Speaker

Debashis Das

Debashis Das

Postdoctoral Fellow, Department of CS and DS, Meharry Medical College.

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Debashis Das is currently working as a post doctoral fellow in the Department of Computer Science and Data Science at Meharry Medical College, TN, USA. He was former Assistant Professor in the Department of Computer Science and Engineering at Narula Institute of Technology, WB, India in 2023. He received his Ph.D. from the University of Kalyani, India, in 2023. He completed his M.Tech and B.Tech in Computer Science and Engineering from MAKAUT in 2018 and 2015, respectively. He has more than 30+ publications in various peer-reviewed reputed journals and conferences. He served as a reviewer for IEEE JBHI, FGCS, and other peer-reviewed journals. His research interests include Healthcare Management, Cybersecurity, Intelligent Transportation Systems (ITS), Blockchain Technology, and Artificial Intelligence (ML, FL). He is a member of IEEE.

The Role of Artificial Intelligence in Detecting and Responding to Public Sector Cyber Threats

Robust cybersecurity solutions in the public sector actively enhance data protection, safeguard critical infrastructure, and foster public trust in government institutions. However, cybersecurity faces a multitude of challenges, including the constant evolution of sophisticated threats, vulnerabilities in software and systems, and the growing complexity of digital landscapes. Artificial Intelligence (AI) emerges as a potent solution by enabling proactive threat detection through real-time analysis of vast datasets, swift identification of anomalies, and the development of adaptive response mechanisms. Therefore, this research employs a mixed-methods approach to investigate the role of AI in enhancing cybersecurity within the public sector including detection and response mechanisms. In this implementation process, we integrate qualitative methods through an in-depth examination of case studies and success stories. These real-world scenarios showcase instances where AI played a pivotal role in preventing and mitigating cyber threats. And quantitative analysis involves AI algorithms scrutinizing extensive datasets to identify subtle indicators of cyber threats. We develop AI algorithms to sift through vast datasets, monitoring and identifying subtle indicators of potential threats, including malware, phishing attacks, and advanced persistent threats. This mixed-methods approach serves as a robust strategy to ensure the reliability and validity of the research findings. The findings underscore the efficacy of AI as a sentinel in the public sector's cybersecurity landscape and significantly enhances threat detection, minimizes potential damage and defense cyber-threats. This research method not only instills confidence in the cybersecurity measures undertaken by government entities but also serves as a model for other organizations seeking effective strategies. Overall, the method contributes to the overall resilience and trustworthiness of government institutions in the digital age.

Debashis Das

Postdoctoral Fellow, Department of CS and DS, Meharry Medical College.

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