Rotimi-Williams BELLO
Biography
Dr. Rotimi-Williams Bello is a Postdoctoral Research Fellow in the Department of Computer Systems Engineering at the Tshwane University of Technology, South Africa. He holds a PhD in Vision and Image Processing from Universiti Sains Malaysia, along with advanced degrees in Computer Science from Nigerian institutions. With over a decade of teaching and research experience across Africa and Asia, his work focuses on artificial intelligence, computer vision, image processing, and smart agriculture. Dr. Bello is an active member of several professional bodies, including the Computer Professionals Council of Nigeria and the International Association of Engineers. His research contributions span AI applications in cybersecurity, ethical implications of automated systems, and the advancement of intelligent technologies for societal benefit.
Research Interest
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AREAS OF SPECIALIZATION/RESEARCH INTEREST
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Computer Vision
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Image Processing
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Smart Agriculture
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Abstract
AI in Cybersecurity: Navigating the Dual-Edged Sword
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Threat detection and response mechanisms in organizations have been revolutionized by the integration of Artificial Intelligence (AI) into cybersecurity frameworks. The ability to predict and identify potential breaches and anomalies and automate responses has been enhanced by machine learning algorithms, thereby fortifying digital infrastructures against evolving threats. However, new challenges are introduced by this advancement, as adversaries exploit AI to serve their negative interest by developing sophisticated attack vectors, including adaptive malware and deepfakes. This presentation delves into the dual nature of AI in cybersecurity, analyzing its role as both a defender and a potential threat. Likewise, it delves into current applications such as threat intelligence, behavioral analytics, and anomaly detection. It also examines and addresses the emerging challenges, including data privacy concerns, adversarial AI, and the ethical implications of automated decision-making in security contexts. This presentation discusses the emergence of adversarial AI, and high spots the importance of Explainable AI (XAI) in maintaining transparency and trust in automated security systems. By this presentation, not only will the attendees gain insights into developing robust AI-driven security strategies that anticipate and mitigate the risks posed by malicious AI applications but also gain insights into the latest research findings, case studies of AI-driven cybersecurity implementations, and best practices for integrating AI technologies into existing security infrastructures.
Join us to navigate the complexities of AI in cybersecurity and to understand how to leverage its capabilities responsibly to protect against the very threats it may inadvertently introduce.
Keywords: Artificial Intelligence, Cybersecurity, Explainable AI, Machine Learning, Threats
