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Author: Publisher: YouGuide Ltd ISBN: 1836797915 Category : Languages : en Pages : 271
Book Description
Designed for professionals, students, and enthusiasts alike, our comprehensive books empower you to stay ahead in a rapidly evolving digital world. * Expert Insights: Our books provide deep, actionable insights that bridge the gap between theory and practical application. * Up-to-Date Content: Stay current with the latest advancements, trends, and best practices in IT, Al, Cybersecurity, Business, Economics and Science. Each guide is regularly updated to reflect the newest developments and challenges. * Comprehensive Coverage: Whether you're a beginner or an advanced learner, Cybellium books cover a wide range of topics, from foundational principles to specialized knowledge, tailored to your level of expertise. Become part of a global network of learners and professionals who trust Cybellium to guide their educational journey. www.cybellium.com
Author: Publisher: YouGuide Ltd ISBN: 1836797915 Category : Languages : en Pages : 271
Book Description
Designed for professionals, students, and enthusiasts alike, our comprehensive books empower you to stay ahead in a rapidly evolving digital world. * Expert Insights: Our books provide deep, actionable insights that bridge the gap between theory and practical application. * Up-to-Date Content: Stay current with the latest advancements, trends, and best practices in IT, Al, Cybersecurity, Business, Economics and Science. Each guide is regularly updated to reflect the newest developments and challenges. * Comprehensive Coverage: Whether you're a beginner or an advanced learner, Cybellium books cover a wide range of topics, from foundational principles to specialized knowledge, tailored to your level of expertise. Become part of a global network of learners and professionals who trust Cybellium to guide their educational journey. www.cybellium.com
Author: Carol Fung Publisher: CRC Press ISBN: 146656413X Category : Computers Languages : en Pages : 261
Book Description
The rapidly increasing sophistication of cyber intrusions makes them nearly impossible to detect without the use of a collaborative intrusion detection network (IDN). Using overlay networks that allow an intrusion detection system (IDS) to exchange information, IDNs can dramatically improve your overall intrusion detection accuracy.Intrusion Detect
Author: Syngress Publisher: Elsevier ISBN: 0080481000 Category : Computers Languages : en Pages : 559
Book Description
The incredible low maintenance costs of Snort combined with its powerful security features make it one of the fastest growing IDSs within corporate IT departments. Snort 2.0 Intrusion Detection is written by a member of Snort.org. The book provides a valuable insight to the code base of Snort and in-depth tutorials of complex installation, configuration, and troubleshooting scenarios. The primary reader will be an individual who has a working knowledge of the TCP/IP protocol, expertise in some arena of IT infrastructure, and is inquisitive about what has been attacking their IT network perimeter every 15 seconds. - The most up-to-date and comprehensive coverage for Snort 2.0! - Expert Advice from the Development Team and Step-by-Step Instructions for Installing, Configuring, and Troubleshooting the Snort 2.0 Intrusion Detection System.
Author: Giovanni Vigna Publisher: Springer Science & Business Media ISBN: 3540408789 Category : Business & Economics Languages : en Pages : 248
Book Description
This book constitutes the refereed proceedings of the 6th International Symposium on Recent Advances in Intrusion Detection, RAID 2003, held in Pittsburgh, PA, USA in September 2003. The 13 revised full papers presented were carefully reviewed and selected from 44 submissions. The papers are organized in topical sections on network infrastructure, anomaly detection, modeling and specification, and IDS sensors.
Author: Yihua Liao Publisher: ISBN: Category : Languages : en Pages : 230
Book Description
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: Mayank Swarnkar Publisher: CRC Press ISBN: 1000967557 Category : Computers Languages : en Pages : 218
Book Description
This book is associated with the cybersecurity issues and provides a wide view of the novel cyber attacks and the defense mechanisms, especially AI-based Intrusion Detection Systems (IDS). Features: A systematic overview of the state-of-the-art IDS Proper explanation of novel cyber attacks which are much different from classical cyber attacks Proper and in-depth discussion of AI in the field of cybersecurity Introduction to design and architecture of novel AI-based IDS with a trans- parent view of real-time implementations Covers a wide variety of AI-based cyber defense mechanisms, especially in the field of network-based attacks, IoT-based attacks, multimedia attacks, and blockchain attacks. This book serves as a reference book for scientific investigators who need to analyze IDS, as well as researchers developing methodologies in this field. It may also be used as a textbook for a graduate-level course on information security.
Author: Ali A. Ghorbani Publisher: Springer Science & Business Media ISBN: 0387887717 Category : Computers Languages : en Pages : 224
Book Description
Network Intrusion Detection and Prevention: Concepts and Techniques provides detailed and concise information on different types of attacks, theoretical foundation of attack detection approaches, implementation, data collection, evaluation, and intrusion response. Additionally, it provides an overview of some of the commercially/publicly available intrusion detection and response systems. On the topic of intrusion detection system it is impossible to include everything there is to say on all subjects. However, we have tried to cover the most important and common ones. Network Intrusion Detection and Prevention: Concepts and Techniques is designed for researchers and practitioners in industry. This book is suitable for advanced-level students in computer science as a reference book as well.
Author: Kwangjo Kim Publisher: Springer ISBN: 9811314446 Category : Computers Languages : en Pages : 92
Book Description
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.
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Author: Carol Fung
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Author: Syngress
Author: Giovanni Vigna
Author: Yihua Liao
Author: Mayank Swarnkar
Author: Ali A. Ghorbani
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Author: Kwangjo Kim