PAPAYA: Platform for PrivAcY preserving data Analytics is one of the GDPR cluster projects that will help companies to follow a privacy-by-design approach & adopt
#PrivacyEnhancingTechnologies to ensure their clients’ privacy is protected.
Detecting advanced multi-stage attacks is difficult in IT systems, but approaches towards detection and response for ICS (Industrial Control Systems) are comparatively less mature. Moreover, attacks discovered in the wild continue to evolve in sophistication. Stopping such attacks demands continual monitoring of the infrastructure and it is difficult to provide operators with targeted security status information in the face of advanced multi-stage ICS threats.
This research aims to develop and test an approach that enhances real-time cyber-security monitoring capabilities for networked ICS environments. The objective is to present information to an operator that is more closely correlated to advanced multi-stage threats, rather than individual alerts, thereby improving the ability of the operator to gauge the current security status of the system.
A threat measurement based approach will be used to investigate how the real-time cyber-security status of an ICS network environment can be measured in terms of an observable threat presence. It is hypothesised that such a status can be appraised by using suitable metrics, which may be derived by analysing, decomposing and modelling known advanced multistage threats. The analysis will target the development of threat models based on a combination of reported ICS attacks and an investigation of future potential advanced threats based on emerging trends in crimeware. A proposed solution will be implemented and tested in a test-bed environment based on a realistic factory automation environment.