Security: The Dark Side of Approximate Computing?

Abstract

Approximate computing promises significant advantages over more traditional computing architectures with respect to circuit area, performance, power efficiency, flexibility, and cost. Its use is suitable in applications where limited and controlled inaccuracies are tolerable or uncertainty is intrinsic in input or their data processing, e.g., as it happens in (deep-) machine learning, image and signal processing. This paper discusses a dimension of approximate computing that has been neglected so far, despite it represents nowadays a major asset, that of security. A number of hardware-related security threats are considered, and the implications of approximate circuits or systems designed to address these threats are discussed.