Disinformation Security at the Nexus of Cybersecurity and AI: Defending digital ecosystems against automated deception

Khan, Ummer Khan Asif Bangalore Ghouse (2025) Disinformation Security at the Nexus of Cybersecurity and AI: Defending digital ecosystems against automated deception. World Journal of Advanced Engineering Technology and Sciences, 15 (2). pp. 2618-2625. ISSN 2582-8266

As artificial intelligence (AI) continues to transform the digital landscape, it has also empowered new forms of disinformation that pose serious threats to cybersecurity. From AI-generated deepfakes to automated botnets spreading propaganda, the convergence of AI and disinformation has created a dynamic, high-stakes threat environment. This paper investigates the emerging field of disinformation security through the lens of cybersecurity and artificial intelligence, highlighting how adversaries exploit algorithmic vulnerabilities and information systems to conduct influence operations, disrupt trust, and manipulate public perception. The study explores current AI-driven tools used for detecting and neutralizing disinformation, including machine learning classifiers, natural language processing, and network analysis. It also addresses the limitations and risks of AI in this domain, such as adversarial attacks and algorithmic bias. By framing disinformation as both a cybersecurity and an AI governance challenge, this paper proposes a multidisciplinary defence strategy that combines technological innovation, threat intelligence, and ethical AI deployment to protect digital infrastructure and public discourse.