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

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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 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.

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

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Publisher :
ISBN 13 : 9781799804499
Total Pages : pages
Book Rating : 4.8/5 (44 download)

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

Download or read book Handbook of Research on Machine and Deep Learning Applications for Cyber Security written by and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Deep Learning Applications for Cyber Security

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Author :
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.

Machine Learning and Cognitive Science Applications in Cyber Security

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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.

Handbook of Research on Emerging Trends and Applications of Machine Learning

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Publisher : IGI Global
ISBN 13 : 1522596453
Total Pages : 674 pages
Book Rating : 4.5/5 (225 download)

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Book Synopsis Handbook of Research on Emerging Trends and Applications of Machine Learning by : Solanki, Arun

Download or read book Handbook of Research on Emerging Trends and Applications of Machine Learning written by Solanki, Arun and published by IGI Global. This book was released on 2019-12-13 with total page 674 pages. Available in PDF, EPUB and Kindle. Book excerpt: As today’s world continues to advance, Artificial Intelligence (AI) is a field that has become a staple of technological development and led to the advancement of numerous professional industries. An application within AI that has gained attention is machine learning. Machine learning uses statistical techniques and algorithms to give computer systems the ability to understand and its popularity has circulated through many trades. Understanding this technology and its countless implementations is pivotal for scientists and researchers across the world. The Handbook of Research on Emerging Trends and Applications of Machine Learning provides a high-level understanding of various machine learning algorithms along with modern tools and techniques using Artificial Intelligence. In addition, this book explores the critical role that machine learning plays in a variety of professional fields including healthcare, business, and computer science. While highlighting topics including image processing, predictive analytics, and smart grid management, this book is ideally designed for developers, data scientists, business analysts, information architects, finance agents, healthcare professionals, researchers, retail traders, professors, and graduate students seeking current research on the benefits, implementations, and trends of machine learning.

Artificial Intelligence for Cybersecurity

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Author :
Publisher : Springer Nature
ISBN 13 : 3030970876
Total Pages : 388 pages
Book Rating : 4.0/5 (39 download)

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Book Synopsis Artificial Intelligence for Cybersecurity by : Mark Stamp

Download or read book Artificial Intelligence for Cybersecurity written by Mark Stamp and published by Springer Nature. This book was released on 2022-07-15 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores new and novel applications of machine learning, deep learning, and artificial intelligence that are related to major challenges in the field of cybersecurity. The provided research goes beyond simply applying AI techniques to datasets and instead delves into deeper issues that arise at the interface between deep learning and cybersecurity. This book also provides insight into the difficult "how" and "why" questions that arise in AI within the security domain. For example, this book includes chapters covering "explainable AI", "adversarial learning", "resilient AI", and a wide variety of related topics. It’s not limited to any specific cybersecurity subtopics and the chapters touch upon a wide range of cybersecurity domains, ranging from malware to biometrics and more. Researchers and advanced level students working and studying in the fields of cybersecurity (equivalently, information security) or artificial intelligence (including deep learning, machine learning, big data, and related fields) will want to purchase this book as a reference. Practitioners working within these fields will also be interested in purchasing this book.

Examining the Impact of Deep Learning and IoT on Multi-Industry Applications

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Publisher : IGI Global
ISBN 13 : 1799875172
Total Pages : 304 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Examining the Impact of Deep Learning and IoT on Multi-Industry Applications by : Raut, Roshani

Download or read book Examining the Impact of Deep Learning and IoT on Multi-Industry Applications written by Raut, Roshani and published by IGI Global. This book was released on 2021-01-29 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep learning, as a recent AI technique, has proven itself efficient in solving many real-world problems. Deep learning algorithms are efficient, high performing, and an effective standard for solving these problems. In addition, with IoT, deep learning is in many emerging and developing domains of computer technology. Deep learning algorithms have brought a revolution in computer vision applications by introducing an efficient solution to several image processing-related problems that have long remained unresolved or moderately solved. Various significant IoT technologies in various industries, such as education, health, transportation, and security, combine IoT with deep learning for complex problem solving and the supported interaction between human beings and their surroundings. Examining the Impact of Deep Learning and IoT on Multi-Industry Applications provides insights on how deep learning, together with IoT, impacts various sectors such as healthcare, agriculture, cyber security, and social media analysis applications. The chapters present solutions to various real-world problems using these methods from various researchers’ points of view. While highlighting topics such as medical diagnosis, power consumption, livestock management, security, and social media analysis, this book is ideal for IT specialists, technologists, security analysts, medical practitioners, imaging specialists, diagnosticians, academicians, researchers, industrial experts, scientists, and undergraduate and postgraduate students who are working in the field of computer engineering, electronics, and electrical engineering.

Confluence of AI, Machine, and Deep Learning in Cyber Forensics

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Publisher : IGI Global
ISBN 13 : 1799849015
Total Pages : 248 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Confluence of AI, Machine, and Deep Learning in Cyber Forensics by : Misra, Sanjay

Download or read book Confluence of AI, Machine, and Deep Learning in Cyber Forensics written by Misra, Sanjay and published by IGI Global. This book was released on 2020-12-18 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: Developing a knowledge model helps to formalize the difficult task of analyzing crime incidents in addition to preserving and presenting the digital evidence for legal processing. The use of data analytics techniques to collect evidence assists forensic investigators in following the standard set of forensic procedures, techniques, and methods used for evidence collection and extraction. Varieties of data sources and information can be uniquely identified, physically isolated from the crime scene, protected, stored, and transmitted for investigation using AI techniques. With such large volumes of forensic data being processed, different deep learning techniques may be employed. Confluence of AI, Machine, and Deep Learning in Cyber Forensics contains cutting-edge research on the latest AI techniques being used to design and build solutions that address prevailing issues in cyber forensics and that will support efficient and effective investigations. This book seeks to understand the value of the deep learning algorithm to handle evidence data as well as the usage of neural networks to analyze investigation data. Other themes that are explored include machine learning algorithms that allow machines to interact with the evidence, deep learning algorithms that can handle evidence acquisition and preservation, and techniques in both fields that allow for the analysis of huge amounts of data collected during a forensic investigation. This book is ideally intended for forensics experts, forensic investigators, cyber forensic practitioners, researchers, academicians, and students interested in cyber forensics, computer science and engineering, information technology, and electronics and communication.

Cyber Security Meets Machine Learning

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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 Multimedia Cyber Security

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Publisher : IGI Global
ISBN 13 : 179982702X
Total Pages : 372 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Handbook of Research on Multimedia Cyber Security by : Gupta, Brij B.

Download or read book Handbook of Research on Multimedia Cyber Security written by Gupta, Brij B. and published by IGI Global. This book was released on 2020-04-03 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: Because it makes the distribution and transmission of digital information much easier and more cost effective, multimedia has emerged as a top resource in the modern era. In spite of the opportunities that multimedia creates for businesses and companies, information sharing remains vulnerable to cyber attacks and hacking due to the open channels in which this data is being transmitted. Protecting the authenticity and confidentiality of information is a top priority for all professional fields that currently use multimedia practices for distributing digital data. The Handbook of Research on Multimedia Cyber Security provides emerging research exploring the theoretical and practical aspects of current security practices and techniques within multimedia information and assessing modern challenges. Featuring coverage on a broad range of topics such as cryptographic protocols, feature extraction, and chaotic systems, this book is ideally designed for scientists, researchers, developers, security analysts, network administrators, scholars, IT professionals, educators, and students seeking current research on developing strategies in multimedia security.

Machine Learning and Security

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Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491979852
Total Pages : 394 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 394 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 and Security

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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

Deep Learning Applications for Cyber-Physical Systems

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Publisher : IGI Global
ISBN 13 : 1799881636
Total Pages : 293 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Deep Learning Applications for Cyber-Physical Systems by : Mundada, Monica R.

Download or read book Deep Learning Applications for Cyber-Physical Systems written by Mundada, Monica R. and published by IGI Global. This book was released on 2021-12-17 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big data generates around us constantly from daily business, custom use, engineering, and science activities. Sensory data is collected from the internet of things (IoT) and cyber-physical systems (CPS). Merely storing such a massive amount of data is meaningless, as the key point is to identify, locate, and extract valuable knowledge from big data to forecast and support services. Such extracted valuable knowledge is usually referred to as smart data. It is vital to providing suitable decisions in business, science, and engineering applications. Deep Learning Applications for Cyber-Physical Systems provides researchers a platform to present state-of-the-art innovations, research, and designs while implementing methodological and algorithmic solutions to data processing problems and designing and analyzing evolving trends in health informatics and computer-aided diagnosis in deep learning techniques in context with cyber physical systems. Covering topics such as smart medical systems, intrusion detection systems, and predictive analytics, this text is essential for computer scientists, engineers, practitioners, researchers, students, and academicians, especially those interested in the areas of internet of things, machine learning, deep learning, and cyber-physical systems.

Research Anthology on Artificial Intelligence Applications in Security

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Publisher : IGI Global
ISBN 13 : 1799877485
Total Pages : 2253 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Research Anthology on Artificial Intelligence Applications in Security by : Management Association, Information Resources

Download or read book Research Anthology on Artificial Intelligence Applications in Security written by Management Association, Information Resources and published by IGI Global. This book was released on 2020-11-27 with total page 2253 pages. Available in PDF, EPUB and Kindle. Book excerpt: As industries are rapidly being digitalized and information is being more heavily stored and transmitted online, the security of information has become a top priority in securing the use of online networks as a safe and effective platform. With the vast and diverse potential of artificial intelligence (AI) applications, it has become easier than ever to identify cyber vulnerabilities, potential threats, and the identification of solutions to these unique problems. The latest tools and technologies for AI applications have untapped potential that conventional systems and human security systems cannot meet, leading AI to be a frontrunner in the fight against malware, cyber-attacks, and various security issues. However, even with the tremendous progress AI has made within the sphere of security, it’s important to understand the impacts, implications, and critical issues and challenges of AI applications along with the many benefits and emerging trends in this essential field of security-based research. Research Anthology on Artificial Intelligence Applications in Security seeks to address the fundamental advancements and technologies being used in AI applications for the security of digital data and information. The included chapters cover a wide range of topics related to AI in security stemming from the development and design of these applications, the latest tools and technologies, as well as the utilization of AI and what challenges and impacts have been discovered along the way. This resource work is a critical exploration of the latest research on security and an overview of how AI has impacted the field and will continue to advance as an essential tool for security, safety, and privacy online. This book is ideally intended for cyber security analysts, computer engineers, IT specialists, practitioners, stakeholders, researchers, academicians, and students interested in AI applications in the realm of security research.

Hands-On Machine Learning for Cybersecurity

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Publisher : Packt Publishing Ltd
ISBN 13 : 178899096X
Total Pages : 306 pages
Book Rating : 4.7/5 (889 download)

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Book Synopsis Hands-On Machine Learning for Cybersecurity by : Soma Halder

Download or read book Hands-On Machine Learning for Cybersecurity written by Soma Halder and published by Packt Publishing Ltd. This book was released on 2018-12-31 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get into the world of smart data security using machine learning algorithms and Python libraries Key FeaturesLearn machine learning algorithms and cybersecurity fundamentalsAutomate your daily workflow by applying use cases to many facets of securityImplement smart machine learning solutions to detect various cybersecurity problemsBook Description Cyber threats today are one of the costliest losses that an organization can face. In this book, we use the most efficient tool to solve the big problems that exist in the cybersecurity domain. The book begins by giving you the basics of ML in cybersecurity using Python and its libraries. You will explore various ML domains (such as time series analysis and ensemble modeling) to get your foundations right. You will implement various examples such as building system to identify malicious URLs, and building a program to detect fraudulent emails and spam. Later, you will learn how to make effective use of K-means algorithm to develop a solution to detect and alert you to any malicious activity in the network. Also learn how to implement biometrics and fingerprint to validate whether the user is a legitimate user or not. Finally, you will see how we change the game with TensorFlow and learn how deep learning is effective for creating models and training systems What you will learnUse machine learning algorithms with complex datasets to implement cybersecurity conceptsImplement machine learning algorithms such as clustering, k-means, and Naive Bayes to solve real-world problemsLearn to speed up a system using Python libraries with NumPy, Scikit-learn, and CUDAUnderstand how to combat malware, detect spam, and fight financial fraud to mitigate cyber crimesUse TensorFlow in the cybersecurity domain and implement real-world examplesLearn how machine learning and Python can be used in complex cyber issuesWho this book is for This book is for the data scientists, machine learning developers, security researchers, and anyone keen to apply machine learning to up-skill computer security. Having some working knowledge of Python and being familiar with the basics of machine learning and cybersecurity fundamentals will help to get the most out of the book

Handbook of Research on Machine Learning Techniques for Pattern Recognition and Information Security

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Author :
Publisher : IGI Global
ISBN 13 : 1799833011
Total Pages : 355 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Handbook of Research on Machine Learning Techniques for Pattern Recognition and Information Security by : Dua, Mohit

Download or read book Handbook of Research on Machine Learning Techniques for Pattern Recognition and Information Security written by Dua, Mohit and published by IGI Global. This book was released on 2021-05-14 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: The artificial intelligence subset machine learning has become a popular technique in professional fields as many are finding new ways to apply this trending technology into their everyday practices. Two fields that have majorly benefited from this are pattern recognition and information security. The ability of these intelligent algorithms to learn complex patterns from data and attain new performance techniques has created a wide variety of uses and applications within the data security industry. There is a need for research on the specific uses machine learning methods have within these fields, along with future perspectives. The Handbook of Research on Machine Learning Techniques for Pattern Recognition and Information Security is a collection of innovative research on the current impact of machine learning methods within data security as well as its various applications and newfound challenges. While highlighting topics including anomaly detection systems, biometrics, and intrusion management, this book is ideally designed for industrial experts, researchers, IT professionals, network developers, policymakers, computer scientists, educators, and students seeking current research on implementing machine learning tactics to enhance the performance of information security.

Network Intrusion Detection using Deep Learning

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Author :
Publisher : Springer
ISBN 13 : 9811314446
Total Pages : 92 pages
Book Rating : 4.8/5 (113 download)

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Book Synopsis Network Intrusion Detection using Deep Learning by : Kwangjo Kim

Download or read book Network Intrusion Detection using Deep Learning written by Kwangjo Kim and published by Springer. This book was released on 2018-09-25 with total page 92 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents recent advances in intrusion detection systems (IDSs) using state-of-the-art deep learning methods. It also provides a systematic overview of classical machine learning and the latest developments in deep learning. In particular, it discusses deep learning applications in IDSs in different classes: generative, discriminative, and adversarial networks. Moreover, it compares various deep learning-based IDSs based on benchmarking datasets. The book also proposes two novel feature learning models: deep feature extraction and selection (D-FES) and fully unsupervised IDS. Further challenges and research directions are presented at the end of the book. Offering a comprehensive overview of deep learning-based IDS, the book is a valuable reerence resource for undergraduate and graduate students, as well as researchers and practitioners interested in deep learning and intrusion detection. Further, the comparison of various deep-learning applications helps readers gain a basic understanding of machine learning, and inspires applications in IDS and other related areas in cybersecurity.