Multi-Access Filtering for Privacy-Preserving Fog Computing


The military and other traditionally conservative and sensitive sectors, such as government and law enforcement, are beginning to show an increased interest in fog computing. This is in part driven by how interconnected our society has become, as well as advances in technologies such as the Internet of Things (IoT). When deploying fog computing, however, one of the most important things to think about is how to prevent the leaking of private information. For this reason, in this paper, we present a privacy-preserving multi-layer access filtering model that was designed for a fog computing environment; consequently, we coined this model the fog-based access filter (FAF). Access filter initialization algorithm, optimal privacy-energy-time algorithm, and tuple reduction algorithm are the three fundamental algorithms that make up FAF. In addition to this, a hierarchical classification is utilized in order to differentiate the different protection objectives. The results of our experimental evaluation show that FAF makes it possible to strike the best possible balance between the level of privacy protection and the amount of computational effort required.

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