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The Compressed Sensing (CS) paradigm unifies sensing and compression of sparse signals in a simple linear measurement step. Reconstruction of the signal from the CS measurements relies on the knowledge of the measurement matrix used for sensing. Generation of the pseudo-random sensing matrix utilizing a cryptographic key, offers a natural method for encrypting the signal during CS. This CS based encryption has the inherent advantage that encryption occurs implicitly in the sensing process - without requiring additional computation. Additionally, the robustness of recovery from compressed sensing, allows a new form of "Robust encryption" for multimedia data, wherein the signal is recoverable with high fidelity despite the introduction of additive noise in the encrypted data.
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