Risk Assessment of Artificial Intelligence Systems in Cybersecurity
Keywords:
cybersecurity, NIST, Risk mitigation, vulnerabilities, methodologiesAbstract
The article focuses on the vital function of AI (Artificial Intelligence) in cybersecurity measures and argues for effective risk assessment techniques in AI-powered cybersecurity. In this section, the article explored AI in cybersecurity by emphasizing the AI technologies that are in use and what their applications are in the field of threat detection, vulnerability management, and proactive defense mechanisms. Moreover, the article looked into the AI security risk types, such as malicious AI, biases, fairness issues, potential vulnerabilities, and the ethical questions the AI process causes. The paper explained the concepts of frameworks and methodologies for assessing risks in AI systems, beginning with existing risk assessment frameworks, such as the NIST cybersecurity framework and the FAIR framework methodologies. Risk mitigation strategies of AI systems, regulatory and ethical issues, and future AI and cybersecurity problems concerning technological progress are also assessed. As concluded, implementing regulations for compliance, ethical principles, and technological developments is the key to meeting the new challenges and developing safe and sustainable digital systems. The recommendations comprise fostering transparency, accountability, and continuous education and awareness programs to enable people to manage ethical dilemmas and mitigate the risks very well.
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