Introduction To Machine Learning With Applications In Information Security

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Introduction to Machine Learning with Applications in Information Security

Author : Mark Stamp
Publisher : CRC Press
ISBN 13 : 1351818074
Total Pages : 346 pages
Book Rating : 4.3/5 (518 download)

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Book Synopsis Introduction to Machine Learning with Applications in Information Security by : Mark Stamp

Download or read book Introduction to Machine Learning with Applications in Information Security written by Mark Stamp and published by CRC Press. This book was released on 2017-09-22 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to Machine Learning with Applications in Information Security provides a class-tested introduction to a wide variety of machine learning algorithms, reinforced through realistic applications. The book is accessible and doesn’t prove theorems, or otherwise dwell on mathematical theory. The goal is to present topics at an intuitive level, with just enough detail to clarify the underlying concepts. The book covers core machine learning topics in-depth, including Hidden Markov Models, Principal Component Analysis, Support Vector Machines, and Clustering. It also includes coverage of Nearest Neighbors, Neural Networks, Boosting and AdaBoost, Random Forests, Linear Discriminant Analysis, Vector Quantization, Naive Bayes, Regression Analysis, Conditional Random Fields, and Data Analysis. Most of the examples in the book are drawn from the field of information security, with many of the machine learning applications specifically focused on malware. The applications presented are designed to demystify machine learning techniques by providing straightforward scenarios. Many of the exercises in this book require some programming, and basic computing concepts are assumed in a few of the application sections. However, anyone with a modest amount of programming experience should have no trouble with this aspect of the book. Instructor resources, including PowerPoint slides, lecture videos, and other relevant material are provided on an accompanying website: http://www.cs.sjsu.edu/~stamp/ML/. For the reader’s benefit, the figures in the book are also available in electronic form, and in color. About the Author Mark Stamp has been a Professor of Computer Science at San Jose State University since 2002. Prior to that, he worked at the National Security Agency (NSA) for seven years, and a Silicon Valley startup company for two years. He received his Ph.D. from Texas Tech University in 1992. His love affair with machine learning began in the early 1990s, when he was working at the NSA, and continues today at SJSU, where he has supervised vast numbers of master’s student projects, most of which involve a combination of information security and machine learning.

Introduction to Machine Learning with Applications in Information Security

Author : Mark Stamp
Publisher : CRC Press
ISBN 13 : 1000626261
Total Pages : 498 pages
Book Rating : 4.0/5 (6 download)

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Book Synopsis Introduction to Machine Learning with Applications in Information Security by : Mark Stamp

Download or read book Introduction to Machine Learning with Applications in Information Security written by Mark Stamp and published by CRC Press. This book was released on 2022-09-27 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to Machine Learning with Applications in Information Security, Second Edition provides a classroom-tested introduction to a wide variety of machine learning and deep learning algorithms and techniques, reinforced via realistic applications. The book is accessible and doesn’t prove theorems, or dwell on mathematical theory. The goal is to present topics at an intuitive level, with just enough detail to clarify the underlying concepts. The book covers core classic machine learning topics in depth, including Hidden Markov Models (HMM), Support Vector Machines (SVM), and clustering. Additional machine learning topics include k-Nearest Neighbor (k-NN), boosting, Random Forests, and Linear Discriminant Analysis (LDA). The fundamental deep learning topics of backpropagation, Convolutional Neural Networks (CNN), Multilayer Perceptrons (MLP), and Recurrent Neural Networks (RNN) are covered in depth. A broad range of advanced deep learning architectures are also presented, including Long Short-Term Memory (LSTM), Generative Adversarial Networks (GAN), Extreme Learning Machines (ELM), Residual Networks (ResNet), Deep Belief Networks (DBN), Bidirectional Encoder Representations from Transformers (BERT), and Word2Vec. Finally, several cutting-edge deep learning topics are discussed, including dropout regularization, attention, explainability, and adversarial attacks. Most of the examples in the book are drawn from the field of information security, with many of the machine learning and deep learning applications focused on malware. The applications presented serve to demystify the topics by illustrating the use of various learning techniques in straightforward scenarios. Some of the exercises in this book require programming, and elementary computing concepts are assumed in a few of the application sections. However, anyone with a modest amount of computing experience should have no trouble with this aspect of the book. Instructor resources, including PowerPoint slides, lecture videos, and other relevant material are provided on an accompanying website: http://www.cs.sjsu.edu/~stamp/ML/.

Machine Learning and Security

Author : Clarence Chio
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491979879
Total Pages : 385 pages
Book Rating : 4.4/5 (919 download)

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Book Synopsis Machine Learning and Security by : Clarence Chio

Download or read book Machine Learning and Security written by Clarence Chio and published by "O'Reilly Media, Inc.". This book was released on 2018-01-26 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: Can machine learning techniques solve our computer security problems and finally put an end to the cat-and-mouse game between attackers and defenders? Or is this hope merely hype? Now you can dive into the science and answer this question for yourself. With this practical guide, you’ll explore ways to apply machine learning to security issues such as intrusion detection, malware classification, and network analysis. Machine learning and security specialists Clarence Chio and David Freeman provide a framework for discussing the marriage of these two fields, as well as a toolkit of machine-learning algorithms that you can apply to an array of security problems. This book is ideal for security engineers and data scientists alike. Learn how machine learning has contributed to the success of modern spam filters Quickly detect anomalies, including breaches, fraud, and impending system failure Conduct malware analysis by extracting useful information from computer binaries Uncover attackers within the network by finding patterns inside datasets Examine how attackers exploit consumer-facing websites and app functionality Translate your machine learning algorithms from the lab to production Understand the threat attackers pose to machine learning solutions

Machine Learning for Cyber Security

Author : Preeti Malik
Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 3110766744
Total Pages : 160 pages
Book Rating : 4.1/5 (17 download)

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Book Synopsis Machine Learning for Cyber Security by : Preeti Malik

Download or read book Machine Learning for Cyber Security written by Preeti Malik and published by Walter de Gruyter GmbH & Co KG. This book was released on 2022-12-05 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book shows how machine learning (ML) methods can be used to enhance cyber security operations, including detection, modeling, monitoring as well as defense against threats to sensitive data and security systems. Filling an important gap between ML and cyber security communities, it discusses topics covering a wide range of modern and practical ML techniques, frameworks and tools.

Cyber Security Meets Machine Learning

Author : Xiaofeng Chen
Publisher : Springer Nature
ISBN 13 : 9813367261
Total Pages : 168 pages
Book Rating : 4.8/5 (133 download)

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Book Synopsis Cyber Security Meets Machine Learning by : Xiaofeng Chen

Download or read book Cyber Security Meets Machine Learning written by Xiaofeng Chen and published by Springer Nature. This book was released on 2021-07-02 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning boosts the capabilities of security solutions in the modern cyber environment. However, there are also security concerns associated with machine learning models and approaches: the vulnerability of machine learning models to adversarial attacks is a fatal flaw in the artificial intelligence technologies, and the privacy of the data used in the training and testing periods is also causing increasing concern among users. This book reviews the latest research in the area, including effective applications of machine learning methods in cybersecurity solutions and the urgent security risks related to the machine learning models. The book is divided into three parts: Cyber Security Based on Machine Learning; Security in Machine Learning Methods and Systems; and Security and Privacy in Outsourced Machine Learning. Addressing hot topics in cybersecurity and written by leading researchers in the field, the book features self-contained chapters to allow readers to select topics that are relevant to their needs. It is a valuable resource for all those interested in cybersecurity and robust machine learning, including graduate students and academic and industrial researchers, wanting to gain insights into cutting-edge research topics, as well as related tools and inspiring innovations.

Handbook of Research on Machine and Deep Learning Applications for Cyber Security

Author : Ganapathi, Padmavathi
Publisher : IGI Global
ISBN 13 : 1522596135
Total Pages : 482 pages
Book Rating : 4.5/5 (225 download)

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Book Synopsis Handbook of Research on Machine and Deep Learning Applications for Cyber Security by : Ganapathi, Padmavathi

Download or read book Handbook of Research on Machine and Deep Learning Applications for Cyber Security written by Ganapathi, Padmavathi and published by IGI Global. This book was released on 2019-07-26 with total page 482 pages. Available in PDF, EPUB and Kindle. Book excerpt: As the advancement of technology continues, cyber security continues to play a significant role in todays 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.

Machine Learning and Cognitive Science Applications in Cyber Security

Author : Khan, Muhammad Salman
Publisher : IGI Global
ISBN 13 : 1522581014
Total Pages : 321 pages
Book Rating : 4.5/5 (225 download)

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Book Synopsis Machine Learning and Cognitive Science Applications in Cyber Security by : Khan, Muhammad Salman

Download or read book Machine Learning and Cognitive Science Applications in Cyber Security written by Khan, Muhammad Salman and published by IGI Global. This book was released on 2019-05-15 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the past few years, with the evolution of advanced persistent threats and mutation techniques, sensitive and damaging information from a variety of sources have been exposed to possible corruption and hacking. Machine learning, artificial intelligence, predictive analytics, and similar disciplines of cognitive science applications have been found to have significant applications in the domain of cyber security. Machine Learning and Cognitive Science Applications in Cyber Security examines different applications of cognition that can be used to detect threats and analyze data to capture malware. Highlighting such topics as anomaly detection, intelligent platforms, and triangle scheme, this publication is designed for IT specialists, computer engineers, researchers, academicians, and industry professionals interested in the impact of machine learning in cyber security and the methodologies that can help improve the performance and reliability of machine learning applications.

Machine Learning for Computer and Cyber Security

Author : Brij B. Gupta
Publisher : CRC Press
ISBN 13 : 0429995725
Total Pages : 352 pages
Book Rating : 4.4/5 (299 download)

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Book Synopsis Machine Learning for Computer and Cyber Security by : Brij B. Gupta

Download or read book Machine Learning for Computer and Cyber Security written by Brij B. Gupta and published by CRC Press. This book was released on 2019-02-05 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: While Computer Security is a broader term which incorporates technologies, protocols, standards and policies to ensure the security of the computing systems including the computer hardware, software and the information stored in it, Cyber Security is a specific, growing field to protect computer networks (offline and online) from unauthorized access, botnets, phishing scams, etc. Machine learning is a branch of Computer Science which enables computing machines to adopt new behaviors on the basis of observable and verifiable data and information. It can be applied to ensure the security of the computers and the information by detecting anomalies using data mining and other such techniques. This book will be an invaluable resource to understand the importance of machine learning and data mining in establishing computer and cyber security. It emphasizes important security aspects associated with computer and cyber security along with the analysis of machine learning and data mining based solutions. The book also highlights the future research domains in which these solutions can be applied. Furthermore, it caters to the needs of IT professionals, researchers, faculty members, scientists, graduate students, research scholars and software developers who seek to carry out research and develop combating solutions in the area of cyber security using machine learning based approaches. It is an extensive source of information for the readers belonging to the field of Computer Science and Engineering, and Cyber Security professionals. Key Features: This book contains examples and illustrations to demonstrate the principles, algorithms, challenges and applications of machine learning and data mining for computer and cyber security. It showcases important security aspects and current trends in the field. It provides an insight of the future research directions in the field. Contents of this book help to prepare the students for exercising better defense in terms of understanding the motivation of the attackers and how to deal with and mitigate the situation using machine learning based approaches in better manner.

Deep Learning Applications for Cyber Security

Author : Mamoun Alazab
Publisher : Springer
ISBN 13 : 3030130576
Total Pages : 246 pages
Book Rating : 4.0/5 (31 download)

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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 246 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.

AI, Machine Learning and Deep Learning

Author : Fei Hu
Publisher : CRC Press
ISBN 13 : 1000878872
Total Pages : 347 pages
Book Rating : 4.0/5 (8 download)

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Book Synopsis AI, Machine Learning and Deep Learning by : Fei Hu

Download or read book AI, Machine Learning and Deep Learning written by Fei Hu and published by CRC Press. This book was released on 2023-06-05 with total page 347 pages. Available in PDF, EPUB and Kindle. Book excerpt: Today, Artificial Intelligence (AI) and Machine Learning/ Deep Learning (ML/DL) have become the hottest areas in information technology. In our society, many intelligent devices rely on AI/ML/DL algorithms/tools for smart operations. Although AI/ML/DL algorithms and tools have been used in many internet applications and electronic devices, they are also vulnerable to various attacks and threats. AI parameters may be distorted by the internal attacker; the DL input samples may be polluted by adversaries; the ML model may be misled by changing the classification boundary, among many other attacks and threats. Such attacks can make AI products dangerous to use. While this discussion focuses on security issues in AI/ML/DL-based systems (i.e., securing the intelligent systems themselves), AI/ML/DL models and algorithms can actually also be used for cyber security (i.e., the use of AI to achieve security). Since AI/ML/DL security is a newly emergent field, many researchers and industry professionals cannot yet obtain a detailed, comprehensive understanding of this area. This book aims to provide a complete picture of the challenges and solutions to related security issues in various applications. It explains how different attacks can occur in advanced AI tools and the challenges of overcoming those attacks. Then, the book describes many sets of promising solutions to achieve AI security and privacy. The features of this book have seven aspects: This is the first book to explain various practical attacks and countermeasures to AI systems Both quantitative math models and practical security implementations are provided It covers both "securing the AI system itself" and "using AI to achieve security" It covers all the advanced AI attacks and threats with detailed attack models It provides multiple solution spaces to the security and privacy issues in AI tools The differences among ML and DL security and privacy issues are explained Many practical security applications are covered

Game Theory and Machine Learning for Cyber Security

Author : Charles A. Kamhoua
Publisher : John Wiley & Sons
ISBN 13 : 1119723922
Total Pages : 546 pages
Book Rating : 4.1/5 (197 download)

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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.

Mastering Machine Learning

Author : Cybellium Ltd
Publisher : Cybellium Ltd
ISBN 13 :
Total Pages : 335 pages
Book Rating : 4.8/5 (549 download)

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Book Synopsis Mastering Machine Learning by : Cybellium Ltd

Download or read book Mastering Machine Learning written by Cybellium Ltd and published by Cybellium Ltd. This book was released on 2023-09-05 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: Are you ready to become a master of machine learning? In "Mastering Machine Learning" by Kris Hermans, you'll embark on a transformative journey that will empower you with the skills and knowledge needed to conquer the world of data-driven intelligence. Discover Cutting-Edge Techniques and Practical Applications From self-driving cars to personalized recommendations, machine learning is transforming industries and reshaping the way we live and work. In this comprehensive guide, Kris Hermans equips you with the tools to harness the power of machine learning. Dive into the core concepts, algorithms, and models that underpin this revolutionary field. Become a Proficient Practitioner Whether you're a beginner or an experienced professional, this book provides a clear and structured path to mastering machine learning. Through hands-on examples and real-world case studies, you'll gain practical expertise in implementing machine learning models and solving complex problems. Kris Hermans guides you through the process, ensuring you develop a deep understanding of the techniques and algorithms that drive intelligent systems. From Fundamentals to Advanced Topics "Mastering Machine Learning" covers the full spectrum of machine learning, starting with the foundations of supervised and unsupervised learning and progressing to reinforcement learning, neural networks, and deep learning. Explore diverse models and learn how to choose the right approach for different applications. With this knowledge, you'll be able to tackle real-world challenges with confidence. Unlock the Potential of Machine Learning Across Industries Discover how machine learning is revolutionizing industries such as finance, healthcare, e-commerce, and cybersecurity. Through captivating case studies, you'll witness the transformative impact of machine learning and gain insights into how organizations are leveraging this technology to drive innovation, improve decision-making, and achieve unprecedented success. Navigate Ethical Considerations As machine learning becomes increasingly powerful, it's crucial to consider the ethical implications. "Mastering Machine Learning" addresses these important considerations head-on. Learn about the ethical challenges and responsibilities associated with machine learning applications and gain the knowledge to make informed, ethical decisions in your own work.

Introduction to Machine Learning

Author : Ethem Alpaydin
Publisher : MIT Press
ISBN 13 : 0262028182
Total Pages : 639 pages
Book Rating : 4.2/5 (62 download)

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Book Synopsis Introduction to Machine Learning by : Ethem Alpaydin

Download or read book Introduction to Machine Learning written by Ethem Alpaydin and published by MIT Press. This book was released on 2014-08-22 with total page 639 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction -- Supervised learning -- Bayesian decision theory -- Parametric methods -- Multivariate methods -- Dimensionality reduction -- Clustering -- Nonparametric methods -- Decision trees -- Linear discrimination -- Multilayer perceptrons -- Local models -- Kernel machines -- Graphical models -- Brief contents -- Hidden markov models -- Bayesian estimation -- Combining multiple learners -- Reinforcement learning -- Design and analysis of machine learning experiments.

Machine Learning for Cyber Agents

Author : Stanislav Abaimov
Publisher : Springer Nature
ISBN 13 : 3030915859
Total Pages : 235 pages
Book Rating : 4.0/5 (39 download)

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Book Synopsis Machine Learning for Cyber Agents by : Stanislav Abaimov

Download or read book Machine Learning for Cyber Agents written by Stanislav Abaimov and published by Springer Nature. This book was released on 2022-01-27 with total page 235 pages. Available in PDF, EPUB and Kindle. Book excerpt: The cyber world has been both enhanced and endangered by AI. On the one hand, the performance of many existing security services has been improved, and new tools created. On the other, it entails new cyber threats both through evolved attacking capacities and through its own imperfections and vulnerabilities. Moreover, quantum computers are further pushing the boundaries of what is possible, by making machine learning cyber agents faster and smarter. With the abundance of often-confusing information and lack of trust in the diverse applications of AI-based technologies, it is essential to have a book that can explain, from a cyber security standpoint, why and at what stage the emerging, powerful technology of machine learning can and should be mistrusted, and how to benefit from it while avoiding potentially disastrous consequences. In addition, this book sheds light on another highly sensitive area – the application of machine learning for offensive purposes, an aspect that is widely misunderstood, under-represented in the academic literature and requires immediate expert attention.

Artificial Intelligence in Cyber Security: Theories and Applications

Author : Tushar Bhardwaj
Publisher : Springer Nature
ISBN 13 : 3031285816
Total Pages : 144 pages
Book Rating : 4.0/5 (312 download)

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Book Synopsis Artificial Intelligence in Cyber Security: Theories and Applications by : Tushar Bhardwaj

Download or read book Artificial Intelligence in Cyber Security: Theories and Applications written by Tushar Bhardwaj and published by Springer Nature. This book was released on 2023-11-10 with total page 144 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights the applications and theory of artificial intelligence in the domain of cybersecurity. The book proposes new approaches and ideas to present applications of innovative approaches in real-time environments. In the past few decades, there has been an exponential rise in the application of artificial intelligence technologies (such as deep learning, machine learning, blockchain) for solving complex and intricate problems arising in the domain of cybersecurity. The versatility of these techniques has made them a favorite among scientists and researchers working in diverse areas. This book serves as a reference for young scholars, researchers, and industry professionals working in the field of Artificial Intelligence and Cybersecurity.

Machine Learning for Cybersecurity

Author : Marwan Omar
Publisher : Springer Nature
ISBN 13 : 3031158938
Total Pages : 54 pages
Book Rating : 4.0/5 (311 download)

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Book Synopsis Machine Learning for Cybersecurity by : Marwan Omar

Download or read book Machine Learning for Cybersecurity written by Marwan Omar and published by Springer Nature. This book was released on 2022-09-24 with total page 54 pages. Available in PDF, EPUB and Kindle. Book excerpt: This SpringerBrief presents the underlying principles of machine learning and how to deploy various deep learning tools and techniques to tackle and solve certain challenges facing the cybersecurity industry. By implementing innovative deep learning solutions, cybersecurity researchers, students and practitioners can analyze patterns and learn how to prevent cyber-attacks and respond to changing malware behavior. The knowledge and tools introduced in this brief can also assist cybersecurity teams to become more proactive in preventing threats and responding to active attacks in real time. It can reduce the amount of time spent on routine tasks and enable organizations to use their resources more strategically. In short, the knowledge and techniques provided in this brief can help make cybersecurity simpler, more proactive, less expensive and far more effective Advanced-level students in computer science studying machine learning with a cybersecurity focus will find this SpringerBrief useful as a study guide. Researchers and cybersecurity professionals focusing on the application of machine learning tools and techniques to the cybersecurity domain will also want to purchase this SpringerBrief.

Applications of Machine Learning and Deep Learning for Privacy and Cybersecurity

Author : Anacleto Correia
Publisher : Information Science Reference
ISBN 13 : 9781799894308
Total Pages : 0 pages
Book Rating : 4.8/5 (943 download)

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Book Synopsis Applications of Machine Learning and Deep Learning for Privacy and Cybersecurity by : Anacleto Correia

Download or read book Applications of Machine Learning and Deep Learning for Privacy and Cybersecurity written by Anacleto Correia and published by Information Science Reference. This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This comprehensive and timely book provides an overview of the field of Machine and Deep Learning in the areas of cybersecurity and privacy, followed by an in-depth view of emerging research exploring the theoretical aspects of machine and deep learning, as well as real-world implementations"--