• Tim Abdiukov

This article explores the growing importance of cognitive security in industry and business, particularly as deepfakes and generative AI become increasingly hazardous. It describes a situation in which advanced synthetic media and AI-produced content are being used to target the minds of decision-makers by exploiting their psychological and contextual susceptibilities. The main areas discussed are the Deepfake and Generative AI threats, what constitutes misuse, and include examples of misuse, such as phishing and information poisoning. Additionally, the discussion explores how these misuses can be countered with the help of cognitive security systems and their ability to detect anomalies. The paper highlights cutting-edge mitigation solutions, including multimodal detection, neuro-inspired frameworks, and collaborative defense solutions, while also addressing technical, ethical, and privacy constraints. Through the integration of behavioral intelligence with real-time analytics and continuous learning, the paper suggests a multidimensional defense posture that can be sustained in the changing AI-driven hazards of a dynamic enterprise scenario.

Cognitive security, generative AI, deepfakes, anomaly detection, smishing, AbuseGPT, professional networks, neuro-inspired detection, behavioral analytics, adaptive security.

"Cognitive Security in Professional Networks: Mitigating Deepfake and Generative AI Threats through Neuro-Inspired Anomaly Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 8, page no.f543-f555, August-2024, Available :http://www.jetir.org/papers/JETIR2408764.pdf

"Cognitive Security in Professional Networks: Mitigating Deepfake and Generative AI Threats through Neuro-Inspired Anomaly Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 8, page no. ppf543-f555, August-2024, Available at : http://www.jetir.org/papers/JETIR2408764.pdf