A. James Clark School of Engineering
Permanent URI for this communityhttp://hdl.handle.net/1903/1654
The collections in this community comprise faculty research works, as well as graduate theses and dissertations.
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Item Effective Iterative Techniques for Fingerprinting Design IP(IEEE, 1999-06) Caldwell, Andrew E.; Choi, Hyun-Jin; Kahng, Andrew B.; Mantik, Stefanus; Potkonjak, Miodrag; Qu, Gang; Wong, Jennifer L.While previous watermarking-based approaches to intellectual property protection (IPP) have asymmetrically emphasized the IP provider’s rights, the true goal of IPP is to ensure the rights of both the IP provider and the IP buyer. Symmetric 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. In this paper, we propose the first generic symmetric fingerprinting technique which can be applied to an arbitrary optimization/synthesis problem and, therefore, to hardware and software intellectual property. The key idea is to apply iterative optimization in an incremental fashion to solve a fingerprinted instance; this leverages the optimization effort already spent in obtaining a previous solution, yet generates a uniquely fingerprinted new solution. We use this approach as the basis for developing specific fingerprinting techniques for four important problems in VLSI CAD: partitioning, graph coloring, satisfiability, and standard-cell placement. We demonstrate the effectiveness of our fingerprinting techniques on a number of standard benchmarks for these tasks. Our approach provides an effective tradeoff between runtime and resilience against collusion.Item Effective Iterative Techniques for Fingerprinting Design IP(IEEE, 2004-01) Caldwell, Andrew E.; Choi, Hyun-Jin; Kahng, Andrew B.; Mantik, Stefanus; Potkonjak, Miodrag; Qu, Gang; Wong, Jennifer L.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 fingerprinting 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 functionally and timing identical designs. To reduce the cost of generating such distinct copies, we apply iterative optimization in an incremental fashion to solve a fingerprinted instance. Therefore, we leverage on the optimization effort already spent in obtaining previous solutions, yet we generate a uniquely fingerprinted new solution. This generic approach is the basis for developing specific fingerprinting techniques for four important problems in VLSI CAD: partitioning, graph coloring, satisfiability, and standard-cell placement. We demonstrate the effectiveness of the new fingerprinting-based IPP techniques on a number of standard benchmarks.