Towards a Formal Approach Based on Bigraphs for Fog Security: Case of Oil and Gas Refinery Plant Fog has the advantage of reducing service latency and improving perceived quality, as well as the benefit of total data distribution. However, its security or privacy issues pose major challenges due to the heterogeneity, hierarchical structure, and very large scale infrastructure of Fog architecture. CABRS model, an extension of Bigraphical Reactive Systems with Control Agents, is showed to be an appropriate formal semantic framework for Fog architecture specification. It separates, for a complex system, the concerns of computation and physical entities distribution, respectively into two different models: 1) computational or virtual agentsu0027 model and 2) physical Bigraph model. The main objective of this paper is twofold; first, we propose a multiviews architecture to Fog computing taking into account security level, then we define, according to this semantic framework, the physical entities of Fog architecture and their geographical dispersion, as well as the virtual entities devoted to represent security functionalities. Our proposal is illustrated through a realistic case study of Oil and Gas Refinery Plant.

Towards a Threat Model for Fog Computing In recent years, the addition of billions of Internet of Thing (IoT) device spawned a massive demand for computing service near the edge of the network. Due to latency, limited mobility, and location awareness, cloud computing is not capable enough to serve these devices. As a result, the focus is shifting more towards distributed platform service to put ample computing power near the edge of the networks. Thus, paradigms such as Fog and Edge computing are gaining attention from researchers as well as business stakeholders. Fog computing is a new computing paradigm, which places computing nodes in between the Cloud and the end user to reduce latency and increase availability. As an emerging technology, Fog computing also brings newer security challenges for the stakeholders to solve. Before designing the security models for Fog computing, it is better to understand the existing threats to Fog computing. In this regard, a thorough threat model can significantly help to identify these threats. Threat modeling is a sophisticated engineering process by which a computerbased system is analyzed to discover security flaws. In this paper, we applied two popular security threat modeling processes  CIAA and STRIDE  to identify and analyze attackers, their capabilities and motivations, and a list of potential threats in the context of Fog computing. We posit that such a systematic and thorough discussion of a threat model for Fog computing will help security researchers and professionals to design secure and reliable Fog computing systems.