Abstract
Traditionally, multimedia data such as audio, images, and videos have been protected using message authentication code (MAC) for authenticity and integrity verification. Standard MAC algorithms are very good at strict protection against manipulations. However, the sensitivity of a standard MAC is extremely high to manipulations, making it unsuitable for application in multimedia, where minor modifications are sometimes acceptable. Multimedia data, such as images, are usually pre-processed with standard image processing operations, compression, quantization, etc. which modifies the original image data. This processing yields the integrity verification and authentication on images to fail if the standard MAC based algorithms are used. Retransmissions may help in reducing the problem to a certain extent; however, retransmissions might not be possible over a unidirectional channel or in real-time transmissions where receiving an authentic part of an image (or other signals in general such as audio or video) might be better than having no image at all. There are specialized algorithms for image authentication which are tolerant to a certain degree of modifications in the data, introduced by channel noise or image processing operations. Such algorithms are called fuzzy authentication algorithms (Ur-Rehman O, Applications of Iterative Soft Decision Decoding, 2013) or fuzzy image authentication algorithms when applied to images. The decision of these authentication algorithms is not a strict binary decision as that of a standard MAC. Such algorithms are tolerant to modifications and this tolerance level can be adjusted by adjusting the parameters of the algorithm to vary their lenience to modifications. Fuzzy image authentication algorithms should be designed in a manner that they can differentiate legitimate manipulations from illegitimate manipulations. Many such algorithms have been proposed in literature for image authentication. These algorithms are normally based on image content rather than the data itself. Even if certain operations such as compression, quantization, etc. are applied, the content of the image remains unchanged. In this chapter, algorithms for fuzzy image authentication, with error localization and correction capabilities are discussed. Once the modifications in the image are localized to a specific region within the image, they can be corrected using the error correcting codes embedded in the authentication algorithms. These fuzzy image authentication algorithms will help in partial image acceptance despite minor errors left uncorrected by the error correcting codes. Simulation results given in this chapter show how such algorithms react to bit (and/or block) errors and how the error correction and fuzzy authentication has little or no visual impact on the resultant image quality.
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Ur-Rehman, O., Živić, N. (2015). Fuzzy Image Authentication with Error Localization and Correction. In: Živić, N. (eds) Robust Image Authentication in the Presence of Noise. Springer, Cham. https://doi.org/10.1007/978-3-319-13156-6_5
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DOI: https://doi.org/10.1007/978-3-319-13156-6_5
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