Collaborative Fog Computing Architecture for Privacy-Preserving Data Aggregation

Abstract

The increased digitization of several critical infrastructure services on Internet like home banking, online payments, etc. exposes them to a range of sophisticated information security attacks. Thus, there is an urgent need for strong collaboration between all governmental and non-governmental organizations in order to form the defenses by sharing. Sharing and analyzing sensitive traffic data is an important aspect to protect critical infrastructures. However, privacy concerns of the data contributors about sharing their sensitive data prevent them from gaining the benefits from collaboration, or at least weaken it to a degree of insufficiency. To cope with those privacy concerns, we extend our preceding work about constructing an efficient framework for personal collaborative event processing permitting information sharing and processing amongst administratively and geographically disjoint organizations. The structure is able to aggregating and correlating events coming from the organizations in near real-time while preserving the privacy of sensitive data even in case of coalition among the entities in the environment. The key novelty of the structure is the use of a pseudorandom oracle capability dispensed among the use of FOG structure among the organizations collaborating to the system for obfuscating the data, that permits for achieving a good level of privacy at the same time as guaranteeing scalability in both dimensions: horizontally (range of collaborators) and vertically (range of dataset per collaborator).