AMSEP: Automated Multi-level Security Management for Multimedia Event Processing
Hichem Ben Abdallah, Takoua Abdellatif, Faouzi Chekir · Procedia Computer Science · 2018
Efficient event processing is fundamental for IoT systems handling critical data such as security surveillance and e-health. There is a need for data real time processing and accurate classification of events following their security level. These tasks are challenging in IoT context systems which handle a big volume of multimedia data. They require a large processing time and event consumers have different points of interest and multi-level access rights. In this paper, we propose AMSEP for multi-level security management of multimedia events. AMSEP automatically analyses incoming multimedia events, calculates their security levels following multi-level security policies in order to send them securely to their destinations. The proposed system is based on Deep Learning processing and on a publish/subscribe broker extension (Kafka). We show that mixing the two building blocks allows to fulfill three main challenges in IoT: (1) Accurate and real time event processing, (2) Dynamic adaptation to modify security policies and (3) event scalability and reliable routing of events from sources to destinations.