AI-Supported Incident Response Management in Cybersecurity Operations

Abstract

As cyber threats continue to become more complex and more frequent, organizations are encountering a major challenge in the process of making their cybersecurity operations effective in terms of incident response management (IRM). AI-assisted incident response management employs advanced machine learning and artificial intelligence tools to automate, optimize, and improve the process of decision-making, allowing detecting, identifying, and mitigating security incidents much faster and more accurately. With the use of AI technologies, including anomaly detection, predictive analytics, natural language processing, and deep learning, AI systems can effectively process extensive amounts of data, detect new threats, and minimize the human effort in response activities with time constraints. This abstract will discuss the role of AI in IRM systems and how it can simplify threat intelligence, prioritize attacks, and automate regular responses. Moreover, it emphasizes the application of AI-based tools to enhance the efforts of security teams, shorten the response time, and minimize the possible consequences of cyber attacks. The article also addresses the difficulties and constraints of applying AI in cybersecurity operations, such as of accuracy, ethical issues and the dynamism of cyberattacks. With the further development of AI, its application to incident response management is likely to increase, and organizations will be provided with an opportunity to withstand more complex cyber threats more efficiently and retain their efficiency.