As the advancement of technology continues, cyber security continues to play a significant role in today's world. With society becoming more dependent on the internet, new opportunities for virtual attacks can lead to the exposure of critical information. Machine and deep learning techniques to prevent this exposure of information are being applied to address mounting concerns in computer security. The Handbook of Research on Machine and Deep Learning Applications for Cyber Security is a pivotal reference source that provides vital research on the application of machine learning techniques for network security research. While highlighting topics such as web security, malware detection, and secure information sharing, this publication explores recent research findings in the area of electronic security as well as challenges and countermeasures in cyber security research. It is ideally designed for software engineers, IT specialists, cybersecurity analysts, industrial experts, academicians, researchers, and post-graduate students.
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Padmavathi Ganapathi is Professor and Head, Department of Computer Science. She has a total of 27 years teaching experience and 15 years research experience. Professor Ganapathi has more than 200 Publications and is a life member of: CSI, ISTE, AACE, and ISCA.
D. Shanmugapriya received a B.Sc degree in Computer Science and Computer Applications (1999), a M.Sc degree in Computer Science (2001), a Ph.D degree in Computer Science (2013), from Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, Tamil Nadu, India, and a M.Phil Degree in Computer Science (2003) from Manonmanium Sundaranar University, Tamil Nadu. She is currently the Head and an Assistant professor in the Department of Information Technology at Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, Tamil Nadu, India, with 19 years of teaching and Research experience. She has more than 25 research papers in reputed journals and conference proceedings. She was the co-principal Investigator for the projects sanctioned by DRDO and UGC. Her research interests include Cyber Security, Biometrics and Image Processing.
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Buch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - As the advancement of technology continues, cyber security continues to play a significant role in today's world. With society becoming more dependent on the internet, new opportunities for virtual attacks can lead to the exposure of critical information. Machine and deep learning techniques to prevent this exposure of information are being applied to address mounting concerns in computer security. The Handbook of Research on Machine and Deep Learning Applications for Cyber Security is a pivotal reference source that provides vital research on the application of machine learning techniques for network security research. While highlighting topics such as web security, malware detection, and secure information sharing, this publication explores recent research findings in the area of electronic security as well as challenges and countermeasures in cyber security research. It is ideally designed for software engineers, IT specialists, cybersecurity analysts, industrial experts, academicians, researchers, and post-graduate students. Nº de ref. del artículo: 9781522596110
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