Kankanhalli, M. S.Chang, E.-C.Guan, X.Huang, Z.Wu, Y.J.A.Jorge and N.M.Correia and H.Jones and M.B.Kamegai2014-01-262014-01-2620013-211-83769-81812-7118https://doi.org/10.2312/EGMM/egmm01/119-1303D volume data has been increasingly used in many appli- cations. The digital nature of the data allows easy creation, copying and distribution. However, it also allows ease of manipulation which can enable wilful or inadvertent misrepresentation of the content. For an ap- plication like medical imaging, this can have serious diagnostic and legal implications. Thus there is a strong need to establish the integrity of a particular volume data-set. We argue that the traditional data authenti- cation mechanisms like digital signatures or cryptographic methods are not very useful in this context due to their extreme fragility. What is required is a method that can detect the integrity for allowable content- preserving manipulations.We have developed a novel authentication pro- cedure which is robust against benign content manipulation. The volume data can be robustly authenticated under normal operations such as scal- ing, resampling and additive Gaussian noise. On the other hand, it offers protection against any malefic or unintentional data manipulation which significantly changes the content of the volume data-set. Such manipu- lations include cropping, changing of voxel values etc. Our method uses segmentation, wavelet-based foveation, and encryption to achieve this. We have implemented the method and tested its robustness for several manipulations.