AI Cybersecurity Identity Threats in 2026: A Theoretical Analysis

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Authors: Saksham Shekher
Cited by: 0

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