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Machine Learning For Application Layer Intrusion Detection
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Book Synopsis Machine Learning for Application-Layer Intrusion Detection by : Konrad
Download or read book Machine Learning for Application-Layer Intrusion Detection written by Konrad and published by Lulu.com. This book was released on 2011-09-21 with total page 181 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is concerned with the automatic detection of unknown attacks in network communication. Based on concepts of machine learning, a framework for self-learning intrusion detection is proposed which enables accurate and efficient identification of attacks in the application layer of network communication. The book is a doctoral thesis and targets researchers and postgraduate students in the area of computer security and machine learning.
Book Synopsis Deep Learning Applications for Cyber Security by : Mamoun Alazab
Download or read book Deep Learning Applications for Cyber Security written by Mamoun Alazab and published by Springer. This book was released on 2019-08-14 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cybercrime remains a growing challenge in terms of security and privacy practices. Working together, deep learning and cyber security experts have recently made significant advances in the fields of intrusion detection, malicious code analysis and forensic identification. This book addresses questions of how deep learning methods can be used to advance cyber security objectives, including detection, modeling, monitoring and analysis of as well as defense against various threats to sensitive data and security systems. Filling an important gap between deep learning and cyber security communities, it discusses topics covering a wide range of modern and practical deep learning techniques, frameworks and development tools to enable readers to engage with the cutting-edge research across various aspects of cyber security. The book focuses on mature and proven techniques, and provides ample examples to help readers grasp the key points.
Book Synopsis Nature-Inspired Computation in Data Mining and Machine Learning by : Xin-She Yang
Download or read book Nature-Inspired Computation in Data Mining and Machine Learning written by Xin-She Yang and published by Springer Nature. This book was released on 2019-09-03 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews the latest developments in nature-inspired computation, with a focus on the cross-disciplinary applications in data mining and machine learning. Data mining, machine learning and nature-inspired computation are current hot research topics due to their importance in both theory and practical applications. Adopting an application-focused approach, each chapter introduces a specific topic, with detailed descriptions of relevant algorithms, extensive literature reviews and implementation details. Covering topics such as nature-inspired algorithms, swarm intelligence, classification, clustering, feature selection, cybersecurity, learning algorithms over cloud, extreme learning machines, object categorization, particle swarm optimization, flower pollination and firefly algorithms, and neural networks, it also presents case studies and applications, including classifications of crisis-related tweets, extraction of named entities in the Tamil language, performance-based prediction of diseases, and healthcare services. This book is both a valuable a reference resource and a practical guide for students, researchers and professionals in computer science, data and management sciences, artificial intelligence and machine learning.
Book Synopsis Mathematics and Computing by : Debasis Giri
Download or read book Mathematics and Computing written by Debasis Giri and published by Springer. This book was released on 2017-04-14 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the Third International Conference on Mathematics and Computing, ICMC 2017, held in Haldia, India, in January 2017. The 35 papers presented in this volume were carefully reviewed and selected from 129 submissions. They were organized in topical sections named: security and privacy; computing; applied mathematics; and pure mathematics.
Book Synopsis Modeling Decisions for Artificial Intelligence by : Vicenç Torra
Download or read book Modeling Decisions for Artificial Intelligence written by Vicenç Torra and published by Springer Science & Business Media. This book was released on 2010-10-19 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains papers presented at the 7th International Conference on Modeling Decisions for Arti?cial Intelligence (MDAI 2010), held in Perpignan, France, October 27–29. This conference followed MDAI 2004 (Barcelona, C- alonia, Spain), MDAI 2005 (Tsukuba, Japan), MDAI 2006 (Tarragona, Cata- nia, Spain), MDAI 2007 (Kitakyushu, Japan), MDAI 2008 (Sabadell, Catalonia, Spain), and MDAI 2009 (Awaji Island, Japan) with proceedings also published in the LNAI series (Vols. 3131, 3558, 3885, 4617, 5285, and 5861). The aim of this conference was to provide a forum for researchers to discuss theory and tools for modeling decisions, as well as applications that encompass decision-making processes and information fusion techniques. The organizers received 43 papers from 12 di?erent countries, from Europe, Asia, Australia and Africa, 25 of which are published in this volume. Each s- mission received at least two reviews from the Program Committee and a few externalreviewers.Wewouldliketoexpressourgratitudetothemfortheirwork. The plenary talks presented at the conference are also included in this volume. TheconferencewassupportedbytheCNRS:CentreNationaldelaRecherche Scienti?que,theUniversit´ edePerpignanVia Domitia,theELIAUS:Laboratoire Electronique Informatique Automatique Syst` emes, IMERIR: Ecole d'Ing´ enierie Informatique et Robotique, the UNESCO Chair in Data Privacy, the Japan - cietyforFuzzyTheoryandIntelligentInformatics(SOFT),theCatalanAssoc- tionfor Arti?cialIntelligence(ACIA), the EuropeanSociety for Fuzzy Logicand Technology(EUSFLAT), the Spanish MEC(ARES—CONSOLIDER INGENIO 2010 CSD2007-00004).
Book Synopsis Intrusion Detection: A Machine Learning Approach by : Jeffrey J P Tsai
Download or read book Intrusion Detection: A Machine Learning Approach written by Jeffrey J P Tsai and published by World Scientific. This book was released on 2011-01-03 with total page 185 pages. Available in PDF, EPUB and Kindle. Book excerpt: This important book introduces the concept of intrusion detection, discusses various approaches for intrusion detection systems (IDS), and presents the architecture and implementation of IDS. It emphasizes on the prediction and learning algorithms for intrusion detection and highlights techniques for intrusion detection of wired computer networks and wireless sensor networks. The performance comparison of various IDS via simulation will also be included.
Book Synopsis Modeling Decisions for Artificial Intelligence by : Vincenc Torra
Download or read book Modeling Decisions for Artificial Intelligence written by Vincenc Torra and published by Springer. This book was released on 2012-11-07 with total page 433 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 9th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2012, held in Girona, Catalonia, Spain, in November 2012. The 32 revised full papers were carefully reviewed and selected from 49 submissions and are presented with 4 plenary talks. The papers are organized in topical sections on aggregation operators, integrals, data privacy and security, reasoning, applications, and clustering and similarity.
Book Synopsis Correct Software in Web Applications and Web Services by : Bernhard Thalheim
Download or read book Correct Software in Web Applications and Web Services written by Bernhard Thalheim and published by Springer. This book was released on 2015-06-12 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: The papers in this volume aim at obtaining a common understanding of the challenging research questions in web applications comprising web information systems, web services, and web interoperability; obtaining a common understanding of verification needs in web applications; achieving a common understanding of the available rigorous approaches to system development, and the cases in which they have succeeded; identifying how rigorous software engineering methods can be exploited to develop suitable web applications; and at developing a European-scale research agenda combining theory, methods and tools that would lead to suitable web applications with the potential to implement systems for computation in the public domain.
Book Synopsis Proceedings of International Joint Conference on Computational Intelligence by : Mohammad Shorif Uddin
Download or read book Proceedings of International Joint Conference on Computational Intelligence written by Mohammad Shorif Uddin and published by Springer. This book was released on 2019-07-03 with total page 728 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers outstanding research papers presented at the International Joint Conference on Computational Intelligence (IJCCI 2018), which was held at Daffodil International University on 14–15 December 2018. The topics covered include: collective intelligence, soft computing, optimization, cloud computing, machine learning, intelligent software, robotics, data science, data security, big data analytics, and signal and natural language processing.
Book Synopsis Security, Privacy, and Anonymity in Computation, Communication, and Storage by : Guojun Wang
Download or read book Security, Privacy, and Anonymity in Computation, Communication, and Storage written by Guojun Wang and published by Springer. This book was released on 2019-07-10 with total page 522 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 12th International Conference on Security, Privacy, and Anonymity in Computation, Communication, and Storage, SpaCCS 2019, held in Atlanta, GA, USA in July 2019. The 37 full papers were carefully reviewed and selected from 109 submissions. The papers cover many dimensions including security algorithms and architectures, privacy-aware policies, regulations and techniques, anonymous computation and communication, encompassing fundamental theoretical approaches, practical experimental projects, and commercial application systems for computation, communication and storage.
Book Synopsis Game Theory and Machine Learning for Cyber Security by : Charles A. Kamhoua
Download or read book Game Theory and Machine Learning for Cyber Security written by Charles A. Kamhoua and published by John Wiley & Sons. This book was released on 2021-09-15 with total page 546 pages. Available in PDF, EPUB and Kindle. Book excerpt: GAME THEORY AND MACHINE LEARNING FOR CYBER SECURITY Move beyond the foundations of machine learning and game theory in cyber security to the latest research in this cutting-edge field In Game Theory and Machine Learning for Cyber Security, a team of expert security researchers delivers a collection of central research contributions from both machine learning and game theory applicable to cybersecurity. The distinguished editors have included resources that address open research questions in game theory and machine learning applied to cyber security systems and examine the strengths and limitations of current game theoretic models for cyber security. Readers will explore the vulnerabilities of traditional machine learning algorithms and how they can be mitigated in an adversarial machine learning approach. The book offers a comprehensive suite of solutions to a broad range of technical issues in applying game theory and machine learning to solve cyber security challenges. Beginning with an introduction to foundational concepts in game theory, machine learning, cyber security, and cyber deception, the editors provide readers with resources that discuss the latest in hypergames, behavioral game theory, adversarial machine learning, generative adversarial networks, and multi-agent reinforcement learning. Readers will also enjoy: A thorough introduction to game theory for cyber deception, including scalable algorithms for identifying stealthy attackers in a game theoretic framework, honeypot allocation over attack graphs, and behavioral games for cyber deception An exploration of game theory for cyber security, including actionable game-theoretic adversarial intervention detection against advanced persistent threats Practical discussions of adversarial machine learning for cyber security, including adversarial machine learning in 5G security and machine learning-driven fault injection in cyber-physical systems In-depth examinations of generative models for cyber security Perfect for researchers, students, and experts in the fields of computer science and engineering, Game Theory and Machine Learning for Cyber Security is also an indispensable resource for industry professionals, military personnel, researchers, faculty, and students with an interest in cyber security.
Book Synopsis Big Data, Machine Learning, and Applications by : Malaya Dutta Borah
Download or read book Big Data, Machine Learning, and Applications written by Malaya Dutta Borah and published by Springer Nature. This book was released on 2024-01-06 with total page 758 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes refereed proceedings of the Second International Conference on Big Data, Machine Learning, and Applications, BigDML 2021. The volume focuses on topics such as computing methodology; machine learning; artificial intelligence; information systems; security and privacy. This volume will benefit research scholars, academicians, and industrial people who work on data storage and machine learning.
Book Synopsis Game Theory and Machine Learning for Cyber Security by : Charles A. Kamhoua
Download or read book Game Theory and Machine Learning for Cyber Security written by Charles A. Kamhoua and published by John Wiley & Sons. This book was released on 2021-09-08 with total page 546 pages. Available in PDF, EPUB and Kindle. Book excerpt: GAME THEORY AND MACHINE LEARNING FOR CYBER SECURITY Move beyond the foundations of machine learning and game theory in cyber security to the latest research in this cutting-edge field In Game Theory and Machine Learning for Cyber Security, a team of expert security researchers delivers a collection of central research contributions from both machine learning and game theory applicable to cybersecurity. The distinguished editors have included resources that address open research questions in game theory and machine learning applied to cyber security systems and examine the strengths and limitations of current game theoretic models for cyber security. Readers will explore the vulnerabilities of traditional machine learning algorithms and how they can be mitigated in an adversarial machine learning approach. The book offers a comprehensive suite of solutions to a broad range of technical issues in applying game theory and machine learning to solve cyber security challenges. Beginning with an introduction to foundational concepts in game theory, machine learning, cyber security, and cyber deception, the editors provide readers with resources that discuss the latest in hypergames, behavioral game theory, adversarial machine learning, generative adversarial networks, and multi-agent reinforcement learning. Readers will also enjoy: A thorough introduction to game theory for cyber deception, including scalable algorithms for identifying stealthy attackers in a game theoretic framework, honeypot allocation over attack graphs, and behavioral games for cyber deception An exploration of game theory for cyber security, including actionable game-theoretic adversarial intervention detection against advanced persistent threats Practical discussions of adversarial machine learning for cyber security, including adversarial machine learning in 5G security and machine learning-driven fault injection in cyber-physical systems In-depth examinations of generative models for cyber security Perfect for researchers, students, and experts in the fields of computer science and engineering, Game Theory and Machine Learning for Cyber Security is also an indispensable resource for industry professionals, military personnel, researchers, faculty, and students with an interest in cyber security.
Book Synopsis Artificial Intelligence for Cloud and Edge Computing by : Sanjay Misra
Download or read book Artificial Intelligence for Cloud and Edge Computing written by Sanjay Misra and published by Springer Nature. This book was released on 2022-01-13 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses the future possibilities of AI with cloud computing and edge computing. The main goal of this book is to conduct analyses, implementation and discussion of many tools (of artificial intelligence, machine learning and deep learning and cloud computing, fog computing, and edge computing including concepts of cyber security) for understanding integration of these technologies. With this book, readers can quickly get an overview of these emerging topics and get many ideas of the future of AI with cloud, edge, and in many other areas. Topics include machine and deep learning techniques for Internet of Things based cloud systems; security, privacy and trust issues in AI based cloud and IoT based cloud systems; AI for smart data storage in cloud-based IoT; blockchain based solutions for AI based cloud and IoT based cloud systems.This book is relevent to researchers, academics, students, and professionals.
Book Synopsis The 8th International Conference on Advanced Machine Learning and Technologies and Applications (AMLTA2022) by : Aboul Ella Hassanien
Download or read book The 8th International Conference on Advanced Machine Learning and Technologies and Applications (AMLTA2022) written by Aboul Ella Hassanien and published by Springer Nature. This book was released on 2022-04-16 with total page 708 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 8th International Conference on Advanced Machine Learning Technologies and Applications, AMLTA 2022, held in Cairo, Egypt, during May 5-7, 2022. The 8th edition of AMLTA will be organized by the Scientific Research Group in Egypt (SRGE), Egypt, collaborating with Port Said University, Egypt, and VSB-Technical University of Ostrava, Czech Republic. AMLTA series aims to become the premier international conference for an in-depth discussion on the most up-to-date and innovative ideas, research projects, and practices in the field of machine learning technologies and their applications. The book covers current research on advanced machine learning technology, including deep learning technology, sentiment analysis, cyber-physical system, IoT, and smart cities informatics and AI against COVID-19, data mining, power and control systems, business intelligence, social media, digital transformation, and smart systems.
Book Synopsis Computational Intelligence in Security for Information Systems by : Álvaro Herrero
Download or read book Computational Intelligence in Security for Information Systems written by Álvaro Herrero and published by Springer. This book was released on 2011-05-31 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 4th International Conference on Computational Intelligence in Security for Information Systems, CISIS 2011, held in Torremolinos-Málaga, in June 2011 as a satellite event of IWANN 2011, the International Work-conference on Artificial and Natural Neural Networks. The 38 revised full papers presented were carefully reviewed and selected from a total of 70 submissions. The papers are organized in topical sections on machine learning and intelligence, network security, cryptography, securing software, and applications of intelligent methods for security.
Book Synopsis Hands-On Deep Learning for IoT by : Md. Rezaul Karim
Download or read book Hands-On Deep Learning for IoT written by Md. Rezaul Karim and published by Packt Publishing Ltd. This book was released on 2019-06-27 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: Implement popular deep learning techniques to make your IoT applications smarter Key FeaturesUnderstand how deep learning facilitates fast and accurate analytics in IoTBuild intelligent voice and speech recognition apps in TensorFlow and ChainerAnalyze IoT data for making automated decisions and efficient predictionsBook Description Artificial Intelligence is growing quickly, which is driven by advancements in neural networks(NN) and deep learning (DL). With an increase in investments in smart cities, smart healthcare, and industrial Internet of Things (IoT), commercialization of IoT will soon be at peak in which massive amounts of data generated by IoT devices need to be processed at scale. Hands-On Deep Learning for IoT will provide deeper insights into IoT data, which will start by introducing how DL fits into the context of making IoT applications smarter. It then covers how to build deep architectures using TensorFlow, Keras, and Chainer for IoT. You’ll learn how to train convolutional neural networks(CNN) to develop applications for image-based road faults detection and smart garbage separation, followed by implementing voice-initiated smart light control and home access mechanisms powered by recurrent neural networks(RNN). You’ll master IoT applications for indoor localization, predictive maintenance, and locating equipment in a large hospital using autoencoders, DeepFi, and LSTM networks. Furthermore, you’ll learn IoT application development for healthcare with IoT security enhanced. By the end of this book, you will have sufficient knowledge need to use deep learning efficiently to power your IoT-based applications for smarter decision making. What you will learnGet acquainted with different neural network architectures and their suitability in IoTUnderstand how deep learning can improve the predictive power in your IoT solutionsCapture and process streaming data for predictive maintenanceSelect optimal frameworks for image recognition and indoor localizationAnalyze voice data for speech recognition in IoT applicationsDevelop deep learning-based IoT solutions for healthcareEnhance security in your IoT solutionsVisualize analyzed data to uncover insights and perform accurate predictionsWho this book is for If you’re an IoT developer, data scientist, or deep learning enthusiast who wants to apply deep learning techniques to build smart IoT applications, this book is for you. Familiarity with machine learning, a basic understanding of the IoT concepts, and some experience in Python programming will help you get the most out of this book.
