DEFEDGE: Threat-Driven Security Testing and Proactive Defense Identification for Edge-Cloud Systems

Abstract

Nowadays, the edge-cloud (EC) paradigm is adopted in several domains, including manufacturing, health, and critical infrastructure management. Identifying existing threats and vulnerabilities of an EC system and determining appropriate countermeasures is a costly and time-consuming process due to the inherent system complexity and to the heterogeneity of involved assets. Moreover, even when appropriate security measures are enforced, attacks may still succeed because of the natural degradation of security mechanisms’ effectiveness due to attackers’ reconnaissance efforts and/or to unknown vulnerabilities coming into play. This paper describes the objectives of the DEFEDGE project, which aims to define a set of techniques for the development of secure and resilient edge-cloud systems and for their assessment based on a threat-driven approach. The main idea is to leverage the results of a guided threat modeling process to derive both the security controls and the mechanisms to be enforced, as well as the security tests to perform in order to verify the effectiveness of controls in place. Security controls selection and enforcement will follow Moving Target Defense principles. Security testing will exploit existing threat intelligence and attack patterns knowledge bases to derive a set of general-purpose attack procedures that can be suitably customized to test a target system. For the generation of attack procedures and their customization, the project will also explore machine learning techniques to infer new attack patterns and scenarios, in order to improve the overall testing effectiveness.