Analysis of Machine Learning Techniques for Intrusion Detection System: A Review
Analysis of Machine Learning Techniques for Intrusion Detection System: A Review

Author: Asghar Ali Shah

Publisher: Infinite Study

Published:

Total Pages: 11

ISBN-13:

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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.

Machine Learning Techniques and Analytics for Cloud Security
Machine Learning Techniques and Analytics for Cloud Security

Author: Rajdeep Chakraborty

Publisher: John Wiley & Sons

Published: 2021-11-30

Total Pages: 484

ISBN-13: 1119764092

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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.

Machine Learning in Intrusion Detection
Machine Learning in Intrusion Detection

Author: Yihua Liao

Publisher:

Published: 2005

Total Pages: 230

ISBN-13:

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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.

Computational Methodologies for Electrical and Electronics Engineers
Computational Methodologies for Electrical and Electronics Engineers

Author: Singh, Rajiv

Publisher: IGI Global

Published: 2021-03-18

Total Pages: 281

ISBN-13: 1799833291

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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.

Design and Development of Efficient Energy Systems
Design and Development of Efficient Energy Systems

Author: Suman Lata Tripathi

Publisher: John Wiley & Sons

Published: 2021-03-16

Total Pages: 384

ISBN-13: 1119761778

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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.

Computer Networks, Big Data and IoT
Computer Networks, Big Data and IoT

Author: A.Pasumpon Pandian

Publisher: Springer Nature

Published: 2021-06-21

Total Pages: 980

ISBN-13: 9811609659

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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.

Proceedings of International Conference on Emerging Technologies and Intelligent Systems
Proceedings of International Conference on Emerging Technologies and Intelligent Systems

Author: Mostafa Al-Emran

Publisher: Springer

Published: 2021-12-03

Total Pages: 1046

ISBN-13: 9783030859893

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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.

Computing and Network Sustainability
Computing and Network Sustainability

Author: Sheng-Lung Peng

Publisher: Springer

Published: 2019-05-02

Total Pages: 522

ISBN-13: 9811371504

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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.

2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)
2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)

Author: IEEE Staff

Publisher:

Published: 2021-09-03

Total Pages:

ISBN-13: 9781665417044

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In this globally competitive environment scientific analysis of system under study is the key issues in attaining market leadership This competitive advantage through quality process, product and services in the market place is possible through the development of knowledge bases and easy access to structured databases on systems, processes and technology based on quantitative study Further due to ever emerging new trends of fashion and taste as well as technology, predicting future with certainty can be the daydream This theme is most appropriate in the current context as well as in the future The Conference will not only take stock of trends and developments at the globally competitive environment, but will also provide future directions to young researchers and practitioners

Sensor Data Analysis and Management
Sensor Data Analysis and Management

Author: A. Suresh

Publisher: John Wiley & Sons

Published: 2021-11-22

Total Pages: 228

ISBN-13: 1119682428

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Discover detailed insights into the methods, algorithms, and techniques for deep learning in sensor data analysis Sensor Data Analysis and Management: The Role of Deep Learning delivers an insightful and practical overview of the applications of deep learning techniques to the analysis of sensor data. The book collects cutting-edge resources into a single collection designed to enlighten the reader on topics as varied as recent techniques for fault detection and classification in sensor data, the application of deep learning to Internet of Things sensors, and a case study on high-performance computer gathering and processing of sensor data. The editors have curated a distinguished group of perceptive and concise papers that show the potential of deep learning as a powerful tool for solving complex modelling problems across a broad range of industries, including predictive maintenance, health monitoring, financial portfolio forecasting, and driver assistance. The book contains real-time examples of analyzing sensor data using deep learning algorithms and a step-by-step approach for installing and training deep learning using the Python keras library. Readers will also benefit from the inclusion of: A thorough introduction to the Internet of Things for human activity recognition, based on wearable sensor data An exploration of the benefits of neural networks in real-time environmental sensor data analysis Practical discussions of supervised learning data representation, neural networks for predicting physical activity based on smartphone sensor data, and deep-learning analysis of location sensor data for human activity recognition An analysis of boosting with XGBoost for sensor data analysis Perfect for industry practitioners and academics involved in deep learning and the analysis of sensor data, Sensor Data Analysis and Management: The Role of Deep Learning will also earn a place in the libraries of undergraduate and graduate students in data science and computer science programs.