An Adaptive Hybrid Intrusion Detection System
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| Author | : Alfonso Valdes |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 360 |
| Release | : 2006-02-03 |
| Genre | : Business & Economics |
| ISBN | : 3540317783 |
This book constitutes the refereed proceedings of the 8th International Symposium on Recent Advances in Intrusion Detection held in September 2005. The 15 revised full papers and two practical experience reports were carefully reviewed and selected from 83 submissions. The papers are organized in topical sections on worm detection and containment, anomaly detection, intrusion prevention and response, intrusion detection based on system calls and network-based, as well as intrusion detection in mobile and wireless networks.
| Author | : Yang Xiao |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 423 |
| Release | : 2007-12-29 |
| Genre | : Computers |
| ISBN | : 0387331123 |
This book identifies vulnerabilities in the physical layer, the MAC layer, the IP layer, the transport layer, and the application layer, of wireless networks, and discusses ways to strengthen security mechanisms and services. Topics covered include intrusion detection, secure PHY/MAC/routing protocols, attacks and prevention, immunization, key management, secure group communications and multicast, secure location services, monitoring and surveillance, anonymity, privacy, trust establishment/management, redundancy and security, and dependable wireless networking.
| Author | : Lv, Zhihan |
| Publisher | : IGI Global |
| Total Pages | : 332 |
| Release | : 2024-01-24 |
| Genre | : Computers |
| ISBN | : |
The rapid adoption of deep learning models has resulted in many business services becoming model services, yet most AI systems lack the necessary automation and industrialization capabilities. This leads to heavy reliance on manual operation and maintenance, which not only consumes power but also causes resource wastage and stability issues during system mutations. The inadequate self-adaptation of AI systems poses significant challenges in terms of cost-effectiveness and operational stability. Principles and Applications of Adaptive Artificial Intelligence, edited by Zhihan Lv from Uppsala University, Sweden, offers a comprehensive solution to the self-adaptation problem in AI systems. It explores the latest concepts, technologies, and applications of Adaptive AI, equipping academic scholars and professionals with the necessary knowledge to overcome the challenges faced by traditional business logic transformed into model services. With its problem-solving approach, real-world case studies, and thorough analysis, the Handbook provides practitioners with practical ideas and solutions, while also serving as a valuable teaching material and reference guide for students and educators in AI-related disciplines. By emphasizing self-adaptation, continuous model iteration, and dynamic learning based on real-time feedback, the book empowers readers to significantly enhance the cost-effectiveness and operational stability of AI systems, making it an indispensable resource for researchers, professionals, and students seeking to revolutionize their research and applications in the field of Adaptive AI.
| Author | : S.G. Poonambalam |
| Publisher | : Springer |
| Total Pages | : 541 |
| Release | : 2012-11-28 |
| Genre | : Computers |
| ISBN | : 3642351972 |
This book constitutes the proceedings of the First International Conference on Intelligent Robotics and Manufacturing, IRAM 2012, held in Kuala Lumpur, Malaysia, in November 2012. The 64 revised full papers included in this volume were carefully reviewed and selected from 102 initial submissions. The papers are organized in topical sections named: mobile robots, intelligent autonomous systems, robot vision and robust, autonomous agents, micro, meso and nano-scale automation and assembly, flexible manufacturing systems, CIM and micro-machining, and fabrication techniques.
| Author | : Dhruba Kumar Bhattacharyya |
| Publisher | : CRC Press |
| Total Pages | : 364 |
| Release | : 2013-06-18 |
| Genre | : Computers |
| ISBN | : 146658209X |
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 | : Kevin Daimi |
| Publisher | : Springer |
| Total Pages | : 609 |
| Release | : 2017-08-12 |
| Genre | : Technology & Engineering |
| ISBN | : 3319584243 |
This book introduces readers to the tools needed to protect IT resources and communicate with security specialists when there is a security problem. The book covers a wide range of security topics including Cryptographic Technologies, Network Security, Security Management, Information Assurance, Security Applications, Computer Security, Hardware Security, and Biometrics and Forensics. It introduces the concepts, techniques, methods, approaches, and trends needed by security specialists to improve their security skills and capabilities. Further, it provides a glimpse into future directions where security techniques, policies, applications, and theories are headed. The book represents a collection of carefully selected and reviewed chapters written by diverse security experts in the listed fields and edited by prominent security researchers. Complementary slides are available for download on the book’s website at Springer.com.
| Author | : Al-Sakib Khan Pathan |
| Publisher | : CRC Press |
| Total Pages | : 516 |
| Release | : 2014-01-29 |
| Genre | : Computers |
| ISBN | : 1482203510 |
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.
| Author | : Jürgen Beyerer |
| Publisher | : Springer |
| Total Pages | : 76 |
| Release | : 2016-11-25 |
| Genre | : Technology & Engineering |
| ISBN | : 3662538067 |
The work presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains some selected papers from the international Conference ML4CPS – Machine Learning for Cyber Physical Systems, which was held in Karlsruhe, September 29th, 2016. Cyber Physical Systems are characterized by their ability to adapt and to learn: They analyze their environment and, based on observations, they learn patterns, correlations and predictive models. Typical applications are condition monitoring, predictive maintenance, image processing and diagnosis. Machine Learning is the key technology for these developments.
| Author | : Álvaro Herrero |
| Publisher | : Springer Nature |
| Total Pages | : 477 |
| Release | : 2020-08-27 |
| Genre | : Technology & Engineering |
| ISBN | : 3030578054 |
This book contains accepted papers presented at CISIS 2020 held in the beautiful and historic city of Burgos (Spain), in September 2020. The aim of the CISIS 2020 conference is to offer a meeting opportunity for academic and industry-related researchers belonging to the various, vast communities of computational intelligence, information security, and data mining. The need for intelligent, flexible behaviour by large, complex systems, especially in mission-critical domains, is intended to be the catalyst and the aggregation stimulus for the overall event. After a thorough peer-review process, the CISIS 2020 International Program Committee selected 43 papers which are published in these conference proceedings achieving an acceptance rate of 28%. Due to the COVID-19 outbreak, the CISIS 2020 edition was blended, combining on-site and on-line participation. In this relevant edition, a special emphasis was put on the organization of five special sessions related to relevant topics as Fake News Detection and Prevention, Mathematical Methods and Models in Cybersecurity, Measurements for a Dynamic Cyber-Risk Assessment, Cybersecurity in a Hybrid Quantum World, Anomaly/Intrusion Detection, and From the least to the least: cryptographic and data analytics solutions to fulfil least minimum privilege and endorse least minimum effort in information systems. The selection of papers was extremely rigorous in order to maintain the high quality of the conference and we would like to thank the members of the Program Committees for their hard work in the reviewing process. This is a crucial process to the creation of a high standard conference, and the CISIS conference would not exist without their help.
| Author | : Satchidananda Dehuri |
| Publisher | : World Scientific |
| Total Pages | : 325 |
| Release | : 2011 |
| Genre | : Business & Economics |
| ISBN | : 184816386X |
Knowledge Mining Using Intelligent Agents explores the concept of knowledge discovery processes and enhances decision-making capability through the use of intelligent agents like ants, termites and honey bees. In order to provide readers with an integrated set of concepts and techniques for understanding knowledge discovery and its practical utility, this book blends two distinct disciplines data mining and knowledge discovery process, and intelligent agents-based computing (swarm intelligence and computational intelligence). For the more advanced reader, researchers, and decision/policy-makers are given an insight into emerging technologies and their possible hybridization, which can be used for activities like dredging, capturing, distributions and the utilization of knowledge in their domain of interest (i.e. business, policy-making, etc.). By studying the behavior of swarm intelligence, this book aims to integrate the computational intelligence paradigm and intelligent distributed agents architecture to optimize various engineering problems and efficiently represent knowledge from the large gamut of data.
