Video Surveillance Authentication: Real-Time ENF Signal Hiding at the Edge

Due to the significance of the visual information exchanged in Internet of Video Things (IoVT) networks, attackers are constantly launching new attacks and attempt to exploit new vulnerabilities. One of the most common and difficult-to-prevent attacks on the Visual Layer is the Frame Duplication Attack (FDA). Recently, two techniques were proposed for FDA detection at the edge by using the embedded Electrical Network Frequency (ENF) signals in an effort to surpass limitations of conventional passive methods. In this paper, a Real-Time ENF signal hiding technique at the edge is proposed. Our motivation is to examine the possibility of authenticating the surveillance feed by hiding the ENF signal. Experiments are conducted, including an extensive performance comparison between the proposed and reference encoder, a feasibility study for the proposed encoder’s integration to a Raspberry Pi for video streaming purposes and finally the implementation of a proof-of-concept prototype. According to the findings, the proposed approach provides real-time FDA detection at reduced computational complexity and hardware requirements, thus rendering this method appropriate for applications at the edge.