Cryptographically Privileged State Estimation With Gaussian Keystreams

Abstract

State estimation via public channels requires additional planning with regards to state privacy and information leakage of involved parties. In some scenarios, it is desirable to allow partial leakage of state information, thus distinguishing between privileged and unprivileged estimators and their capabilities. Existing methods that make this distinction typically result in reduced estimation quality, require additional communication channels, or lack a formal cryptographic backing. We introduce a method to decrease estimation quality at an unprivileged estimator using a stream of pseudorandom Gaussian samples while leaving privileged estimation unaffected and requiring no additional transmission beyond an initial key exchange. First, a cryptographic definition of privileged estimation is given, capturing the difference between privileges, before a privileged estimation scheme meeting the security notion is presented. Achieving cryptographically privileged estimation without additional channel requirements allows quantifiable estimation to be made available to the public while keeping the best estimation private to trusted privileged parties and can find uses in a variety of service-providing and privacy-preserving scenarios.