Abstract
With the rapid development of wireless sensor network, the transmission and processing of multimedia data gradually become the main task of wireless sensors. To reduce the data bandwidth, many wireless sensors use frame rate up-conversion (FRUC) to recover the dropped frames at the receiver. FRUC is actually a temporal-domain tampering operation of video at the receiver, and FRUC forgery can be found by analyzing the statistical feature of the video. In this chapter, a forensics algorithm based on edge feature is proposed to discover forged traces of FRUC by detecting the edge variation of video frames. First, the Sobel operator is used to detect the edge of video frames. Then, the edge is quantified to obtain the edge complexity of each frame. Finally, the periodicity of the edge complexity along time axis is detected, and FRUC forgery is automatically identified by hard threshold decision. Experimental results show that the proposed algorithm has a good forensics performance for different FRUC forgery methods. Especially after the attacks of de-noising and compression, the proposed algorithm can still ensure high detection accuracy.
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Ma, W., Li, R. (2019). Digital Forensics for Frame Rate Up-Conversion in Wireless Sensor Network. In: Al-Turjman, F. (eds) Artificial Intelligence in IoT. Transactions on Computational Science and Computational Intelligence. Springer, Cham. https://doi.org/10.1007/978-3-030-04110-6_8
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DOI: https://doi.org/10.1007/978-3-030-04110-6_8
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