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Information from surveillance video is essential for situational awareness(SAW). Nowadays, a prohibitively large amount of surveillance data is beinggenerated continuously by ubiquitously distributed video sensors. It is verychallenging to immediately identify the objects of interest or zoom insuspicious actions from thousands of video frames. Making the big dataindexable is critical to tackle this problem. It is ideal to generate patternindexes in a real-time, on-site manner on the video streaming instead ofdepending on the batch processing at the cloud centers. The modernedge-fog-cloud computing paradigm allows implementation of time sensitive tasksat the edge of the network. The on-site edge devices collect the informationsensed in format of frames and extracts useful features. The near-site fognodes conduct the contextualization and classification of the features. Theremote cloud center is in charge of more data intensive and computing intensivetasks. However, exchanging the index information among devices in differentlayers raises security concerns where an adversary can capture or tamper withfeatures to mislead the surveillance system. In this paper, a blockchainenabled scheme is proposed to protect the index data through an encryptedsecure channel between the edge and fog nodes. It reduces the chance of attackson the small edge and fog devices. The feasibility of the proposal is validatedthrough intensive experimental analysis.

Real-Time Index Authentication for Event-Oriented Surveillance Video Query using Blockchain