Estimation Theoretic Optimal Encoding Design for Secure Transmission of Multiple Parameters

Abstract

During this time, he was involved in the inverse problems and fusion of multiple modality measurements. In 1993, he joined the

Estimation Theoretic Secure Communication via Encoder Randomization

“…r (θ) can be expressed as (27) with p(y|θ) representing the conditional PDF of the n observations for a given value of θ [33]. Also, due to (4), I…”

“…In [26], a robust parameter encoding approach is developed and the optimization is based on the worst-case CRB of the parameter in order to guarantee a certain level of estimation accuracy at the intended receiver. The results in [25] are extended to vector parameter estimation scenarios in [27]. The common assumption in [25]- [27] is that the encoding function is not available to the eavesdropper; hence, it acts like a secret key similarly to the assumption of flipping probabilities not being available to the eavesdropper in [22] and [24].…”

“…The results in [25] are extended to vector parameter estimation scenarios in [27]. The common assumption in [25]- [27] is that the encoding function is not available to the eavesdropper; hence, it acts like a secret key similarly to the assumption of flipping probabilities not being available to the eavesdropper in [22] and [24]. On the other hand, for determining fundamental security limits of many systems (such as those investigated in the classical information theoretical framework), it is a common practice to assume that the eavesdropper has the full knowledge of the encoding strategy at the transmitter.…”

“…As the encoding strategy is available to the eavesdropper, the encoder randomization is allowed to increase ambiguity to possibly enhance security. The work in this manuscript is distinguished from [25]- [27] as it assumes that the mapping strategy is available to both the eavesdropper and the receiver (i.e., not secret), allows stochastic encoding in the transmitter, considers multiple observations rather than a single one, and employs different performance metrics leading to a distinct optimization problem. It is also different from those studies (such as [22], [23]) that allow stochastic encryption as it considers direct encoding of a random parameter rather than a measured deterministic one.…”

Optimal Parameter Design for Estimation Theoretic Secure Broadcast

“…In [2] and [3], the optimal deterministic encoding of a random scalar parameter is investigated to minimize the expectation of conditional Cramér-Rao bound (ECRB) and the worst-case Fisher information of the parameter at the intended receiver, respectively, while ensuring a certain estimation error at the eavesdropper. In [4], secure transmission of a vector parameter is investigated and practical encoding strategies are introduced. In [5], estimation theoretic security is investigated when the encoder at the transmitter is allowed to use a randomized mapping with two functions and the eavesdropper is fully aware of the encoding strategy.…”