TAXONOMY OF SECURITY AND PRIVACY CHALLENGES IN MULTI-TENANT FOG COMPUTING

Abstract

Fog computing offers low-latency services, which have made it possible for Internet of Things (IoT) applications to get cloud capabilities closer to the end users. However, in distributed and heterogeneous fog environments, the use of multi-tenancy is a crucial component for resource sharing and scalability, which introduces new possibilities for privacy and security violations. A taxonomy of security and privacy issues in multi-tenant fog computing is presented in this paper. The taxonomy systematically classifies attacks and vulnerabilities based on attack origin (external, internal, cross-layer), fog layer interaction (IoT–Fog, Fog–Fog, Fog–Cloud, Cross-layer), and violated security goals (confidentiality, integrity, availability, accountability, and privacy). Through an in-depth systematic literature review (SLR), we identify critical gaps in current defence mechanisms and discuss open research challenges unique to the multi-tenant fog paradigm, including isolation, trust management, data provenance, and dynamic resource migration. This taxonomy serves as a foundation for developing secure and privacy-preserving multi-tenancy models and guiding future research directions in fog-based distributed systems.