AUTOMATING INCIDENT RESPONSE: AI-DRIVEN APPROACHES TO CLOUD SECURITY INCIDENT MANAGEMENT
Abstract
The increasing integration of cloud computing into modern computerised infrastructures has made security more crucial in the fight against dangers such as data breaches and administrative disruptions. The complexity of cloud environments challenges traditional incident response tactics, which has led to the rise of artificial intelligence (AI) solutions. With a focus on 2020, this study explores AI-driven approaches to cloud security incident management. It covers evolving risks to cloud security and encourages proactive response techniques. Associations can work on event identification, investigation, and objective in real-time by using AI calculations. Important topics bear in mind the role AI plays in threat intelligence, example recognition, and anomaly detection in cloud environments. AI-driven automation makes incident containment easier and decreases the impact of interruptions on operations. Issues with data security and algorithmic inclination, for instance, are looked at.
Keywords: Cyber Incident Response, Machine Learning, Threat Detection, AI-driven threat detection, real-time monitoring, data protection, cloud security solutions, cloud infrastructure.
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Copyright (c) 2020 Chelonian Research Foundation
This work is licensed under a Creative Commons Attribution 4.0 International License.