Toyota Financial Services, Dallas TX, USA.
Research Article
World Journal of Advanced Research and Reviews, 2024, 24(03), 3639-3647
Received on 14 November 2024; revised on 22 December 2024; accepted on 28 December 2024
Deepfake technologies - encompassing generative adversarial networks, diffusion-based synthesis, and transformer-driven voice cloning - have evolved from entertainment novelties into precision socio-technical weapons targeting organizational trust infrastructures. Existing countermeasures focus narrowly on artifact-level detection accuracy, failing to model systemic vulnerabilities within enterprise decision chains, financial authorization workflows, and executive identity trust graphs. This paper introduces the Cognitive Authenticity Assurance Architecture, a novel multi-layered defense framework integrating Cognitive Attack Surface Modeling, Trust Graph Disruption Index analytics, Adversarial Co-Evolution Defense Engine, Authenticity-by-Design Protocol with cryptographic watermarking, and Zero-Trust Media Verification Architecture. The framework reconceptualizes deepfake threats as cognitive supply-chain attacks on organizational trust ecosystems rather than isolated media forgeries. A graph-theoretic Trust Graph Disruption Index metric quantifies synthetic identity propagation risk across enterprise communication networks. Simulation results demonstrate a 47% reduction in successful executive impersonation attacks, 39% improvement in synthetic media identification speed within financial workflows, and 52% reduction in decision-layer compromise probability. This architecture advances deepfake mitigation beyond detection into organizational trust engineering, establishing a new operational and theoretical paradigm for enterprise cognitive resilience.
Deepfake Detection; Cognitive Attack Surface; Trust Graph Disruption; Adversarial Co-Evolution; Zero-Trust Media Verification; Organizational Resilience; Synthetic Identity
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Sivaramakrishnan Narayanan. Authenticity assurance architecture: A Multi-layer organizational deepfake threat taxonomy and control framework. World Journal of Advanced Research and Reviews, 2024, 24(3), 3639-3647. Article DOI: https://doi.org/10.30574/wjarr.2024.24.3.3945