Multi-Access Filtering for Privacy-Preserving Fog Computing

The interest in fog computing is growing, including in traditionally conservative and sensitive areas such as military and governments. This is partly driven by the interconnectivity of our society, and advances in technologies such as Internet-of-Things (IoT). However, protecting against privacy leakage is one of several key considerations in fog computing deployment. Therefore, in this paper, we present a privacy-preserving multi-layer access filtering model, designed for a fog computing environment; hence, coined fog-based access filter (FAF). FAF comprises three key algorithms, namely: access filter initialization algorithm, optimal privacy-energy-time algorithm, and tuple reduction algorithm. Also, a hierarchical classification is used to distinguish the protection objectives. Findings from our experimental evaluation demonstrate that FAF allows one to achieve an optimal balance between privacy protection and computational costs.