Visible to the public Pushing Data Privacy Control to the Edge in IoT Using Policy Enforcement Fog Module

TitlePushing Data Privacy Control to the Edge in IoT Using Policy Enforcement Fog Module
Publication TypeConference Paper
Year of Publication2017
AuthorsAl-Hasnawi, Abduljaleel, Lilien, Leszek
Conference NameCompanion Proceedings of The10th International Conference on Utility and Cloud Computing
PublisherACM
Conference LocationNew York, NY, USA
ISBN Number978-1-4503-5195-9
Keywordsactive data bundles, cloud computing, Fog Computing, Human Behavior, Internet of Things, policy, privacy, Privacy Policies, pubcrawl, real-time processing, Scalability, sensitive data, smart home
Abstract

Some IoT data are time-sensitive and cannot be processed in clouds, which are too far away from IoT devices. Fog computing, located as close as possible to data sources at the edge of IoT systems, deals with this problem. Some IoT data are sensitive and require privacy controls. The proposed Policy Enforcement Fog Module (PEFM), running within a single fog, operates close to data sources connected to their fog, and enforces privacy policies for all sensitive IoT data generated by these data sources. PEFM distinguishes two kinds of fog data processing. First, fog nodes process data for local IoT applications, running within the local fog. All real-time data processing must be local to satisfy real-time constraints. Second, fog nodes disseminate data to nodes beyond the local fog (including remote fogs and clouds) for remote (and non-real-time) IoT applications. PEFM has two components for these two kinds of fog data processing. First, Local Policy Enforcement Module (LPEM), performs direct privacy policy enforcement for sensitive data accessed by local IoT applications. Second, Remote Policy Enforcement Module (RPEM), sets up a mechanism for indirectly enforcing privacy policies for sensitive data sent to remote IoT applications. RPEM is based on creating and disseminating Active Data Bundles-software constructs bundling inseparably sensitive data, their privacy policies, and an execution engine able to enforce privacy policies. To prove effectiveness and efficiency of the solution, we developed a proof-of-concept scenario for a smart home IoT application. We investigate privacy threats for sensitive IoT data and show a framework for using PEFM to overcome these threats.

URLhttp://dx.doi.org/10.1145/3147234.3148124
DOI10.1145/3147234.3148124
Citation Keyal-hasnawi_pushing_2017