Intrusion Detection A Machine Learning Approach
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Author | : Jeffrey J P Tsai |
Publisher | : World Scientific |
Total Pages | : 185 |
Release | : 2011-01-03 |
Genre | : Computers |
ISBN | : 1908978260 |
Download Intrusion Detection: A Machine Learning Approach Book in PDF, Epub and Kindle
This important book introduces the concept of intrusion detection, discusses various approaches for intrusion detection systems (IDS), and presents the architecture and implementation of IDS. It emphasizes on the prediction and learning algorithms for intrusion detection and highlights techniques for intrusion detection of wired computer networks and wireless sensor networks. The performance comparison of various IDS via simulation will also be included.
Author | : Zhenwei Yu |
Publisher | : World Scientific |
Total Pages | : 185 |
Release | : 2011 |
Genre | : Computers |
ISBN | : 1848164475 |
Download Intrusion Detection Book in PDF, Epub and Kindle
Introduces the concept of intrusion detection, discusses various approaches for intrusion detection systems (IDS), and presents the architecture and implementation of IDS. This title also includes the performance comparison of various IDS via simulation.
Author | : Kwangjo Kim |
Publisher | : Springer |
Total Pages | : 79 |
Release | : 2018-10-02 |
Genre | : Computers |
ISBN | : 9789811314438 |
Download Network Intrusion Detection using Deep Learning Book in PDF, Epub and Kindle
This book presents recent advances in intrusion detection systems (IDSs) using state-of-the-art deep learning methods. It also provides a systematic overview of classical machine learning and the latest developments in deep learning. In particular, it discusses deep learning applications in IDSs in different classes: generative, discriminative, and adversarial networks. Moreover, it compares various deep learning-based IDSs based on benchmarking datasets. The book also proposes two novel feature learning models: deep feature extraction and selection (D-FES) and fully unsupervised IDS. Further challenges and research directions are presented at the end of the book. Offering a comprehensive overview of deep learning-based IDS, the book is a valuable reerence resource for undergraduate and graduate students, as well as researchers and practitioners interested in deep learning and intrusion detection. Further, the comparison of various deep-learning applications helps readers gain a basic understanding of machine learning, and inspires applications in IDS and other related areas in cybersecurity.
Author | : Hari Vasudevan |
Publisher | : Springer Nature |
Total Pages | : 686 |
Release | : 2020-05-06 |
Genre | : Technology & Engineering |
ISBN | : 9811532427 |
Download Advanced Computing Technologies and Applications Book in PDF, Epub and Kindle
This book features selected papers presented at the 2nd International Conference on Advanced Computing Technologies and Applications, held at SVKM’s Dwarkadas J. Sanghvi College of Engineering, Mumbai, India, from 28 to 29 February 2020. Covering recent advances in next-generation computing, the book focuses on recent developments in intelligent computing, such as linguistic computing, statistical computing, data computing and ambient applications.
Author | : Nandita Sengupta |
Publisher | : Springer Nature |
Total Pages | : 151 |
Release | : 2020-01-24 |
Genre | : Computers |
ISBN | : 9811527164 |
Download Intrusion Detection Book in PDF, Epub and Kindle
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.
Author | : Kwangjo Kim |
Publisher | : Springer |
Total Pages | : 79 |
Release | : 2018-09-25 |
Genre | : Computers |
ISBN | : 9811314446 |
Download Network Intrusion Detection using Deep Learning Book in PDF, Epub and Kindle
This book presents recent advances in intrusion detection systems (IDSs) using state-of-the-art deep learning methods. It also provides a systematic overview of classical machine learning and the latest developments in deep learning. In particular, it discusses deep learning applications in IDSs in different classes: generative, discriminative, and adversarial networks. Moreover, it compares various deep learning-based IDSs based on benchmarking datasets. The book also proposes two novel feature learning models: deep feature extraction and selection (D-FES) and fully unsupervised IDS. Further challenges and research directions are presented at the end of the book. Offering a comprehensive overview of deep learning-based IDS, the book is a valuable reerence resource for undergraduate and graduate students, as well as researchers and practitioners interested in deep learning and intrusion detection. Further, the comparison of various deep-learning applications helps readers gain a basic understanding of machine learning, and inspires applications in IDS and other related areas in cybersecurity.
Author | : IEEE Staff |
Publisher | : |
Total Pages | : |
Release | : 2019-06-12 |
Genre | : |
ISBN | : 9781728101682 |
Download 2019 3rd International Conference on Electronics, Communication and Aerospace Technology (ICECA) Book in PDF, Epub and Kindle
ICECA 2019 will provide an outstanding international forum for scientists from all over the world to share ideas and achievements in the theory and practice of all areas of aero space technologies Presentations should highlight inventive systems as a concept that combines theoretical research and applications in Electronics, Communication, Information and Aerospace technologies
Author | : Yihua Liao |
Publisher | : |
Total Pages | : 230 |
Release | : 2005 |
Genre | : |
ISBN | : |
Download Machine Learning in Intrusion Detection Book in PDF, Epub and Kindle
Detection of anomalies in data is one of the fundamental machine learning tasks. Anomaly detection provides the core technology for a broad spectrum of security-centric applications. In this dissertation, we examine various aspects of anomaly based intrusion detection in computer security. First, we present a new approach to learn program behavior for intrusion detection. Text categorization techniques are adopted to convert each process to a vector and calculate the similarity between two program activities. Then the k-nearest neighbor classifier is employed to classify program behavior as normal or intrusive. We demonstrate that our approach is able to effectively detect intrusive program behavior while a low false positive rate is achieved. Second, we describe an adaptive anomaly detection framework that is de- signed to handle concept drift and online learning for dynamic, changing environments. Through the use of unsupervised evolving connectionist systems, normal behavior changes are efficiently accommodated while anomalous activities can still be recognized. We demonstrate the performance of our adaptive anomaly detection systems and show that the false positive rate can be significantly reduced.
Author | : Kwangjo Kim |
Publisher | : |
Total Pages | : |
Release | : 2018 |
Genre | : Computer security |
ISBN | : 9789811314452 |
Download Network Intrusion Detection Using Deep Learning Book in PDF, Epub and Kindle
This book presents recent advances in intrusion detection systems (IDSs) using state-of-the-art deep learning methods. It also provides a systematic overview of classical machine learning and the latest developments in deep learning. In particular, it discusses deep learning applications in IDSs in different classes: generative, discriminative, and adversarial networks. Moreover, it compares various deep learning-based IDSs based on benchmarking datasets. The book also proposes two novel feature learning models: deep feature extraction and selection (D-FES) and fully unsupervised IDS. Further challenges and research directions are presented at the end of the book. Offering a comprehensive overview of deep learning-based IDS, the book is a valuable reerence resource for undergraduate and graduate students, as well as researchers and practitioners interested in deep learning and intrusion detection. Further, the comparison of various deep-learning applications helps readers gain a basic understanding of machine learning, and inspires applications in IDS and other related areas in cybersecurity.
Author | : Jordi Domingo-Pascual |
Publisher | : Springer Science & Business Media |
Total Pages | : 492 |
Release | : 2011-04-28 |
Genre | : Business & Economics |
ISBN | : 3642207561 |
Download NETWORKING 2011 Book in PDF, Epub and Kindle
The two-volume set LNCS 6640 and 6641 constitutes the refereed proceedings of the 10th International IFIP TC 6 Networking Conference held in Valencia, Spain, in May 2011. The 64 revised full papers presented were carefully reviewed and selected from a total of 294 submissions. The papers feature innovative research in the areas of applications and services, next generation Internet, wireless and sensor networks, and network science. The first volume includes 36 papers and is organized in topical sections on anomaly detection, content management, DTN and sensor networks, energy efficiency, mobility modeling, network science, network topology configuration, next generation Internet, and path diversity.