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Innovative Approaches to Public Safety: Implementing Generative Adversarial Networks (GANs) for Cyber Security Enhancement in Public Spaces
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Author(s): Anita Chaudhary (Eternal University, India)
Copyright: 2024
Pages: 9
Source title:
Enhancing Security in Public Spaces Through Generative Adversarial Networks (GANs)
Source Author(s)/Editor(s): Sivaram Ponnusamy (Sandip University, Nashik, India), Jilali Antari (Ibn Zohr Agadir University, Morocco), Pawan R. Bhaladhare (Sandip University, Nashik, India), Amol D. Potgantwar (Sandip University, Nashik, India)and Swaminathan Kalyanaraman (Anna University, Trichy, India)
DOI: 10.4018/979-8-3693-3597-0.ch020
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Abstract
This book chapter examines cutting-edge tactics to improve public safety by using Generative Adversarial Networks (GANs) to improve cyber security in public areas. Conventional security solutions frequently fail to provide adequate protection against cyber-attacks in public settings in an era characterized by growing digital interconnection and changing security risks. Using GANs, a state-of-the-art machine learning method, offers a viable way to strengthen cyber security measures and reduce possible threats. The chapter explores the theoretical underpinnings of GANs and how they are used to identify and neutralize cyber threats in public areas. Through the utilisation of GANs to produce artificial intelligence-generated data and replicate cyber-attack scenarios, entities can anticipate weaknesses and develop resilient protection strategies in advance.
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