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.
Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
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.
Shanmugapriya D. is the Assistant Professor and Head, Department of Information Technology, Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, INDIA since 2001. She has more than 20 years of teaching experience and 10 years of research experience. Her areas of interest include, Cyber Security, Biometric security and Image Processing. She has executed funded projects sponsored by DRDO, DST and UGC. Currently Supervising 4 scholars at Ph.D level, she has more than 25 publications in peer-reviewed journals and Prestigious conferences . She is a Reviewer for many Conferences and Journals. She is a content Writer of Virtual Currency, Block Chain Technology and Basics of Security Auditing for SWAYAM-MOOC course on Cyber Security.
„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.
EUR 5,71 für den Versand von Vereinigtes Königreich nach Deutschland
Versandziele, Kosten & DauerAnbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
Zustand: New. In. Bestandsnummer des Verkäufers ria9781522596110_new
Anzahl: Mehr als 20 verfügbar
Anbieter: PBShop.store UK, Fairford, GLOS, Vereinigtes Königreich
HRD. Zustand: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Bestandsnummer des Verkäufers L1-9781522596110
Anzahl: Mehr als 20 verfügbar
Anbieter: moluna, Greven, Deutschland
Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides vital research on the application of machine learning techniques for network security research. Highlighting topics such as web security, malware detection, and secure information sharing, this publication explores recent research findings in the a. Bestandsnummer des Verkäufers 448011803
Anzahl: Mehr als 20 verfügbar
Anbieter: PBShop.store US, Wood Dale, IL, USA
HRD. Zustand: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Bestandsnummer des Verkäufers L1-9781522596110
Anzahl: Mehr als 20 verfügbar
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch. Zustand: 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. Bestandsnummer des Verkäufers 9781522596110
Anzahl: 1 verfügbar