LeGO is a learning-guided obfuscation framework that overcomes known vulnerabilities in a scalable and systematic manner, leading to a robust and lightweight locking mechanism.
The proposed framework is guided by our security evaluation process that performs a thorough assessment of an obfuscated IP against various attacks and identifies the vulnerabilities.
It then judiciously selects and applies a set of design modification steps or rules that can eliminate these vulnerabilities.
Such a rule-based obfuscation process has the distinctive capability to address all existing as well as emerging attacks through the learning of appropriate design transformation steps that prevent these attacks.
We present an efficient strategy to apply these rules on a design, while resolving any conflict.
