Detection and Analysis of AI-Generated Malicious Content

Abstract

Generative artificial intelligence (AI) technologies are advancing rapidly and, for the first time, pose unprecedented cybersecurity challenges with sophisticated AI-generated malicious content. While these technologies are amazing, they create huge security risks when weaponized to perform cyber attacks. To bridge the critical gap of detecting and analyzing AI-generated malicious content, this research develops comprehensive detection and forensic analysis frameworks. The goal of the study is to develop techniques for identifying, profiling, and analyzing AI-generated threats using advanced pattern recognition and machine learning techniques. The research methodology includes the development of statistical models to distinguish between human and AI-generated malicious content, the implementation of real-time neural network-based detection systems, and the creation of forensic analysis protocols.