Metaheuristic Optimization Review MOR 3066-280X 10.54216/MOR https://www.americaspg.com/journals/show/4200 2024 2024 Intelligent Systems and Machine Learning Lab, Shenzhen 518000, China Al-Seyday. Al-Seyday.T. The emergence of artificial intelligence has transformed the landscape of digital security, communication, and media authenticity. Among its most consequential manifestations are Deepfakes, hyper-realistic synthetic media that undermine trust, destabilize communication ecosystems, and challenge legal and ethical frameworks. This study presents a comprehensive synthesis of methodological contributions across domains such as cybersecurity, communication networks, social media governance, digital forensics, and abuse detection. By organizing the literature into distinct categories, the research highlights how artificial intelligence operates as both the generator of risk and the foundation for its mitigation. Methodological trajectories include conceptual surveys of dual-use AI in cybersecurity, ensemble models for fraud detection, adaptive frameworks for phishing prevention, federated learning for privacy-preserving analytics, and the integration of AI with IoTenabled communication systems. Furthermore, interdisciplinary approaches extend the scope of detection and governance into educational, psychological, and social contexts, demonstrating that the challenge is not solely technical but systemic. The findings underscore recurring themes of hybridization, interpretability, resilience, and ethical responsibility, revealing that the future of AI-based defense mechanisms lies in their capacity to integrate technical rigor with human-centered and institutional perspectives. Ultimately, this review positions Deepfake detection and related AI applications within a wider constellation of methodological innovation, emphasizing that the problem of synthetic deception cannot be resolved through isolated technical solutions but requires coordinated, adaptive, and ethically grounded strategies capable of evolving alongside adversarial threats. 2026 2026 44 65 10.54216/MOR.050103 https://www.americaspg.com/articleinfo/41/show/4200