tamper proofing mechanisms for motion capture data
Repositories of motion captured (Mocap) data can be reused for human motion analysis in physical medicine, biomechanics, and animation related entertainment industry. Mocap data expressed as a matrix can be subject to tampering from shuffling of its elements or change in element values due to motion editing operations. Tampering of the archival system intentionally or due to machine/human errors, may result in loss of research, money and effort. In order to detect and correct errors induced due to tampering; this paper proposes a tamper proofing methodology that combines hash function and watermarking based methods. These patterns (fingerprints) resulting from hash functions help in error detection by identifying the type of attack such as row shuffling, column shuffling, row element shuffling, column element shuffling and their combinations. Random attacks that change data element values are detected by change in watermarks embedded in data elements. Finger prints help in solving the attacks reversal such as column shuffling and element shuffling, whereas watermarking helps in reversing attacks such as column element or row element shuffling. As compared to other attacks, random attacks cannot be reversed, and can be improved using interpolation. Analysis shows that the proposed method uses O(n) space to detect and correct errors, and the time complexity for correction varying from o(n log n) to O(n!).
watermarking spatial encoding decoding blind