AI Cybersecurity Identity Threats in 2026: A Theoretical Analysis
Abstract
Artificial intelligence (AI) has significantly transformed the cybersecurity landscape by enabling both advanced defensive systems and highly adaptive attack mechanisms. Identity-based cyber threats, such as deepfake impersonation, AI-driven phishing, and autonomous identity exploitation, are emerging as dominant vectors of cyber risk. Existing identity management frameworks were not designed to counter adversaries capable of generating synthetic identities and dynamically adapting attack strategies. This paper presents a theoretical analysis of AI-enabled identity threats and proposes a conceptual framework to classify and understand emerging identity exploitation techniques. The study synthesizes recent cybersecurity research and industry trends to identify structural gaps in current identity security models and outline foundational assumptions for future research.
Fields of Study & Subjects
Information and Cyber Security
Spam and Phishing Detection
User Authentication and Security Systems
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 28 January 2026
- Language
- EN