Volume 6 - Issue 2
Security Compliance Tracking of Processes in Networked Cooperating Systems
- Roland Rieke
Fraunhofer Institute SIT, Darmstadt, Germany, Philipps-Universitat Marburg, Germany
roland.rieke@sit.fraunhofer.de
- Maria Zhdanova
Fraunhofer Institute SIT, Darmstadt, Germany
maria.zhdanova@sit.fraunhofer.de
- Jurgen Repp
Fraunhofer Institute SIT, Darmstadt, Germany
juergen.repp@sit.fraunhofer.de
Keywords: Predictive Security Analysis, Model-based Process Behavior Analysis, Security Modeling and Simulation, Security Compliance Monitoring, Security Information and Event Management, Governance and Compliance, Security of Critical Infrastructures
Abstract
Systems of systems that collaborate for a common purpose are called cooperating systems. Typical
examples of novel cooperating systems are electronic health systems and electronic money transfer
systems but also critical infrastructures, such as future vehicular ad hoc networks and distributed
air traffic management systems. Business processes and technical workflows control the cooperation
of the networked systems. Important safety and security goals of the applications, business
goals, and external compliance requirements create security obligations for such processes. These
processes must not only be secure, they must be demonstrably so. To support this, we present an
approach for security compliance tracking of processes in networked cooperating systems using an
advanced method of predictive security analysis at runtime. At that, operational models are utilized
for: (a) tracking conformance of process behavior with respect to the specification, (b) detection
of behavior anomalies which indicate possible attacks, (c) tracking compliance of process behavior
with respect to safety and security requirements, and (d) prediction of possible violations of safety
and security policies in the near future. We provide an extensive background analysis, introduce the
model-based conformance tracking and uncertainty management algorithm, and describe security
compliance tracking and model-based behavior prediction. We demonstrate the implementation of
the proposed approach on a critical infrastructure scenario from a European research project.