Franklin

Intrusion Detection [electronic resource] : A Data Mining Approach / by Nandita Sengupta, Jaya Sil.

Author/Creator:
Sengupta, Nandita author., Author,
Publication:
Singapore : Springer Singapore : Imprint: Springer, 2020.
Format/Description:
Book
1 online resource (XX, 136 pages)
Edition:
1st ed. 2020.
Series:
Computer Science (Springer-11645)
Cognitive Intelligence and Robotics, 2520-1956
Cognitive Intelligence and Robotics, 2520-1956
Contained In:
Springer eBooks
Status/Location:
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Details

Subjects:
Computer networks.
Computer security.
Data encryption (Computer science).
Local subjects:
Computer Communication Networks. (search)
Systems and Data Security. (search)
Cryptology. (search)
System Details:
text file PDF
Summary:
This book presents state-of-the-art research on intrusion detection using reinforcement learning, fuzzy and rough set theories, and genetic algorithm. Reinforcement learning is employed to incrementally learn the computer network behavior, while rough and fuzzy sets are utilized to handle the uncertainty involved in the detection of traffic anomaly to secure data resources from possible attack. Genetic algorithms make it possible to optimally select the network traffic parameters to reduce the risk of network intrusion. The book is unique in terms of its content, organization, and writing style. Primarily intended for graduate electrical and computer engineering students, it is also useful for doctoral students pursuing research in intrusion detection and practitioners interested in network security and administration. The book covers a wide range of applications, from general computer security to server, network, and cloud security.
Contents:
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.
Contributor:
Sil, Jaya. author., Author,
SpringerLink (Online service)
Other format:
Printed edition:
Printed edition:
Printed edition:
ISBN:
978-981-15-2716-6
9789811527166
9789811527159 (Printed edition)
9789811527173 (Printed edition)
9789811527180 (Printed edition)
Publisher Number:
10.1007/978-981-15-2716-6 doi
Access Restriction:
Restricted for use by site license.