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Cyber Security Cryptography and Machine Learning

Cyber Security Cryptography and Machine Learning PDF Author: Shlomi Dolev
Publisher: Springer
ISBN: 331960080X
Category : Computers
Languages : en
Pages : 307

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Book Description
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.

Cyber Security Cryptography and Machine Learning

Cyber Security Cryptography and Machine Learning PDF Author: Shlomi Dolev
Publisher: Springer
ISBN: 331960080X
Category : Computers
Languages : en
Pages : 307

View

Book Description
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.

Cyber Security Cryptography and Machine Learning

Cyber Security Cryptography and Machine Learning PDF Author: Itai Dinur
Publisher: Springer
ISBN: 331994147X
Category : Computers
Languages : en
Pages : 287

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Book Description
This book constitutes the refereed proceedings of the Second International Symposium on Cyber Security Cryptography and Machine Learning, CSCML 2018, held in Beer-Sheva, Israel, in June 2018. The 16 full and 6 short papers presented in this volume were carefully reviewed and selected from 44 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 the scope.

Cyber Security Cryptography and Machine Learning

Cyber Security Cryptography and Machine Learning PDF 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.

Cyber Security Cryptography and Machine Learning

Cyber Security Cryptography and Machine Learning PDF 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.

Cyber Security Cryptography and Machine Learning

Cyber Security Cryptography and Machine Learning PDF Author: Shlomi Dolev
Publisher: Springer
ISBN: 9783030497842
Category : Computers
Languages : en
Pages : 255

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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 Beer-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.

Machine Learning and Cognitive Science Applications in Cyber Security

Machine Learning and Cognitive Science Applications in Cyber Security PDF Author: Khan, Muhammad Salman
Publisher: IGI Global
ISBN: 1522581014
Category : Computers
Languages : en
Pages : 321

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Book Description
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.

Quantum Cryptography and the Future of Cyber Security

Quantum Cryptography and the Future of Cyber Security PDF Author: Chaubey, Nirbhay Kumar
Publisher: IGI Global
ISBN: 1799822559
Category : Computers
Languages : en
Pages : 343

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Book Description
The shortcomings of modern cryptography and its weaknesses against computers that are becoming more powerful necessitate serious consideration of more robust security options. Quantum cryptography is sound, and its practical implementations are becoming more mature. Many applications can use quantum cryptography as a backbone, including key distribution, secure direct communications, large prime factorization, e-commerce, e-governance, quantum internet, and more. For this reason, quantum cryptography is gaining interest and importance among computer and security professionals. Quantum Cryptography and the Future of Cyber Security is an essential scholarly resource that provides the latest research and advancements in cryptography and cyber security through quantum applications. Highlighting a wide range of topics such as e-commerce, machine learning, and privacy, this book is ideal for security analysts, systems engineers, software security engineers, data scientists, vulnerability analysts, professionals, academicians, researchers, security professionals, policymakers, and students.

The CISO’s Next Frontier

The CISO’s Next Frontier PDF Author: Raj Badhwar
Publisher: Springer Nature
ISBN: 3030753549
Category : Computers
Languages : en
Pages : 387

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Book Description
This book provides an advanced understanding of cyber threats as well as the risks companies are facing. It includes a detailed analysis of many technologies and approaches important to decreasing, mitigating or remediating those threats and risks. Cyber security technologies discussed in this book are futuristic and current. Advanced security topics such as secure remote work, data security, network security, application and device security, cloud security, and cyber risk and privacy are presented in this book. At the end of every chapter, an evaluation of the topic from a CISO’s perspective is provided. This book also addresses quantum computing, artificial intelligence and machine learning for cyber security The opening chapters describe the power and danger of quantum computing, proposing two solutions for protection from probable quantum computer attacks: the tactical enhancement of existing algorithms to make them quantum-resistant, and the strategic implementation of quantum-safe algorithms and cryptosystems. The following chapters make the case for using supervised and unsupervised AI/ML to develop predictive, prescriptive, cognitive and auto-reactive threat detection, mitigation, and remediation capabilities against advanced attacks perpetrated by sophisticated threat actors, APT and polymorphic/metamorphic malware. CISOs must be concerned about current on-going sophisticated cyber-attacks, and can address them with advanced security measures. The latter half of this book discusses some current sophisticated cyber-attacks and available protective measures enabled by the advancement of cybersecurity capabilities in various IT domains. Chapters 6-10 discuss secure remote work; chapters 11-17, advanced data security paradigms; chapters 18-28, Network Security; chapters 29-35, application and device security; chapters 36-39, Cloud security; and chapters 40-46 organizational cyber risk measurement and event probability. Security and IT engineers, administrators and developers, CIOs, CTOs, CISOs, and CFOs will want to purchase this book. Risk personnel, CROs, IT and Security Auditors as well as security researchers and journalists will also find this useful.

Malware Analysis Using Artificial Intelligence and Deep Learning

Malware Analysis Using Artificial Intelligence and Deep Learning PDF Author: Mark Stamp
Publisher: Springer Nature
ISBN: 3030625826
Category : Computers
Languages : en
Pages : 651

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Book Description
​This book is focused on the use of deep learning (DL) and artificial intelligence (AI) as tools to advance the fields of malware detection and analysis. The individual chapters of the book deal with a wide variety of state-of-the-art AI and DL techniques, which are applied to a number of challenging malware-related problems. DL and AI based approaches to malware detection and analysis are largely data driven and hence minimal expert domain knowledge of malware is needed. This book fills a gap between the emerging fields of DL/AI and malware analysis. It covers a broad range of modern and practical DL and AI techniques, including frameworks and development tools enabling the audience to innovate with cutting-edge research advancements in a multitude of malware (and closely related) use cases.

Privacy-Preserving Deep Learning

Privacy-Preserving Deep Learning PDF Author: Kwangjo Kim
Publisher: Springer Nature
ISBN: 9811637644
Category : Computers
Languages : en
Pages : 74

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Book Description
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.