Intrusion Detection A Data Mining Approach
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
- PDF / 5,269,604 Bytes
- 151 Pages / 453.544 x 683.151 pts Page_size
- 107 Downloads / 243 Views
Nandita Sengupta Jaya Sil
Intrusion Detection A Data Mining Approach
Cognitive Intelligence and Robotics Series Editors Amit Konar, Department of Electronics and Telecommunication Engineering, Jadavpur University, Kolkata, India Witold Pedrycz, Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada
Cognitive Intelligence refers to the natural intelligence of humans and animals, it is considered that the brain performs intelligent activities. While establishing a hard boundary that distinguishes intelligent activities from others remains controversial, most common behaviors and activities of living organisms that cannot be fully synthesized using artificial means are regarded as intelligent. Thus the acts of sensing and perception, understanding the environment, and voluntary control of muscles, which can be performed by lower-level mammals, are indeed intelligent. Besides the above, advanced mammals can perform more sophisticated cognitive tasks, including logical reasoning, learning, recognition, and complex planning and coordination, none of which can yet be realized artificially to the level of a baby, and thus are regarded as cognitively intelligent. This book series covers two important aspects of brain science. First, it attempts to uncover the mystery behind the biological basis of cognition, with a special emphasis on the decoding of stimulated brain signals or images. Topics in this area include the neural basis of sensory perception, motor control, sensory-motor coordination, and understanding the biological basis of higher-level cognition, including memory, learning, reasoning, and complex planning. The second objective of the series is to publish consolidated research on brain-inspired models of learning, perception, memory, and coordination, including results that can be realized on robots, enabling them to mimic the cognitive activities performed by living creatures. These brain-inspired models of machine intelligence complement the behavioral counterparts studied in traditional artificial intelligence. The series publishes textbooks, monographs, and contributed volumes.
More information about this series at http://www.springer.com/series/15488
Nandita Sengupta Jaya Sil •
Intrusion Detection A Data Mining Approach
123
Nandita Sengupta Department of Information Technology University College of Bahrain Manama, Bahrain
Jaya Sil Department of Computer Science and Technology Indian Institute of Engineering Science and Technology (IIEST), Shibpur Howrah, West Bengal, India
ISSN 2520-1956 ISSN 2520-1964 (electronic) Cognitive Intelligence and Robotics ISBN 978-981-15-2715-9 ISBN 978-981-15-2716-6 (eBook) https://doi.org/10.1007/978-981-15-2716-6 © Springer Nature Singapore Pte Ltd. 2020 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other
Data Loading...
