Third-party cyber evaluations involving OpenAI models
openai.com·13h ago
AI Research
arXiv CS.AI·20d ago·5 min read
AI in Cyberpsychology: A systematic literature review of Cybersecurity enhancement by using AI for analyzing psychology of Victims, Attackers, and Defenders
TL;DR
Cybersecurity faces challenges from the psychological aspects of victims, attackers, and defenders. A systematic review identifies how AI can enhance security by analyzing these psychological factors.
✦ Why It Matters
Implement AI models that analyze user behavior to enhance threat detection and response in your cybersecurity systems today.
Key Takeaways
- Investigate AI techniques like ML and NLP for cybersecurity applications.
- Utilize psychological insights to enhance security awareness training.
- Focus on anomaly detection to identify unusual behavior patterns.
- Address identified research gaps to innovate in AI-CPSY applications.
Full Summary
Cybersecurity aims to protect systems and data from digital threats, while cyberpsychology (CPSY) applies psychological principles to improve these security measures. This systematic literature review analyzed 34 studies on AI's role in CPSY, utilizing the PRISMA methodology.
The review categorizes cybersecurity applications into four areas: Anomaly Detection (AD), Vulnerability Risk Prediction (VRP), Security Awareness Training (SAT), and Authentication/Identity Verification (AIV). Each application is further divided by AI techniques such as machine learning (ML), deep learning (DL), natural language processing (NLP), and reinforcement learning (RL).
The review also highlights prevalent psychological concepts and quantifies the datasets used, revealing current implementation statuses. Additionally, it identifies research gaps and emerging methodologies in AI-CPSY, providing insights into future directions for enhancing cybersecurity.