Peer Reviewed Journal via three different mandatory reviewing processes, since 2006, and, from September 2020, a fourth mandatory peer-editing has been added.
The usage and market size of video event data recorders (VEDRs), also known as car black boxes, are rapidly increasing. Since VEDRs can provide more visual information about car accident situations than any other device that is currently used for accident investigations (e.g., closed-circuit television), the integrity of the VEDR contents is important to any meaningful investigation. Researchers have focused on the file system integrity or photographic approaches to integrity verification. However, unlike other general data, the video data in VEDRs exhibit a unique I/O behavior in that the videos are stored chronologically. In addition, the owners of VEDRs can manipulate unfavorable scenes after accidents to conceal their recorded behavior. Since prior arts do not consider the time relationship between the frames and fail to discover frame-wise forgery, a more detailed integrity assurance is required. In this paper, we focus on the development of a frame-wise forgery detection mechanism that resolves the limitations of previous mechanisms. We introduce SIGMATA, a novel storage integrity guaranteeing mechanism against tampering attempts for VEDRs. We describe its operation, demonstrate its effectiveness for detecting possible frame-wise forgery, and compare it with existing mechanisms. The result shows that the existing mechanisms fail to detect any frame-wise forgery, while our mechanism thoroughly detects every frame-wise forgery. We also evaluate its computational overhead using real VEDR videos. The results show that SIGMATA indeed discovers frame-wise forgery attacks effectively and efficiently, with the encoding overhead less than 1.5 milliseconds per frame.
