Machine Learning And Cryptographic Solutions For Data Protection And Network Security

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Machine Learning and Cryptographic Solutions for Data Protection and Network Security

Machine Learning and Cryptographic Solutions for Data Protection and Network Security
Author :
Publisher : IGI Global
Total Pages : 557
Release :
ISBN-10 : 9798369341605
ISBN-13 :
Rating : 4/5 ( Downloads)

Book Synopsis Machine Learning and Cryptographic Solutions for Data Protection and Network Security by : Ruth, J. Anitha

Download or read book Machine Learning and Cryptographic Solutions for Data Protection and Network Security written by Ruth, J. Anitha and published by IGI Global. This book was released on 2024-05-31 with total page 557 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the relentless battle against escalating cyber threats, data security faces a critical challenge – the need for innovative solutions to fortify encryption and decryption processes. The increasing frequency and complexity of cyber-attacks demand a dynamic approach, and this is where the intersection of cryptography and machine learning emerges as a powerful ally. As hackers become more adept at exploiting vulnerabilities, the book stands as a beacon of insight, addressing the urgent need to leverage machine learning techniques in cryptography. Machine Learning and Cryptographic Solutions for Data Protection and Network Security unveil the intricate relationship between data security and machine learning and provide a roadmap for implementing these cutting-edge techniques in the field. The book equips specialists, academics, and students in cryptography, machine learning, and network security with the tools to enhance encryption and decryption procedures by offering theoretical frameworks and the latest empirical research findings. Its pages unfold a narrative of collaboration and cross-pollination of ideas, showcasing how machine learning can be harnessed to sift through vast datasets, identify network weak points, and predict future cyber threats.


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