Artificial Intelligence For Intrusion Detection Systems
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Artificial Intelligence For Intrusion Detection Systems
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Author : Mayank Swarnkar
language : en
Publisher: CRC Press
Release Date : 2023-10-16
Artificial Intelligence For Intrusion Detection Systems written by Mayank Swarnkar and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-16 with Computers categories.
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.
Artificial Intelligence For Intrusion Detection Systems
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Author : Mayank Swarnkar
language : en
Publisher: CRC Press
Release Date : 2023-10-16
Artificial Intelligence For Intrusion Detection Systems written by Mayank Swarnkar and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-16 with Computers categories.
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.
Artificial Intelligence For Intrusion Detection System
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Author : Joseph Elias
language : en
Publisher:
Release Date : 2018
Artificial Intelligence For Intrusion Detection System written by Joseph Elias and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.
Machine Learning Techniques And Analytics For Cloud Security
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Author : Rajdeep Chakraborty
language : en
Publisher: John Wiley & Sons
Release Date : 2021-12-21
Machine Learning Techniques And Analytics For Cloud Security written by Rajdeep Chakraborty and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-21 with Computers categories.
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.
2018 4th International Conference On Computing Communication And Automation Iccca
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Author : IEEE Staff
language : en
Publisher:
Release Date : 2018-12-14
2018 4th International Conference On Computing Communication And Automation Iccca written by IEEE Staff and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-14 with categories.
School of Computing Science & Engineering of Galgotias University Uttar Pradesh, invites you to associate with us for upcoming conference, ICCCA2018, a two day International Conference to be held on December 14 15, 2018 ICCCA2018 International Conference on Computing, Communication and Automation team with pleasure invites you to contribute with original research papers, to this blind and peer reviewed conference
Design And Analysis Of Security Protocol For Communication
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Author : Dinesh Goyal
language : en
Publisher: John Wiley & Sons
Release Date : 2020-03-17
Design And Analysis Of Security Protocol For Communication written by Dinesh Goyal and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-17 with Computers categories.
The purpose of designing this book is to discuss and analyze security protocols available for communication. Objective is to discuss protocols across all layers of TCP/IP stack and also to discuss protocols independent to the stack. Authors will be aiming to identify the best set of security protocols for the similar applications and will also be identifying the drawbacks of existing protocols. The authors will be also suggesting new protocols if any.
Artificial Intelligence And Applications
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Author : Hamid R. Arabnia
language : en
Publisher: Springer Nature
Release Date : 2025-05-02
Artificial Intelligence And Applications written by Hamid R. Arabnia and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-02 with Computers categories.
This book constitutes the proceedings of the 26th International Conference on Artificial Intelligence and Applications, ICAI 2024, held as part of the 2024 World Congress in Computer Science, Computer Engineering and Applied Computing, in Las Vegas, USA, during July 22 to July 25, 2024. The 38 full papers included in this book were carefully reviewed and selected from 376 submissions. They have been organized in topical sections as follows: Deep convolutional neural networks, ANNs, and applications; machine learning and novel applications; large language models and applications; data science, recognition and authentication methods and applications; artificial intelligence and applications; XXIV Technical Session on Applications of Advanced AI Techniques to information management for solving company-related problems.
The State Of The Art In Intrusion Prevention And Detection
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Author : Al-Sakib Khan Pathan
language : en
Publisher: CRC Press
Release Date : 2014-01-29
The State Of The Art In Intrusion Prevention And Detection written by Al-Sakib Khan Pathan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-29 with Computers categories.
The State of the Art in Intrusion Prevention and Detection analyzes the latest trends and issues surrounding intrusion detection systems in computer networks, especially in communications networks. Its broad scope of coverage includes wired, wireless, and mobile networks; next-generation converged networks; and intrusion in social networks. Presenting cutting-edge research, the book presents novel schemes for intrusion detection and prevention. It discusses tracing back mobile attackers, secure routing with intrusion prevention, anomaly detection, and AI-based techniques. It also includes information on physical intrusion in wired and wireless networks and agent-based intrusion surveillance, detection, and prevention. The book contains 19 chapters written by experts from 12 different countries that provide a truly global perspective. The text begins by examining traffic analysis and management for intrusion detection systems. It explores honeypots, honeynets, network traffic analysis, and the basics of outlier detection. It talks about different kinds of IDSs for different infrastructures and considers new and emerging technologies such as smart grids, cyber physical systems, cloud computing, and hardware techniques for high performance intrusion detection. The book covers artificial intelligence-related intrusion detection techniques and explores intrusion tackling mechanisms for various wireless systems and networks, including wireless sensor networks, WiFi, and wireless automation systems. Containing some chapters written in a tutorial style, this book is an ideal reference for graduate students, professionals, and researchers working in the field of computer and network security.
Artificial Intelligence For Security
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Author : Tuomo Sipola
language : en
Publisher: Springer Nature
Release Date : 2024-06-28
Artificial Intelligence For Security written by Tuomo Sipola and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-28 with Computers categories.
This book discusses the use of artificial intelligence (AI) for security purposes. It is divided into three parts: methodological fundamentals of AI, use of AI for critical infrastructure protection and anomaly detection. The first section describes the latest knowledge for creating safe AIs and using them to enhance protection. This book also presents various domains and examples of AI-driven security. The chapters describe potential methods, demonstrate use cases and discuss the challenges of the evolving field. This includes topics such as defensive use of AI to detect threats. It discusses the offensive use of AI to better understand the future threat landscape, the use of AI for automation in critical infrastructure and overall challenges of AI usage for critical tasks. As new threats emerge, the use of AI technologies to protect the world one lives in is topical. New technologies in this space have advanced rapidly, and subsequently, their use in enhancing protection is an evident development. To this effect, this book brings together a group of international researchers and professionals who present their views on how to create security through AI. This book targets postgraduate students, researchers and professionals who want to understand the use of AI for security. Understanding latest advancements in this field will also be useful to those who want to comprehend modern cybersecurity in detail and who want to follow research and latest trends.
Machine Learning In Intrusion Detection
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Author : Yihua Liao
language : en
Publisher:
Release Date : 2005
Machine Learning In Intrusion Detection written by Yihua Liao and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with categories.
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.