Effective Iterative Techniques for

Fingerprinting is an approach that assigns a unique and invisible ID to each sold instance of the intellectual property (IP). One of the key advantages fingerprinting-based intellectual property protection (IPP) has over watermarking-based IPP is the enabling of tracing stolen hardware or software. Fingerprinting schemes have been widely and effectively used to achieve this goal; however, their application domain has been restricted only to static artifacts, such as image and audio, where distinct copies can be obtained easily. In this paper, we propose the first generic finger- printing technique that can be applied to an arbitrary synthesis (optimization or decision) or compilation problem and, therefore to hardware and software IPs. The key problem with design IP fingerprinting is that there is a need to generate a large number of structurally unique but func- tionally and timing identical designs. To reduce the cost of gener- ating such distinct copies, we apply iterative optimization in an in- cremental fashion to solve a fingerprinted instance. Therefore, we leverage on the optimization effort already spent in obtaining pre- vious solutions, yet we generate a uniquely fingerprinted new solu- tion. This generic approach is the basis for developing specific fin- gerprinting techniques for four important problems in VLSI CAD: partitioning, graph coloring, satisfiability, and standard-cell place- ment. We demonstrate the effectiveness of the new fingerprinting- based IPP techniques on a number of standard benchmarks.