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Network Intrusion Detection Using Deep Learning
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Book Synopsis Network Intrusion Detection using Deep Learning by : Kwangjo Kim
Download or read book Network Intrusion Detection using Deep Learning written by Kwangjo Kim and published by Springer. This book was released on 2018-10-02 with total page 79 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Network Intrusion Detection using Deep Learning by : Kwangjo Kim
Download or read book Network Intrusion Detection using Deep Learning written by Kwangjo Kim and published by Springer. This book was released on 2018-09-25 with total page 79 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Network Intrusion Detection Using Deep Learning by : Kwangjo Kim
Download or read book Network Intrusion Detection Using Deep Learning written by Kwangjo Kim and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis 2018 9th International Conference on Computing, Communication and Networking Technologies (ICCCNT) by : IEEE Staff
Download or read book 2018 9th International Conference on Computing, Communication and Networking Technologies (ICCCNT) written by IEEE Staff and published by . This book was released on 2018-07-10 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The Ninth International Conference on Computing, Communication and Networking Technologies (9th ICCCNT 2018) aims to provide a forum that brings together International researchers from academia and practitioners in the industry to meet and exchange ideas and recent research work on all aspects of Information and Communication Technologies Following the great success of ICCCNT 08, ICCCNT 10, ICCCNT 12, ICCCNT 13, ICCCNT 14, ICCCNT 15,ICCCNT 16 and ICCCNT 17 The ninth edition of the event, ICCCNT 17, will be held in IISc, Bangalore on July 10 12, 2018 The conference will consist of keynote speeches, technical sessions, and exhibition The technical sessions will present original and fundamental research advances, and the workshops will focus on hot topics in Information and Communication Engineering Experts from NASA, MIT, Japan will give key note speeches
Book Synopsis 2019 IEEE 10th International Conference on Software Engineering and Service Science (ICSESS) by : IEEE Staff
Download or read book 2019 IEEE 10th International Conference on Software Engineering and Service Science (ICSESS) written by IEEE Staff and published by . This book was released on 2019-10-18 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Software Engineering,Big Data and Intelligent Computing,Computer Science,Deep Learning,Computer Network and Application Technology,Web Information Systems and Applications, Artificial Intelligence and Expert Systems,Database System and Application,Blockchain Technology,Other related theories, Technologies and applications
Book Synopsis Network Anomaly Detection by : Dhruba Kumar Bhattacharyya
Download or read book Network Anomaly Detection written by Dhruba Kumar Bhattacharyya and published by CRC Press. This book was released on 2013-06-18 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 behavior. Finding these anomalies has extensive applications in areas such as cyber security, credit card and insurance fraud detection, and military surveillance for enemy activities. Network Anomaly Detection: A Machine Learning Perspective presents machine learning techniques in depth to help you more effectively detect and counter network intrusion. In this book, you’ll learn about: Network anomalies and vulnerabilities at various layers The pros and cons of various machine learning techniques and algorithms A taxonomy of attacks based on their characteristics and behavior Feature selection algorithms How to assess the accuracy, performance, completeness, timeliness, stability, interoperability, reliability, and other dynamic aspects of a network anomaly detection system Practical tools for launching attacks, capturing packet or flow traffic, extracting features, detecting attacks, and evaluating detection performance Important unresolved issues and research challenges that need to be overcome to provide better protection for networks Examining numerous attacks in detail, the authors look at the tools that intruders use and show how to use this knowledge to protect networks. The book also provides material for hands-on development, so that you can code on a testbed to implement detection methods toward the development of your own intrusion detection system. It offers a thorough introduction to the state of the art in network anomaly detection using machine learning approaches and systems.
Download or read book Intrusion Detection written by Zhenwei Yu and published by World Scientific. This book was released on 2011 with total page 185 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Deep Learning Applications for Cyber Security by : Mamoun Alazab
Download or read book Deep Learning Applications for Cyber Security written by Mamoun Alazab and published by Springer. This book was released on 2019-08-14 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis 2019 4th International Conference on Computer Science and Engineering (UBMK) by : IEEE Staff
Download or read book 2019 4th International Conference on Computer Science and Engineering (UBMK) written by IEEE Staff and published by . This book was released on 2019-09-11 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: COMPUTER SCIENCE AND ENGINEERING
Book Synopsis Automatic Speech Recognition by : Dong Yu
Download or read book Automatic Speech Recognition written by Dong Yu and published by Springer. This book was released on 2014-11-11 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Deep Learning Applications for Cyber-Physical Systems by : Mundada, Monica R.
Download or read book Deep Learning Applications for Cyber-Physical Systems written by Mundada, Monica R. and published by IGI Global. This book was released on 2021-12-17 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big data generates around us constantly from daily business, custom use, engineering, and science activities. Sensory data is collected from the internet of things (IoT) and cyber-physical systems (CPS). Merely storing such a massive amount of data is meaningless, as the key point is to identify, locate, and extract valuable knowledge from big data to forecast and support services. Such extracted valuable knowledge is usually referred to as smart data. It is vital to providing suitable decisions in business, science, and engineering applications. Deep Learning Applications for Cyber-Physical Systems provides researchers a platform to present state-of-the-art innovations, research, and designs while implementing methodological and algorithmic solutions to data processing problems and designing and analyzing evolving trends in health informatics and computer-aided diagnosis in deep learning techniques in context with cyber physical systems. Covering topics such as smart medical systems, intrusion detection systems, and predictive analytics, this text is essential for computer scientists, engineers, practitioners, researchers, students, and academicians, especially those interested in the areas of internet of things, machine learning, deep learning, and cyber-physical systems.
Book Synopsis Deep Learning Approaches to Cloud Security by : Pramod Singh Rathore
Download or read book Deep Learning Approaches to Cloud Security written by Pramod Singh Rathore and published by John Wiley & Sons. This book was released on 2022-01-26 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: DEEP LEARNING APPROACHES TO CLOUD SECURITY Covering one of the most important subjects to our society today, cloud security, this editorial team delves into solutions taken from evolving deep learning approaches, solutions allowing computers to learn from experience and understand the world in terms of a hierarchy of concepts, with each concept defined through its relation to simpler concepts. Deep learning is the fastest growing field in computer science. Deep learning algorithms and techniques are found to be useful in different areas like automatic machine translation, automatic handwriting generation, visual recognition, fraud detection, and detecting developmental delay in children. However, applying deep learning techniques or algorithms successfully in these areas needs a concerted effort, fostering integrative research between experts ranging from diverse disciplines from data science to visualization. This book provides state of the art approaches of deep learning in these areas, including areas of detection and prediction, as well as future framework development, building service systems and analytical aspects. In all these topics, deep learning approaches, such as artificial neural networks, fuzzy logic, genetic algorithms, and hybrid mechanisms are used. This book is intended for dealing with modeling and performance prediction of the efficient cloud security systems, thereby bringing a newer dimension to this rapidly evolving field. This groundbreaking new volume presents these topics and trends of deep learning, bridging the research gap, and presenting solutions to the challenges facing the engineer or scientist every day in this area. Whether for the veteran engineer or the student, this is a must-have for any library. Deep Learning Approaches to Cloud Security: Is the first volume of its kind to go in-depth on the newest trends and innovations in cloud security through the use of deep learning approaches Covers these important new innovations, such as AI, data mining, and other evolving computing technologies in relation to cloud security Is a useful reference for the veteran computer scientist or engineer working in this area or an engineer new to the area, or a student in this area Discusses not just the practical applications of these technologies, but also the broader concepts and theory behind how these deep learning tools are vital not just to cloud security, but society as a whole Audience: Computer scientists, scientists and engineers working with information technology, design, network security, and manufacturing, researchers in computers, electronics, and electrical and network security, integrated domain, and data analytics, and students in these areas
Book Synopsis 2021 IEEE 18th Annual Consumer Communications and Networking Conference (CCNC) by : IEEE Staff
Download or read book 2021 IEEE 18th Annual Consumer Communications and Networking Conference (CCNC) written by IEEE Staff and published by . This book was released on 2021-01-09 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: IEEE CCNC 2021 will present the latest developments and technical solutions in the areas of home networking, consumer networking, enabling technologies (such as middleware) and novel applications and services The conference will include a peer reviewed program of technical sessions, special sessions, business application sessions, tutorials, and demonstration sessions
Book Synopsis 2021 IEEE Latin American Conference on Communications (LATINCOM) by : IEEE Staff
Download or read book 2021 IEEE Latin American Conference on Communications (LATINCOM) written by IEEE Staff and published by . This book was released on 2021-11-17 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The IEEE LATINCOM is an international conference organized by the IEEE Communications Society (ComSoc) Latin American Region IEEE LATINCOM is the most important conference on communications in Latin America it is held annually and attracts submissions and participants from all around the world Topics covered include Mobile and Wireless Networking, Communications Services, Optical Communications, Communications QoS, Reliability, and Performance Modeling, Communications Systems and Signal Processing, Enabling Technologies and Other Special Selected Areas of Communications
Book Synopsis Machine Learning Techniques and Analytics for Cloud Security by : Rajdeep Chakraborty
Download or read book Machine Learning Techniques and Analytics for Cloud Security written by Rajdeep Chakraborty and published by John Wiley & Sons. This book was released on 2021-11-30 with total page 484 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Computer Security by : William Stallings
Download or read book Computer Security written by William Stallings and published by Pearson Educational. This book was released on 2023-04 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Since the fourth edition of this book was published, the field has seen continued innovations and improvements. In this new edition, we try to capture these changes while maintaining a broad and comprehensive coverage of the entire field. There have been a number of refinements to improve pedagogy and user-friendliness, updated references, and mention of recent security incidents, along with a number of more substantive changes throughout the book"--
Book Synopsis A study on network intrusion detection using classifiers by : Balamurugan Rengeswaran
Download or read book A study on network intrusion detection using classifiers written by Balamurugan Rengeswaran and published by GRIN Verlag. This book was released on 2019-10-21 with total page 42 pages. Available in PDF, EPUB and Kindle. Book excerpt: Research Paper (undergraduate) from the year 2019 in the subject Computer Science - Applied, VIT University, language: English, abstract: In these days of rising internet usage, almost everyone has access to the internet. It is available easily and readily. So along with increase in popularity and importance it also leads to an increase in risks and susceptibility to unwanted attacks. Networks and servers and more prone to malicious attacks than ever. Cyber security is vital in this age. Lots of organizations now interact and communicate with people via the internet. They store huge amounts of data in their computers or devices connected to the network. This data should only be accessed by authorized members of the organization. It is possible for hackers to gain unauthorized access to this data. A lot of sensitive information is present in the data which might lead to harm in the hands of hackers. It is important to protect the network from being attacked in such a way. Network security is an element of cyber security which aims to provide services so that the organizations are safe from such attacks. Intrusion detection systems are present in the network which work along with the firewalls to detect and prevent such attacks. For this project, we aim to identify the suitable machine learning technique to detect such attacks and which can be used in state of the art system.
