Data integrity is a prerequisite for ensuring data availability of IoT data and has received extensive attention in the field of IoT big data security. Stream computing systems are widely used in the field of IoT for real-time data acquisition and computing. However, the real-time, volatility, suddenness, and disorder of stream data make data integrity verification difficult. According to the survey, there is no mature and universal solution. To solve this issue, we constructed a data integrity verification algorithm scheme of the stream computing system (S-DIV) by utilizing homomorphic message authentication code and pseudo-random function security assumption. Furthermore, based on S-DIV, an external data integrity tracking and verification system is constructed to track and analyze the message data stream in real time. By verifying the data integrity of message during the whole life cycle, the problem of data corruption or data loss can be found in time, and error alarm and message recovery can be actively implemented. Then, we conduct the formal security analysis under the standard model and, finally, implement the S-DIV scheme in simulation environment. Experimental results show that the scheme can guarantee data integrity in an acceptable time without affecting the efficiency of the original system.
Keywords: data integrity verification; integrity tracking and verification system; internet of things; stream computing.