A Multi-level Intelligent Selective Encryption Control Model for Multimedia Big Data Security in Sensing System with Resource Constraints

The multimedia big data in multimedia sensing and other IoT (Internet of Things) systems are high-volume, real-time, dynamic and heterogeneous. These characteristics lead to new challenges of data security. When computation and power resources in some IoT nodes are very scarce, these challenges become more serious that complex data security process on multimedia data is restricted by the aforementioned limited resources. Hence, the confidentiality of multimedia big data under resources constraints is investigated in this paper. Firstly, the growth trend of data volume compared with computational resources is discussed, and an analysis model for multimedia data encryption optimization is proposed. Secondly, a general-purpose lightweight speed tunable video encryption scheme is introduced. Thirdly, a series of intelligent selective encryption control models are proposed. Fourthly, the performance of proposed schemes is evaluated by experimental analyses and proves that schemes are effective enough to support real-time encryption of multimedia big data. Additionally, in the age of big data and cloud computing, the aforementioned analysis method can also be applied to other systems with limited resources.