EvoRISK 2017 - 2017 Computational Intelligence for Risk Management, Security and Defence Applications

Events involving natural disasters and hacking attacks can get a wide media coverage; others such as software failures may receive less attention but all have in common that they can have significant economic and social impact. This emphasises the importance of solving challenging problems in risk management, software reliability, security and defence.
In this edition of EvoRISK we put special focus on minimising the risks posed by unreliable software via software testing.
Traditional methods have proven insufficient to address these problems and hence Computational Intelligence techniques present themselves as a more appealing alternative.
Areas of Interest and Contributions
We seek both theoretical developments and applications of Computational Intelligence to these subjects. All bio-inspired computational paradigms are welcome, mainly Genetic and Evolutionary Computation, but also Fuzzy Logic, Intelligent Agent Systems, Neural Networks, Cellular Automata, Artificial Immune Systems and others, including hybrids. Topics include but are not limited to:
Cyber crime: anomaly detection systems, attack prevention and defence, threat forecasting systems, anti spam, antivirus systems, cyber warfare, cyber fraud
Software testing: from security testing (zero-days, pentesting...) to GUI testing
IT Security: Intrusion detection, behaviour monitoring, network traffic analysis, Critical Infrastructure Protection (CIP), advanced persistent threats (APT) detection
Resilient and self-healing systems
Risk management: identification, prevention, monitoring and handling of risks, risk impact and probability estimation systems, contingency plans, real time risk management
Military, counter-terrorism and other defence related aspects
Disaster relief and humanitarian logistics
Real-world applications of these subjects