Biblio

Reversible logic is a building block for adiabatic and quantum computing in addition to other applications. Since common functions are non-reversible, one needs to embed them into proper-size reversible functions by adding ancillary inputs and garbage outputs. We explore the Intellectual Property (IP) piracy of reversible circuits. The number of embeddings of regular functions in a reversible function and the percent of leaked ancillary inputs measure the difficulty of recovering the embedded function. To illustrate the key concepts, we study reversible logic circuits designed using reversible logic synthesis tools based on Binary Decision Diagrams and Quantum Multi-valued Decision Diagrams.

Reversible circuits are vulnerable to intellectual property and integrated circuit piracy. To show these vulnerabilities, a detailed understanding on how to identify the function embedded in a reversible circuit is crucial. To obtain the embedded function, one needs to know the synthesis approach used to generate the reversible circuit in the first place. We present a machine learning based scheme to identify the synthesis approach using telltale signs in the design.