“Autonomous Cyber Incident Response and Recovery” as a research area involves developing systems and methodologies that enable automatic response and recovery from cyber incidents without or with minimal human intervention. This area is becoming increasingly vital as the scale and complexity of cyber threats grow beyond the capacity of traditional, human-centric approaches. Following are some specific aspects and potential research projects in this domain:
- Self-Healing Networks and Systems: Projects here aim to develop networks and systems that can automatically detect breaches or failures and reconfigure themselves to maintain functionality, effectively healing from attacks or technical issues without human intervention.
- Predictive Analytics for Cybersecurity: Utilizing machine learning to predict and pre-emptively counter cyber threats based on trends, anomalies, and patterns in network data.
- Automated Response to Security Incidents: Developing systems that can not only detect threats but also execute predefined actions to mitigate or neutralize those threats. This can include isolating affected systems, deploying patches, or changing network configurations.
- AI-Based Risk Assessment and Management: Projects that focus on using AI to continuously assess cybersecurity risks in real-time and automatically adjust security postures accordingly.
- Legal and Ethical Implications of Autonomous Response: Investigating the legal and ethical boundaries of autonomous cyber incident response, especially concerning privacy, data protection, and accountability.
- Collaborative Autonomous Systems for Cyber Defense: Developing systems that collaborate with other autonomous systems, sharing information and strategies to enhance overall cyber defense capabilities.