Network Intrusion Detection using Deep Learning PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Network Intrusion Detection using Deep Learning PDF full book. Access full book title Network Intrusion Detection using Deep Learning by Kwangjo Kim. Download full books in PDF and EPUB format.
Author: Kwangjo Kim
Publisher: Springer
ISBN: 9789811314438
Category : Computers
Languages : en
Pages : 79
Get Book Here
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.
Author: Kwangjo Kim
Publisher: Springer
ISBN: 9789811314438
Category : Computers
Languages : en
Pages : 79
Get Book Here
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.
Author: Dhruba Kumar Bhattacharyya
Publisher: CRC Press
ISBN: 146658209X
Category : Computers
Languages : en
Pages : 364
Get Book Here
Book Description
With the rapid rise in the ubiquity and sophistication of Internet technology and the accompanying growth in the number of network attacks, network intrusion detection has become increasingly important. Anomaly-based network intrusion detection refers to finding exceptional or nonconforming patterns in network traffic data compared to normal behavi
Author: Dong Yu
Publisher: Springer
ISBN: 1447157796
Category : Technology & Engineering
Languages : en
Pages : 329
Get Book Here
Book Description
This book provides a comprehensive overview of the recent advancement in the field of automatic speech recognition with a focus on deep learning models including deep neural networks and many of their variants. This is the first automatic speech recognition book dedicated to the deep learning approach. In addition to the rigorous mathematical treatment of the subject, the book also presents insights and theoretical foundation of a series of highly successful deep learning models.
Author: IEEE Staff
Publisher:
ISBN: 9781665401197
Category :
Languages : en
Pages :
Get Book Here
Book Description
The 4th International Conference on Smart Systems and Inventive Technology (ICSSIT 2022) is being organized by Francis Xavier Engineering College, Tirunelveli, India during 20 22, January 2022 ICSSIT 2022 will provide an outstanding international forum for sharing knowledge and results in all fields of science, engineering and Technology ICSSIT provides quality key experts who provide an opportunity in bringing up innovative ideas Recent updates in the field of technology will be a platform for the upcoming researchers The conference will be Complete, Concise, Clear and Cohesive in terms of research related to Smart Systems and Technology
Author: Kwangjo Kim
Publisher: Springer
ISBN: 9811314446
Category : Computers
Languages : en
Pages : 92
Get Book Here
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.
Author: Rajdeep Chakraborty
Publisher: John Wiley & Sons
ISBN: 1119764092
Category : Computers
Languages : en
Pages : 484
Get Book Here
Book Description
MACHINE LEARNING TECHNIQUES AND ANALYTICS FOR CLOUD SECURITY This book covers new methods, surveys, case studies, and policy with almost all machine learning techniques and analytics for cloud security solutions The aim of Machine Learning Techniques and Analytics for Cloud Security is to integrate machine learning approaches to meet various analytical issues in cloud security. Cloud security with ML has long-standing challenges that require methodological and theoretical handling. The conventional cryptography approach is less applied in resource-constrained devices. To solve these issues, the machine learning approach may be effectively used in providing security to the vast growing cloud environment. Machine learning algorithms can also be used to meet various cloud security issues, such as effective intrusion detection systems, zero-knowledge authentication systems, measures for passive attacks, protocols design, privacy system designs, applications, and many more. The book also contains case studies/projects outlining how to implement various security features using machine learning algorithms and analytics on existing cloud-based products in public, private and hybrid cloud respectively. Audience Research scholars and industry engineers in computer sciences, electrical and electronics engineering, machine learning, computer security, information technology, and cryptography.
Author: Mamoun Alazab
Publisher: Springer
ISBN: 3030130576
Category : Computers
Languages : en
Pages : 260
Get Book Here
Book Description
Cybercrime remains a growing challenge in terms of security and privacy practices. Working together, deep learning and cyber security experts have recently made significant advances in the fields of intrusion detection, malicious code analysis and forensic identification. This book addresses questions of how deep learning methods can be used to advance cyber security objectives, including detection, modeling, monitoring and analysis of as well as defense against various threats to sensitive data and security systems. Filling an important gap between deep learning and cyber security communities, it discusses topics covering a wide range of modern and practical deep learning techniques, frameworks and development tools to enable readers to engage with the cutting-edge research across various aspects of cyber security. The book focuses on mature and proven techniques, and provides ample examples to help readers grasp the key points.
Author: Kuan-Ching Li
Publisher: CRC Press
ISBN: 1000326136
Category : Computers
Languages : en
Pages : 291
Get Book Here
Book Description
Security, privacy, and trust in the Internet of Things (IoT) and CPS (Cyber-Physical Systems) are different from conventional security as concerns revolve around the collection and aggregation of data or transmission of data over the network. Analysis of cyber-attack vectors and the provision of appropriate mitigation techniques are essential research areas for these systems. Adoption of best practices and maintaining a balance between ease of use and security are, again, crucial for the effective performance of these systems. Recent Advances in Security, Privacy and Trust for Internet of Things (IoT) and Cyber-Physical Systems (CPS) discusses and presents techniques and methodologies, as well as a wide range of examples and illustrations, to effectively show the principles, algorithms, challenges, and applications of security, privacy, and trust for IoT and CPS. Book features: Introduces new directions for research, development, and engineering security, privacy, and trust of IoT and CPS Includes a wealth of examples and illustrations to effectively demonstrate the principles, algorithms, challenges, and applications Covers most of the important security aspects and current trends not present in other reference books This book will also serve as an excellent reference in security, privacy, and trust of IoT and CPS for professionals in this fast-evolving and critical field. The chapters present high-quality contributions from researchers, academics, and practitioners from various national and international organizations and universities.
Author: Ganapathi, Padmavathi
Publisher: IGI Global
ISBN: 1522596135
Category : Computers
Languages : en
Pages : 506
Get Book Here
Book Description
As the advancement of technology continues, cyber security continues to play a significant role in todays world. With society becoming more dependent on the internet, new opportunities for virtual attacks can lead to the exposure of critical information. Machine and deep learning techniques to prevent this exposure of information are being applied to address mounting concerns in computer security. The Handbook of Research on Machine and Deep Learning Applications for Cyber Security is a pivotal reference source that provides vital research on the application of machine learning techniques for network security research. While highlighting topics such as web security, malware detection, and secure information sharing, this publication explores recent research findings in the area of electronic security as well as challenges and countermeasures in cyber security research. It is ideally designed for software engineers, IT specialists, cybersecurity analysts, industrial experts, academicians, researchers, and post-graduate students.
Author: William Stallings
Publisher: Pearson Higher Ed
ISBN: 0133072630
Category : Computers
Languages : en
Pages : 817
Get Book Here
Book Description
This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. Computer Security: Principles and Practice, 2e, is ideal for courses in Computer/Network Security. In recent years, the need for education in computer security and related topics has grown dramatically – and is essential for anyone studying Computer Science or Computer Engineering. This is the only text available to provide integrated, comprehensive, up-to-date coverage of the broad range of topics in this subject. In addition to an extensive pedagogical program, the book provides unparalleled support for both research and modeling projects, giving students a broader perspective. The Text and Academic Authors Association named Computer Security: Principles and Practice, 1e, the winner of the Textbook Excellence Award for the best Computer Science textbook of 2008.
