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GAN-Based Privacy Protection for Public Data Sharing in Wireless Sensor Networks
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Author(s): Swaminathan Kalyanaraman (University College of Engineering, Anna University, Pattukkottai, India), Sivaram Ponnusamy (Sandip University, India), S. Saju (MIET Engineering College, India), R. Vijay (Saranathan College of Engineering, India)and R. Karthikeyan (University College of Engineering, Pattukkottai, India)
Copyright: 2024
Pages: 15
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.ch018
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Abstract
In this study, the authors introduce “SecureNetGAN,” a novel system designed to protect wireless sensor networks (WSNs) from cyber threats through the use of generative adversarial networks (GANs). WSNs are crucial in various applications, from environmental monitoring to securing borders, but they're often targeted by hackers due to their critical nature. The challenge is that traditional security systems can't always keep up with the constantly changing tactics of these attackers. That's where SecureNetGAN comes in. SecureNetGAN leverages the power of GANs, a type of artificial intelligence where two parts of the system, the generator and the discriminator, work against each other. The generator learns to create data that looks like network attacks, while the discriminator gets better at telling real attacks from fake ones.
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