Cybersecurity Addressing Multifaceted AI and Deepfake Threats with a Multidisciplinary Strategy to Mitigate Risks

This study examines the cybersecurity implications stemming from the proliferation of AI-powered deepfake technology. It synthesizes evidence from documented case studies, evaluates the efficacy of contemporary detection methodologies—such as machine learning algorithms, blockchain-based provenance systems, and digital watermarking—and investigates the broader societal, legal, and ethical ramifications of synthetic media misuse. Through a mixed-methods approach incorporating systematic literature review and qualitative expert interviews, the analysis identifies critical vulnerabilities in existing legal structures and public preparedness. The paper subsequently proposes targeted recommendations for legislative modernization and enhanced digital literacy initiatives. It concludes that addressing the multifaceted deepfake threat necessitates a coordinated, multidisciplinary strategy to mitigate risks, uphold digital trust, and advance responsible AI governance.