A Composable Design Space Exploration Framework to Optimize Behavioral Locking

PROCEEDINGS OF THE 2022 DESIGN, AUTOMATION & TEST IN EUROPE CONFERENCE & EXHIBITION (DATE 2022)(2022)

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摘要
Globalization of the integrated circuit (IC) supply chain exposes designs to security threats such as reverse engineering and intellectual property (IP) theft. Designers may want to protect specific high-level synthesis (HLS) optimizations or micro-architectural solutions of their designs. Hence, protecting the IP of ICs is essential. Behavioral locking is an approach to thwart these threats by operating at high levels of abstraction instead of reasoning on the circuit structure. Like any security protection, behavioral locking requires additional area. Existing locking techniques have a different impact on security and overhead, but they do not explore the effects of alternatives when making locking decisions. We develop a design-space exploration (DSE) framework to optimize behavioral locking for a given security metric. For instance, we optimize differential entropy under area or key-bit constraints. We define a set of heuristics to score each locking point by analyzing the system dependence graph of the design. The solution yields better results for 92% of the cases when compared to baseline, state-of-the-art (SOTA) techniques. The approach has results comparable to evolutionary DSE while requiring 100× to 400× less computational time.
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关键词
specific high-level synthesis optimizations,microarchitectural solutions,behavioral locking,circuit structure,security protection,locking techniques,locking decisions,design-space exploration framework,given security metric,score each locking point,composable design space exploration framework,integrated circuit supply chain,security threats,reverse engineering,intellectual property theft,high-level synthesis,HLS optimizations,design-space exploration,differential entropy
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