International Symposium on Cyber Security Cryptography and Machine Learning (CSCML)
InfoSec Conference Summary
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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 the scope.
The information technology became crucial to our everyday life in indispensable infrastructures of our society and therefore a target for attacks by malicious parties.
Cyber security is one of the most important fields of research these days because of this phenomena. The two, sometimes competing, fields of research, cryptography and machine learning are the most important building blocks of cyber security, as cryptography hides information by avoiding the possibility to extract any useful information pattern while machine learning is searching for meaningful information patterns. The subject 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; Cryptography; Cryptographic implementation analysis and construction; Secure Multi-Party computation; Privacy-enhancing technologies and anonymity; 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.