Cyber Security Cryptography and Machine Learning: Third International Symposium, CSCML 2019, Beer-Sheva, Israel, June 27–28, 2019, Proceedings

Danny Hendler (Editor), Moti Yung (Editor), Shlomi Dolev (Editor), Sachin Lodha (Editor)

Research output: Book/ReportBookpeer-review

Abstract

CSCML, the International Symposium on Cyber Security Cryptography and Machine Learning, is an international forum for researchers, entrepreneurs, and practitioners in the theory, design, analysis, implementation, or application of cyber security, cryptography, and machine learning systems and networks, and, in particular, of conceptually innovative topics in these research areas. Information technology has become crucial to our everyday lives, an indispensable infrastructure of our society and therefore a target for attacks by malicious parties. Cyber security is one of the most important fields of research today because of these developments. Two of the (sometimes competing) fields of research, cryptography and machine learning, are the most important building blocks of cyber security. Topics of interest for CSCML include: cyber security design; 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 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; cryptocurrency; Blockchain;
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; and information retrieval, risk analysis, DoS.
Original languageEnglish
PublisherSpringer
Volume11527 LNCS
ISBN (Electronic)978-3-030-20951-3
ISBN (Print)978-3-030-20950-6
StatePublished - 2019

Publication series

NameLecture Notes in Computer Science
PublisherSpringer Verlag
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science (all)

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