dynamic nature attacks, primarily due static configurations. In contrast, integration ML AI into systems significantly enhances adaptability detecting preventing incidents. Additionally, highlights crucial role training employees fortifying cyber threats. adoption layered security strategy, incorporating advanced technological solutions comprehensive practices, was found markedly improve resilience attacks. Based on these insights, recommends embrace technologies systems, prioritization for all organizational members, implementation multifaceted approach better defend evolving threat These strategies essential safeguarding continuity services an increasingly digital interconnected world.

Язык: Английский

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A survey of large language models for cyber threat detection

Computers & Security, Год журнала: 2024, Номер 145, С. 104016 - 104016

Опубликована: Июль 25, 2024

Язык: Английский

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