Zero-Cost Security for Embedded Systems by Compressed Sensing

Compressed Sensing (CS) is a technique for the acquisition of signals using a number of measurements that is potentially much smaller than the number of samples at the Nyquist rate. It can be seen as an extremely simple encoding stage allowing a low cost compression. Yet, its intrinsic structure allows its re-use as a physical level public-key encryption layer thus preventing the need of a dedicated stage whenever the level of attained security is deemed sufficient. This often applies to non-critical embedded applications with tight resource budgets that may thus benefit from a single stage that simultaneously performs data compression and encryption. The talk describes the basics of CS and introduces the ideas behind its reuse as a low-cost encryption. Evaluations on the power and hardware saving due to a joint lossy compression and encryption are developed with emphasis on the fact that more of one public kay can be distributed allowing the reconstruction of the signals with different level of quality. To match the resulting resource saving with the level of security provided, a rigorous cryptanalysis is carried out. Statistical ciphertext-only attacks are analyzed as well as known-plaintext attacks to prove that, though not perfectly secure in the Shannon sense, the method still provides a quite strong computational security.