Machine Learning And Cryptographic Solutions For Data Protection And Network Security
DOWNLOAD
Download Machine Learning And Cryptographic Solutions For Data Protection And Network Security PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Machine Learning And Cryptographic Solutions For Data Protection And Network Security book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Machine Learning And Cryptographic Solutions For Data Protection And Network Security
DOWNLOAD
Author : Vijayalakshmi G. V. Mahesh
language : en
Publisher:
Release Date : 2024-05-31
Machine Learning And Cryptographic Solutions For Data Protection And Network Security written by Vijayalakshmi G. V. Mahesh and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-31 with categories.
Innovative Machine Learning Applications For Cryptography
DOWNLOAD
Author : Ruth, J. Anitha
language : en
Publisher: IGI Global
Release Date : 2024-03-04
Innovative Machine Learning Applications For Cryptography written by Ruth, J. Anitha and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-04 with Computers categories.
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.
Privacy Preserving Machine Learning
DOWNLOAD
Author : Jin Li
language : en
Publisher: Springer Nature
Release Date : 2022-03-14
Privacy Preserving Machine Learning written by Jin Li and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-14 with Computers categories.
This book provides a thorough overview of the evolution of privacy-preserving machine learning schemes over the last ten years, after discussing the importance of privacy-preserving techniques. In response to the diversity of Internet services, data services based on machine learning are now available for various applications, including risk assessment and image recognition. In light of open access to datasets and not fully trusted environments, machine learning-based applications face enormous security and privacy risks. In turn, it presents studies conducted to address privacy issues and a series of proposed solutions for ensuring privacy protection in machine learning tasks involving multiple parties. In closing, the book reviews state-of-the-art privacy-preserving techniques and examines the security threats they face.
Cyber Security Meets Machine Learning
DOWNLOAD
Author : Xiaofeng Chen
language : en
Publisher: Springer Nature
Release Date : 2021-07-02
Cyber Security Meets Machine Learning written by Xiaofeng Chen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-02 with Computers categories.
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.
Machine Learning In Cyber Trust
DOWNLOAD
Author : Jeffrey J. P. Tsai
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-04-05
Machine Learning In Cyber Trust written by Jeffrey J. P. Tsai and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-04-05 with Computers categories.
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.
Cyber Security And Adversarial Machine Learning
DOWNLOAD
Author : Ferhat Ozgur Catak
language : en
Publisher:
Release Date : 2021-10-30
Cyber Security And Adversarial Machine Learning written by Ferhat Ozgur Catak and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-30 with categories.
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.
Cyber Security Cryptography And Machine Learning
DOWNLOAD
Author : Shlomi Dolev
language : en
Publisher: Springer
Release Date : 2017-06-14
Cyber Security Cryptography And Machine Learning written by Shlomi Dolev and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-06-14 with Computers categories.
This book constitutes the proceedings of the first International Symposium on Cyber Security Cryptography and Machine Learning, held in Beer-Sheva, Israel, in June 2017. The 17 full and 4 short papers presented include cyber security; secure software development methodologies, formal methods semantics and verification of secure systems; fault tolerance, reliability, availability of distributed secure systems; game-theoretic approaches to secure computing; automatic recovery of self-stabilizing and self-organizing systems; communication, authentication and identification security; cyber security for mobile and Internet of things; cyber security of corporations; security and privacy for cloud, edge and fog computing; cryptography; cryptographic implementation analysis and construction; secure multi-party computation; privacy-enhancing technologies and anonymity; post-quantum cryptography and security; machine learning and big data; anomaly detection and malware identification; business intelligence and security; digital forensics; digital rights management; trust management and reputation systems; information retrieval, risk analysis, DoS.
Privacy Preserving Deep Learning
DOWNLOAD
Author : Kwangjo Kim
language : en
Publisher: Springer Nature
Release Date : 2021-07-22
Privacy Preserving Deep Learning written by Kwangjo Kim and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-22 with Computers categories.
This book discusses the state-of-the-art in privacy-preserving deep learning (PPDL), especially as a tool for machine learning as a service (MLaaS), which serves as an enabling technology by combining classical privacy-preserving and cryptographic protocols with deep learning. Google and Microsoft announced a major investment in PPDL in early 2019. This was followed by Google’s infamous announcement of “Private Join and Compute,” an open source PPDL tools based on secure multi-party computation (secure MPC) and homomorphic encryption (HE) in June of that year. One of the challenging issues concerning PPDL is selecting its practical applicability despite the gap between the theory and practice. In order to solve this problem, it has recently been proposed that in addition to classical privacy-preserving methods (HE, secure MPC, differential privacy, secure enclaves), new federated or split learning for PPDL should also be applied. This concept involves building a cloud framework that enables collaborative learning while keeping training data on client devices. This successfully preserves privacy and while allowing the framework to be implemented in the real world. This book provides fundamental insights into privacy-preserving and deep learning, offering a comprehensive overview of the state-of-the-art in PPDL methods. It discusses practical issues, and leveraging federated or split-learning-based PPDL. Covering the fundamental theory of PPDL, the pros and cons of current PPDL methods, and addressing the gap between theory and practice in the most recent approaches, it is a valuable reference resource for a general audience, undergraduate and graduate students, as well as practitioners interested learning about PPDL from the scratch, and researchers wanting to explore PPDL for their applications.
Trust Security And Privacy For Big Data
DOWNLOAD
Author : Mamoun Alazab
language : en
Publisher: CRC Press
Release Date : 2022-06-30
Trust Security And Privacy For Big Data written by Mamoun Alazab and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-30 with Computers categories.
Data has revolutionized the digital ecosystem. Readily available large datasets foster AI and machine learning automated solutions. The data generated from diverse and varied sources including IoT, social platforms, healthcare, system logs, bio-informatics, etc. contribute to and define the ethos of Big Data which is volume, velocity and variety. Data lakes formed by the amalgamation of data from these sources requires powerful, scalable and resilient storage and processing platforms to reveal the true value hidden inside this data mine. Data formats and its collection from various sources not only introduce unprecedented challenges to different domains including IoT, manufacturing, smart cars, power grids etc., but also highlight the security and privacy issues in this age of big data. Security and privacy in big data is facing many challenges, such as generative adversary networks, efficient encryption and decryption algorithms, encrypted information retrieval, attribute-based encryption, attacks on availability, and reliability. Providing security and privacy for big data storage, transmission, and processing have been attracting much attention in all big data related areas. The book provides timely and comprehensive information for researchers and industry partners in communications and networking domains to review the latest results in security and privacy related work of Big Data. It will serve computer science and cybersecurity communities including researchers, academicians, students, and practitioners who have interest in big data trust privacy and security aspects. It is a comprehensive work on the most recent developments in security of datasets from varied sources including IoT, cyber physical domains, big data architectures, studies for trustworthy computing, and approaches for distributed systems and big data security solutions etc.
Improving Security Privacy And Trust In Cloud Computing
DOWNLOAD
Author : Goel, Pawan Kumar
language : en
Publisher: IGI Global
Release Date : 2024-02-02
Improving Security Privacy And Trust In Cloud Computing written by Goel, Pawan Kumar and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-02 with Computers categories.
Cloud computing adoption has revolutionized how businesses and individuals harness the power of technology. The cloud's scalability, accessibility, and cost-efficiency have propelled it to the forefront of modern computing paradigms. However, as organizations increasingly rely on cloud services to store, process, and manage their data and applications, an intricate web of challenges has emerged, casting shadows over the very foundations of cloud computing. Improving Security, Privacy, and Trust in Cloud Computing unravels the complexities surrounding the cloud landscape, delving into the core concerns of security, privacy, and trust that have come to define its evolution. It aims to equip readers with the insights, knowledge, and practical strategies needed to navigate the intricate realm of cloud computing while safeguarding their most valuable assets. This book's exploration into security, privacy, and trust in cloud computing takes a holistic approach. Throughout the chapters of this book, readers will embark on a multidimensional expedition. This book will take them through real-world case studies of successful cloud security implementations and unfortunate breaches that underscore the urgency of robust defenses. From data encryption techniques to incident response protocols, this book offers practical insights and actionable strategies that can be implemented by IT professionals, security experts, and decision-makers alike.