ABSTRACT: 

Despite the numerous benefits offered by Artificial Intelligence (AI) applications, recent developments have also revealed their misuse as a significant enabler of various forms of cybercrime, particularly in the creation of so-called deep fake content. Deep fake technology refers to advanced AI-driven techniques capable of generating highly realistic static images, videos, and audio recordings that closely resemble authentic human appearance and behavior. In light of the rapid and remarkable advancements in artificial intelligence, producing convincingly forged visual and auditory content has become increasingly accessible and sophisticated. This research addresses the challenges posed by artificial intelligence and deep fake technologies, focusing on the algorithms and techniques used to generate manipulated videos and audio recordings that have demonstrated a substantial capacity to influence public opinion, decision-making processes, and public policies. Such fabricated content is often exploited for malicious purposes, including election manipulation, financial fraud, and the defamation of public figures.  The researchers adopted a descriptive methodology to systematically explain the nature and implications of deep fake technologies, alongside an analytical approach to examine existing tools, techniques, and applications used to detect forgery and mitigate its associated risks. Based on this methodological framework, the study presents practical findings and proposes a set of recommendations aimed at addressing deep fake attacks and digital forgery crimes.

Keywords:  Artificial Intelligence Applications, Cybercrimes, Deep Fake, Cybercrime, Information Technology.