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Author: Shlomi Dolev
Publisher: Springer Nature
ISBN: 3031346718
Category : Computers
Languages : en
Pages : 539
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Book Description
This book constitutes the refereed proceedings of the 7th International Symposium on Cyber Security, Cryptology, and Machine Learning, CSCML 2023, held in Be'er Sheva, Israel, in June 2023. The 21 full and 15 short papers were carefully reviewed and selected from 70 submissions. They deal with the theory, design, analysis, implementation, and application of cyber security, cryptography and machine learning systems and networks, and conceptually innovative topics in these research areas.
Author: Shlomi Dolev
Publisher: Springer Nature
ISBN: 3031346718
Category : Computers
Languages : en
Pages : 539
Get Book
Book Description
This book constitutes the refereed proceedings of the 7th International Symposium on Cyber Security, Cryptology, and Machine Learning, CSCML 2023, held in Be'er Sheva, Israel, in June 2023. The 21 full and 15 short papers were carefully reviewed and selected from 70 submissions. They deal with the theory, design, analysis, implementation, and application of cyber security, cryptography and machine learning systems and networks, and conceptually innovative topics in these research areas.
Author: Shlomi Dolev
Publisher: Springer Nature
ISBN: 3031076893
Category : Computers
Languages : en
Pages : 522
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Book Description
This book constitutes the refereed proceedings of the 6th International Symposium on Cyber Security Cryptography and Machine Learning, CSCML 2022, held in Be'er Sheva, Israel, in June - July 2022. The 24 full and 11 short papers presented together with a keynote paper in this volume were carefully reviewed and selected from 53 submissions. They deal with the theory, design, analysis, implementation, or application of cyber security, cryptography and machine learning systems and networks, and conceptually innovative topics in these research areas.
Author: Shlomi Dolev
Publisher: Springer Nature
ISBN: 3030780864
Category : Computers
Languages : en
Pages : 506
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Book Description
This book constitutes the refereed proceedings of the 5th International Symposium on Cyber Security Cryptography and Machine Learning, CSCML 2021, held in Be'er Sheva, Israel, in July 2021. The 22 full and 13 short papers presented together with a keynote paper in this volume were carefully reviewed and selected from 48 submissions. They deal with the theory, design, analysis, implementation, or application of cyber security, cryptography and machine learning systems and networks, and conceptually innovative topics in these research areas.
Author: Shlomi Dolev
Publisher: Springer
ISBN: 3030209512
Category : Computers
Languages : en
Pages : 330
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Book Description
This book constitutes the refereed proceedings of the Third International Symposium on Cyber Security Cryptography and Machine Learning, CSCML 2019, held in Beer-Sheva, Israel, in June 2019. The 18 full and 10 short papers presented in this volume were carefully reviewed and selected from 36 submissions. They deal with the theory, design, analysis, implementation, or application of cyber security, cryptography and machine learning systems and networks, and conceptually innovative topics in these research areas.
Author: Xiaofeng Chen
Publisher: Springer Nature
ISBN: 9813367261
Category : Computers
Languages : en
Pages : 168
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Book Description
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: Atul Chaturvedi
Publisher: Springer Nature
ISBN: 9819706416
Category :
Languages : en
Pages : 881
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Book Description
Author: Shlomi Dolev
Publisher: Springer Nature
ISBN: 3030497852
Category : Computers
Languages : en
Pages : 265
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Book Description
This book constitutes the refereed proceedings of the Fourth International Symposium on Cyber Security Cryptography and Machine Learning, CSCML 2020, held in Be'er Sheva, Israel, in July 2020. The 12 full and 4 short papers presented in this volume were carefully reviewed and selected from 38 submissions. They deal with the theory, design, analysis, implementation, or application of cyber security, cryptography and machine learning systems and networks, and conceptually innovative topics in these research areas.
Author: Ruth, J. Anitha
Publisher: IGI Global
ISBN:
Category : Computers
Languages : en
Pages : 313
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Book Description
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: Vijayalakshmi G. V. Mahesh
Publisher: Engineering Science Reference
ISBN:
Category : Computers
Languages : en
Pages : 0
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Book Description
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. This book is an indispensable guide for scholars navigating the intricate domains of Elliptic Curve Cryptography, Cryptanalysis, Pairing-based Cryptography, Artificial Intelligence, Digital Signature Algorithms, and more. It not only sheds light on current challenges but also provides actionable insights and recommendations, making it an essential resource for those seeking to understand the evolving landscape of data security and actively contribute to its fortification. In a world where the stakes of cybersecurity are higher than ever, this book emerges as a beacon of knowledge, offering a proactive and informed solution to the persistent challenges faced by the research community.
Author: Sanjay Misra
Publisher: Springer Nature
ISBN: 3030722368
Category : Technology & Engineering
Languages : en
Pages : 467
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Book Description
This book provides stepwise discussion, exhaustive literature review, detailed analysis and discussion, rigorous experimentation results (using several analytics tools), and an application-oriented approach that can be demonstrated with respect to data analytics using artificial intelligence to make systems stronger (i.e., impossible to breach). We can see many serious cyber breaches on Government databases or public profiles at online social networking in the recent decade. Today artificial intelligence or machine learning is redefining every aspect of cyber security. From improving organizations’ ability to anticipate and thwart breaches, protecting the proliferating number of threat surfaces with Zero Trust Security frameworks to making passwords obsolete, AI and machine learning are essential to securing the perimeters of any business. The book is useful for researchers, academics, industry players, data engineers, data scientists, governmental organizations, and non-governmental organizations.
