Machine Learning for Cyber Security, Xiaofeng Chen; Xinyi Huang; Jun Zhang
Автор: Shlomi Dolev; Sachin Lodha Название: Cyber Security Cryptography and Machine Learning ISBN: 3319600796 ISBN-13(EAN): 9783319600796 Издательство: Springer Рейтинг: Цена: 9083.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the proceedings of the first International Symposium on Cyber Security Cryptography and Machine Learning, held in Beer-Sheva, Israel, in June 2017. The 17 full and 4 short papers presented include cyber security; secure software development methodologies, formal methods semantics and verification of secure systems;
Автор: Miroslav Kubat Название: An Introduction to Machine Learning ISBN: 3319348868 ISBN-13(EAN): 9783319348865 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents basic ideas of machine learning in a way that is easy to understand, by providing hands-on practical advice, using simple examples, and motivating students with discussions of interesting applications.
Автор: Aboul Ella Hassanien; Tai-Hoon Kim; Janusz Kacprzy Название: Bio-inspiring Cyber Security and Cloud Services: Trends and Innovations ISBN: 3662436159 ISBN-13(EAN): 9783662436158 Издательство: Springer Рейтинг: Цена: 26122.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume presents recent research in cyber security and reports how organizations can gain competitive advantages by applying the different security techniques in real-world scenarios.
Автор: G. Sai Sundara Krishnan; R. Anitha; R. S. Lekshmi; Название: Computational Intelligence, Cyber Security and Computational Models ISBN: 8132216792 ISBN-13(EAN): 9788132216797 Издательство: Springer Рейтинг: Цена: 39182.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book contains cutting-edge research material presented by researchers, engineers, developers, and practitioners from academia and industry at the International Conference on Computational Intelligence, Cyber Security and Computational Models (ICC3) organized by PSG College of Technology, Coimbatore, India during December 19-21, 2013.
Описание: This bookaims at promoting high-quality research by researchers and practitioners fromacademia and industry at the InternationalConference on Computational Intelligence, Cyber Security, and ComputationalModels ICC3 2015 organized by PSG College of Technology, Coimbatore, Indiaduring December 17 - 19, 2015.
Автор: Krishna P. Venkata, Gurumoorthy Sasikumar, Obaidat Mohammad S. Название: Social Network Forensics, Cyber Security, and Machine Learning ISBN: 9811314551 ISBN-13(EAN): 9789811314551 Издательство: Springer Рейтинг: Цена: 8384.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book discusses the issues and challenges in Online Social Networks (OSNs). It highlights various aspects of OSNs consisting of novel social network strategies and the development of services using different computing models. Moreover, the book investigates how OSNs are impacted by cutting-edge innovations.
Описание: As the advancement of technology continues, cyber security continues to play a significant role in today's world. With society becoming more dependent on the internet, new opportunities for virtual attacks can lead to the exposure of critical information. Machine and deep learning techniques to prevent this exposure of information are being applied to address mounting concerns in computer security.
The Handbook of Research on Machine and Deep Learning Applications for Cyber Security is a pivotal reference source that provides vital research on the application of machine learning techniques for network security research. While highlighting topics such as web security, malware detection, and secure information sharing, this publication explores recent research findings in the area of electronic security as well as challenges and countermeasures in cyber security research. It is ideally designed for software engineers, IT specialists, cybersecurity analysts, industrial experts, academicians, researchers, and post-graduate students.
Автор: Marcus A. Maloof Название: Machine Learning and Data Mining for Computer Security ISBN: 1849965447 ISBN-13(EAN): 9781849965446 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: "Machine Learning and Data Mining for Computer Security" provides an overview of the current state of research in machine learning and data mining as it applies to problems in computer security.
Автор: Yampolskiy Roman V. Название: Artificial Intelligence Safety and Security ISBN: 0815369824 ISBN-13(EAN): 9780815369820 Издательство: Taylor&Francis Рейтинг: Цена: 7961.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book addresses different aspects of the AI control problem as it relates to the development of safe and secure artificial intelligence. It will be the first to address challenges of constructing safe and secure artificially intelligent systems.
Автор: Aboul Ella Hassanien; Tai-Hoon Kim; Janusz Kacprzy Название: Bio-inspiring Cyber Security and Cloud Services: Trends and Innovations ISBN: 3662508788 ISBN-13(EAN): 9783662508787 Издательство: Springer Рейтинг: Цена: 22201.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume presents recent research in cyber security and reports how organizations can gain competitive advantages by applying the different security techniques in real-world scenarios.
Описание: This book provides an overview of recent innovations and achievements in the broad areas of cyber-physical systems (CPS), including architecture, networking, systems, applications, security, and privacy.
Автор: Bradley Efron and Trevor Hastie Название: Computer Age Statistical Inference ISBN: 1107149894 ISBN-13(EAN): 9781107149892 Издательство: Cambridge Academ Рейтинг: Цена: 9029.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.
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