Analysis Of Machine Learning Techniques For Intrusion Detection System A Review
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| Author | : Asghar Ali Shah |
| Publisher | : Infinite Study |
| Total Pages | : 11 |
| Release | : |
| Genre | : |
| ISBN | : |
Security is a key issue to both computer and computer networks. Intrusion detection System (IDS) is one of the major research problems in network security. IDSs are developed to detect both known and unknown attacks. There are many techniques used in IDS for protecting computers and networks from network based and host based attacks. Various Machine learning techniques are used in IDS. This study analyzes machine learning techniques in IDS. It also reviews many related studies done in the period from 2000 to 2012 and it focuses on machine learning techniques. Related studies include single, hybrid, ensemble classifiers, baseline and datasets used.
| Author | : Zhenwei Yu |
| Publisher | : World Scientific |
| Total Pages | : 185 |
| Release | : 2011 |
| Genre | : Computers |
| ISBN | : 1848164475 |
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.
| Author | : Yihua Liao |
| Publisher | : |
| Total Pages | : 230 |
| Release | : 2005 |
| Genre | : |
| ISBN | : |
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 | : Rajdeep Chakraborty |
| Publisher | : John Wiley & Sons |
| Total Pages | : 484 |
| Release | : 2021-11-30 |
| Genre | : Computers |
| ISBN | : 1119764092 |
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 | : Singh, Rajiv |
| Publisher | : IGI Global |
| Total Pages | : 281 |
| Release | : 2021-03-18 |
| Genre | : Technology & Engineering |
| ISBN | : 1799833291 |
Artificial intelligence has been applied to many areas of science and technology, including the power and energy sector. Renewable energy in particular has experienced the tremendous positive impact of these developments. With the recent evolution of smart energy technologies, engineers and scientists working in this sector need an exhaustive source of current knowledge to effectively cater to the energy needs of citizens of developing countries. Computational Methodologies for Electrical and Electronics Engineers is a collection of innovative research that provides a complete insight and overview of the application of intelligent computational techniques in power and energy. Featuring research on a wide range of topics such as artificial neural networks, smart grids, and soft computing, this book is ideally designed for programmers, engineers, technicians, ecologists, entrepreneurs, researchers, academicians, and students.
| Author | : Mostafa Al-Emran |
| Publisher | : Springer Nature |
| Total Pages | : 1024 |
| Release | : 2021-12-02 |
| Genre | : Technology & Engineering |
| ISBN | : 3030859908 |
This book sheds light on the emerging research trends in intelligent systems and their applications. It mainly focuses on four different themes, including Artificial Intelligence and Soft Computing, Information Security and Networking, Medical Informatics, and Advances in Information Systems. Each chapter contributes to the aforementioned themes by discussing the recent design, developments, and modifications of intelligent systems and their applications.
| Author | : IEEE Staff |
| Publisher | : |
| Total Pages | : |
| Release | : 2020-10-21 |
| Genre | : |
| ISBN | : 9781728173474 |
2020 6th International Conference on Science in Information Technology (ICSITech) is aimed at keeping abreast of the current development and innovation in the advanced of research area on Science in Information Technology as well as providing an engaging forum for participants to share knowledge and expertise in related issues The Scope topics include, but are not limited to Agent System and Multi Agent Systems, Analysis & Design of Information System, Big Data and Data Mining, Cloud & Grid Computing, Cryptography, Decision Support System, DNA Computing, E Government, E Business, Embedded System, Enterprise System, Green software development, Green computing, Human Computer Interaction, Image Processing &Computer Vision, Informatics Theory, Information System, IT for Education, IT for Industry, IT for Society, Mechatronics, Mobile Computing & Applications, Natural Language Processing,Network & Data Communications, Soft Computing, Software Engineering, and Web Engineering
| Author | : Sheng-Lung Peng |
| Publisher | : Springer |
| Total Pages | : 525 |
| Release | : 2019-05-02 |
| Genre | : Technology & Engineering |
| ISBN | : 9811371504 |
This book offers a compilation of technical papers presented at the International Research Symposium on Computing and Network Sustainability (IRSCNS 2018) held in Goa, India on 30–31st August 2018. It covers areas such as sustainable computing and security, sustainable systems and technologies, sustainable methodologies and applications, sustainable networks applications and solutions, user-centered services and systems and mobile data management. Presenting novel and recent technologies, it is a valuable resource for researchers and industry professionals alike.
| Author | : A.Pasumpon Pandian |
| Publisher | : Springer Nature |
| Total Pages | : 980 |
| Release | : 2021-06-21 |
| Genre | : Technology & Engineering |
| ISBN | : 9811609659 |
This book presents best selected research papers presented at the International Conference on Computer Networks, Big Data and IoT (ICCBI 2020), organized by Vaigai College Engineering, Madurai, Tamil Nadu, India, during 15–16 December 2020. The book covers original papers on computer networks, network protocols and wireless networks, data communication technologies and network security. The book is a valuable resource and reference for researchers, instructors, students, scientists, engineers, managers and industry practitioners in those important areas.
| Author | : Suman Lata Tripathi |
| Publisher | : John Wiley & Sons |
| Total Pages | : 386 |
| Release | : 2021-04-13 |
| Genre | : Computers |
| ISBN | : 1119761638 |
There is not a single industry which will not be transformed by machine learning and Internet of Things (IoT). IoT and machine learning have altogether changed the technological scenario by letting the user monitor and control things based on the prediction made by machine learning algorithms. There has been substantial progress in the usage of platforms, technologies and applications that are based on these technologies. These breakthrough technologies affect not just the software perspective of the industry, but they cut across areas like smart cities, smart healthcare, smart retail, smart monitoring, control, and others. Because of these “game changers,” governments, along with top companies around the world, are investing heavily in its research and development. Keeping pace with the latest trends, endless research, and new developments is paramount to innovate systems that are not only user-friendly but also speak to the growing needs and demands of society. This volume is focused on saving energy at different levels of design and automation including the concept of machine learning automation and prediction modeling. It also deals with the design and analysis for IoT-enabled systems including energy saving aspects at different level of operation. The editors and contributors also cover the fundamental concepts of IoT and machine learning, including the latest research, technological developments, and practical applications. Valuable as a learning tool for beginners in this area as well as a daily reference for engineers and scientists working in the area of IoT and machine technology, this is a must-have for any library.
