AI and ML Algorithms in Cyber Security
Keywords:
Artificial Intelligence, Cybersecurity, Machine Learning, Threat Intelligence, Incident Response, Adversarial Attacks, Ethical Considerations, Collaborative Defense Strategies.Abstract
The rapid evolution of cyber threats, coupled with the increasing complexity of digital ecosystems, has necessitated more intelligent and adaptive security solutions. Artificial Intelligence (AI) and Machine Learning (ML) have emerged as transformative technologies in the cybersecurity landscape, enabling organizations to proactively detect, prevent, and respond to malicious activities with greater speed and precision. This paper explores the integration of AI and ML algorithms in various cybersecurity applications, including threat detection, incident response, vulnerability management, and user behavior analytics. It also examines the alignment of these technologies with established cybersecurity frameworks and standards such as NIST CSF, ISO/IEC 27001, and the NIST AI Risk Management Framework to ensure ethical, secure, and effective implementation. By evaluating real-world use cases and current challenges, the paper underscores the critical role of AI/ML in building resilient, future-ready cyber defense strategies.
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https://zvelo.com/ai-and-machine-learning-in-cybersecurity
https://www.stanfieldit.com/the-role-of-ai-and-ml-in-business-cyber-security
M. Ozkan-Okay et al., "A Comprehensive Survey: Evaluating the Efficiency of Artificial Intelligence and Machine Learning Techniques on Cyber Security Solutions," in IEEE Access, vol. 12, pp. 12229-12256, 2024, Doi: 10.1109/ACCESS.2024.3355547.
Sai Kiran Arcot Ramesh, "AI-Enhanced Cyber Threat Detection," International Journal of Computer Trends and Technology, vol. 72, no. 6, pp. 64-71, 2024
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