Intrusion Detection

CHF 201.20
Auf Lager
SKU
9QDNBVNGRCU
Stock 1 Verfügbar
Free Shipping Kostenloser Versand
Geliefert zwischen Mi., 29.10.2025 und Do., 30.10.2025

Details


Details dimension reduction techniques, which reduce the complexity of intrusion detection systems without sacrificing prediction accuracy Sheds new light on real-time design of adaptive intrusion detection systems Includes a special chapter on reinforcement learning used for intrusion detection systems and discretization techniques

Autorentext

Nandita Sengupta holds a Bachelor of Engineering degree from the Indian Institute of Engineering Science and Technology (IIEST), Shibpur, India (formerly known as Bengal Engineering College, Shibpur, Calcutta University). She completed a postgraduate management course in Information Technology at IMT, an M.Tech. (Information Technology) and Ph.D. in Engineering (Computer Science and Technology) at IIEST, Shibpur, India. She has worked in the field for 29 years, including 11 years in industry and 18 years teaching IT various subjects. She is currently an Associate Professor at the University College of Bahrain, Bahrain. Her areas of interest are analysis of algorithms, theory of computation, soft computing techniques, network computing and security.

Jaya Sil has been a Professor at the Department of Computer Science and Technology at the Indian Institute of Engineering Science and Technology, Shibpur, since 2003. She completed her B.E. in Electronics and Telecommunication Engineering at B.E. College, at Calcutta University, India, in 1984, and M.E. (Tele) at Jadavpur University, Kolkata, India, in 1986. She received her Ph.D. (Engg) degree in the field of artificial intelligence from Jadavpur University, Kolkata, in 1996, and started her teaching career in 1987 as a lecturer at the Department of Computer Science and Technology at B.E. College, Howrah. She worked as a Postdoctoral Fellow at Nanyang Technological University, Singapore, from 2002 to 2003. She undertook collaborative research in Husar at the Bioinformatics Lab, Heidelberg, Germany, and also visited Wroclaw University of Technology, Poland, in 2012. She was awarded an INSA Senior Scientist Fellowship. Prof. Sil has delivered tutorials and invited talks, and has also presented papers and chaired sessions at various international conferences in abroad and India. She has published more than 200 research papers (including conference papers) in the field of bioinformatics, machinelearning and image processing along with applications in a variety of engineering fields. She has published numerous books and several book chapters and acted as a reviewer for IEEE, Elsevier, and Springer Journals.

Inhalt

Chapter 1. Introduction.- Chapter 2. Discretization.- Chapter 3. Data Reduction.- Chapter 4. Q-Learning Classifiers.- Chapter 5. Hierarchical Q - Learning Classifier.- Chapter 6. Conclusions and Future Research. <p

Cart 30 Tage Rückgaberecht
Cart Garantie

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09789811527180
    • Anzahl Seiten 156
    • Lesemotiv Verstehen
    • Genre Allgemein & Lexika
    • Auflage 1st edition 2020
    • Herausgeber Springer Nature Singapore
    • Gewicht 248g
    • Untertitel A Data Mining Approach
    • Größe H235mm x B155mm x T9mm
    • Jahr 2021
    • EAN 9789811527180
    • Format Kartonierter Einband
    • ISBN 9811527180
    • Veröffentlichung 25.01.2021
    • Titel Intrusion Detection
    • Autor Jaya Sil , Nandita Sengupta
    • Sprache Englisch

Bewertungen

Schreiben Sie eine Bewertung
Nur registrierte Benutzer können Bewertungen schreiben. Bitte loggen Sie sich ein oder erstellen Sie ein Konto.