[PDF] Machine Learning And Cryptographic Solutions For Data Protection And Network Security eBook

Author : Ruth, J. Anitha
Publisher : IGI Global
Page : 557 pages
File Size : 49,41 MB
Release : 2024-05-31
Category : Computers
ISBN :

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In the relentless battle against escalating cyber threats, data security faces a critical challenge – the need for innovative solutions to fortify encryption and decryption processes. The increasing frequency and complexity of cyber-attacks demand a dynamic approach, and this is where the intersection of cryptography and machine learning emerges as a powerful ally. As hackers become more adept at exploiting vulnerabilities, the book stands as a beacon of insight, addressing the urgent need to leverage machine learning techniques in cryptography. Machine Learning and Cryptographic Solutions for Data Protection and Network Security unveil the intricate relationship between data security and machine learning and provide a roadmap for implementing these cutting-edge techniques in the field. The book equips specialists, academics, and students in cryptography, machine learning, and network security with the tools to enhance encryption and decryption procedures by offering theoretical frameworks and the latest empirical research findings. Its pages unfold a narrative of collaboration and cross-pollination of ideas, showcasing how machine learning can be harnessed to sift through vast datasets, identify network weak points, and predict future cyber threats.

Author : Ruth, J. Anitha
Publisher : IGI Global
Page : 313 pages
File Size : 15,36 MB
Release : 2024-03-04
Category : Computers
ISBN :

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Data security is paramount in our modern world, and the symbiotic relationship between machine learning and cryptography has recently taken center stage. The vulnerability of traditional cryptosystems to human error and evolving cyber threats is a pressing concern. The stakes are higher than ever, and the need for innovative solutions to safeguard sensitive information is undeniable. Innovative Machine Learning Applications for Cryptography emerges as a steadfast resource in this landscape of uncertainty. Machine learning's prowess in scrutinizing data trends, identifying vulnerabilities, and constructing adaptive analytical models offers a compelling solution. The book explores how machine learning can automate the process of constructing analytical models, providing a continuous learning mechanism to protect against an ever-increasing influx of data. This book goes beyond theoretical exploration, and provides a comprehensive resource designed to empower academic scholars, specialists, and students in the fields of cryptography, machine learning, and network security. Its broad scope encompasses encryption, algorithms, security, and more unconventional topics like Quantum Cryptography, Biological Cryptography, and Neural Cryptography. By examining data patterns and identifying vulnerabilities, it equips its readers with actionable insights and strategies that can protect organizations from the dire consequences of security breaches.

Author : Xiaofeng Chen
Publisher : Springer Nature
Page : 168 pages
File Size : 24,51 MB
Release : 2021-07-02
Category : Computers
ISBN : 9813367261

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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.

Author : Edward Curry
Publisher : Springer Nature
Page : 399 pages
File Size : 49,77 MB
Release : 2021-08-01
Category : Computers
ISBN : 3030681769

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This open access book presents the foundations of the Big Data research and innovation ecosystem and the associated enablers that facilitate delivering value from data for business and society. It provides insights into the key elements for research and innovation, technical architectures, business models, skills, and best practices to support the creation of data-driven solutions and organizations. The book is a compilation of selected high-quality chapters covering best practices, technologies, experiences, and practical recommendations on research and innovation for big data. The contributions are grouped into four parts: · Part I: Ecosystem Elements of Big Data Value focuses on establishing the big data value ecosystem using a holistic approach to make it attractive and valuable to all stakeholders. · Part II: Research and Innovation Elements of Big Data Value details the key technical and capability challenges to be addressed for delivering big data value. · Part III: Business, Policy, and Societal Elements of Big Data Value investigates the need to make more efficient use of big data and understanding that data is an asset that has significant potential for the economy and society. · Part IV: Emerging Elements of Big Data Value explores the critical elements to maximizing the future potential of big data value. Overall, readers are provided with insights which can support them in creating data-driven solutions, organizations, and productive data ecosystems. The material represents the results of a collective effort undertaken by the European data community as part of the Big Data Value Public-Private Partnership (PPP) between the European Commission and the Big Data Value Association (BDVA) to boost data-driven digital transformation.

Author : Bimal Kumar Roy
Publisher : Springer Nature
Page : 461 pages
File Size : 46,12 MB
Release : 2023-10-17
Category : Technology & Engineering
ISBN : 9819922291

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The book features original papers from International Conference on Cryptology & Network Security with Machine Learning (ICCNSML 2022), organized by PSIT, Kanpur, India during 16 – 18 December 2022. This conference proceeding will provide the understanding of core concepts of Cryptology & Network Security with ML in data communication. The book covers research papers in public key cryptography, elliptic curve cryptography, post quantum cryptography, lattice based cryptography, non-commutative ring based cryptography, cryptocurrency, authentication, key agreement, Hash functions, block/stream ciphers, polynomial based cryptography, code based cryptography, NTRU cryptosystems, security and privacy in machine learning, block chain, IoT security, wireless security protocols, cryptanalysis, number theory, quantum computing, cryptographic aspects of network security, complexity theory, and cryptography with machine learning.

Author : Preeti Malik
Publisher : Walter de Gruyter GmbH & Co KG
Page : 160 pages
File Size : 28,52 MB
Release : 2022-12-05
Category : Business & Economics
ISBN : 3110766744

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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.

Author : Jeffrey J. P. Tsai
Publisher : Springer Science & Business Media
Page : 367 pages
File Size : 35,31 MB
Release : 2009-04-05
Category : Computers
ISBN : 0387887350

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Many networked computer systems are far too vulnerable to cyber attacks that can inhibit their functioning, corrupt important data, or expose private information. Not surprisingly, the field of cyber-based systems is a fertile ground where many tasks can be formulated as learning problems and approached in terms of machine learning algorithms. This book contains original materials by leading researchers in the area and covers applications of different machine learning methods in the reliability, security, performance, and privacy issues of cyber space. It enables readers to discover what types of learning methods are at their disposal, summarizing the state-of-the-practice in this significant area, and giving a classification of existing work. Those working in the field of cyber-based systems, including industrial managers, researchers, engineers, and graduate and senior undergraduate students will find this an indispensable guide in creating systems resistant to and tolerant of cyber attacks.

Author : Clarence Chio
Publisher : "O'Reilly Media, Inc."
Page : 385 pages
File Size : 12,22 MB
Release : 2018-01-26
Category : Computers
ISBN : 1491979879

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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

Author : Ferhat Ozgur Catak
Publisher :
Page : 300 pages
File Size : 14,45 MB
Release : 2021-10-30
Category :
ISBN : 9781799890638

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Focuses on learning vulnerabilities and cyber security. The book gives detail on the new threats and mitigation methods in the cyber security domain, and provides information on the new threats in new technologies such as vulnerabilities in deep learning, data privacy problems with GDPR, and new solutions.

Author : Brij B. Gupta
Publisher : CRC Press
Page : 352 pages
File Size : 13,49 MB
Release : 2019-02-05
Category : Computers
ISBN : 0429995725

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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.