A semi-adaptive time variant modeling method is developed to be used in conjunction with an arithmetic coder to compress data in a secure fashion. The modeling method introduces randomness into the symbols coding probabilities by ensuring that the update time for computing the coding probabilities is performed at random intervals as specified by the output of a stream cipher. The method results in the ability to efectively compress the datu while ensuring its security. The compression ratios of the method are very close to the ratios obtained from standurd implementation of adaptive modelers.The computational complexity of the proposed method is less than the computational complexity of performing a compression step that is followed by an encvyption step. Additionally, the computational complexity of the method is less than the computational complexity of typical implementations of adaptive modelers. The methodology allows for building high security architectures that are ideal for real time operations.
This paper develops a nonconventional view of dedicated architectures. Instead of devices to evaluate a given algorithm, the architectures are considered as generators of transformations parameterized by the compute time. With this approach, a single architecture can be used to implement a family of transformations with varying degrees of complexity. The paper considers in detail the transformations generated by a matrix multiplication array.The paper shows that the approach enables the designer to use the available (or desired) compute time as one more design parameter. For some real-time applications it becomes possible to incorporate the compute time as a constraint for designs based in optimality criteria. In particular, the paper considers a least square approximation problem.
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