SIGMATA: Storage Integrity Guaranteeing Mechanism against Tampering Attempts for Video Event Data Recorders
نویسندگان
چکیده
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.
منابع مشابه
Some general methods for tampering with watermarks
Watermarks allow embedded signals to be extracted from audio and video content for a variety of purposes. One application is for copyright control, where it is envisaged that digital video recorders will not permit the recording of content that is watermarked as “never copy”. In such a scenario, it is important that the watermark survive both normal signal transformations and attempts to remove...
متن کاملPublic watermarks and resistance to tampering
Public watermarks allow embedded signals to be extracted from audio and video content for a variety of purposes. One application is for copyright control, where it is envisaged that digital video recorders will not permit the recording of content that is watermarked as "never copy". In such a scenario, it is important that the watermark survive both normal signal transformations and attempts to...
متن کاملLinkChains: Exploring the Space of Decentralised Trustworthy Linked Data
Distributed ledger platforms based on blockchains provide a fully distributed form of data storage which can guarantee data integrity. Certain use cases, such as medical applications, can benefit from guarantees that the results of arbitrary queries against a Linked Data set faithfully represent its contents as originally published, without tampering or data corruption. We describe potential ap...
متن کاملHistoric Integrity in Distributed Systems
In an all-digital, all-online setting, long-term secure record-keeping is a difficult task. The record-keeping problem comes up with increasing frequency, as we migrate to exclusively digital ways of transacting business. Accountability requires information about the content and the timing of business transactions. In the digital world, ideally, we should be able to tell with conviction when a ...
متن کاملVideo Authentication: Issues and Challenges
Video authentication aims to ensure the trustworthiness of the video by verifying the integrity and source of video data. It has gained much attention in the recent years. In this paper we present the issues in the designing of a video authentication system. These issues include the classification of tampering attacks, levels of tampering attack and robustness. Further we present the categoriza...
متن کامل