The Evolution of Deepfake Threats in Cybersecurity: A Systematic Literature Review on AI and Blockchain-Based Defense Mechanisms
Keywords:
Cyber Attack, Cyber SecurityAbstract
Deepfake technology, powered by advanced artificial intelligence (AI), has introduced new and highly sophisticated threats in the cybersecurity domain. These synthetic media, generated primarily through deep learning models such as Generative Adversarial Networks (GANs), are being utilized in a range of malicious activities including misinformation, identity theft, voice phishing (vishing), and corporate fraud. This Systematic Literature Review (SLR) analyzes four recent scientific studies published between 2021 and 2024 that propose various detection and prevention mechanisms for deepfakes. Special focus is given to AI-based detection techniques and blockchain-integrated verification systems. The review highlights decentralized defense frameworks, federated learning approaches, and challenges in achieving real-time detection. This paper contributes to the growing body of knowledge by outlining technological trends, identifying current gaps, and proposing future directions in deepfake defense within cybersecurity.
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