Biblio

In this paper, a technique to design analog circuits with enhanced security is described. The proposed key based obfuscation technique uses a mesh topology to obfuscate the physical dimensions and the threshold voltage of the transistor. To mitigate the additional overhead of implementing the obfuscated circuitry, a satisfiability modulo theory (SMT) based algorithm is proposed to auto-determine the sizes of the transistors selected for obfuscation such that only a limited set of key values produce the correct circuit functionality. The proposed algorithm and the obfuscation methodology is implemented on an LC tank voltage-controlled oscillator (VCO). The operating frequency of the VCO is masked with a 24-bit encryption key applied to a 2×6 mesh structure that obfuscates the dimensions of each varactor transistor. The probability of determining the correct key is 5.96×10-8 through brute force attack. The dimensions of the obfuscated transistors determined by the analog satisfiability (aSAT) algorithm result in at least a 15%, 3%, and 13% deviation in, respectively, the effective transistor dimensions, target frequency, and voltage amplitude when an incorrect key is applied to the VCO. In addition, only one key produces the desired frequency and properly sets the overall performance specifications of the VCO. The simulated results indicate that the proposed design methodology, which quickly and accurately determines the transistor sizes for obfuscation, produces the target specifications and provides protection for analog circuits against IP piracy and reverse engineering.

Power-noise viruses can be used as denial-of-service attacks by causing voltage emergencies in multi-core microprocessors that may lead to data corruptions and system crashes. In this paper, we present a run-time system for detecting and mitigating power-noise viruses. We present voltage noise data from a power-noise virus and benchmarks collected from an Arm multi-core processor, and we observe that the frequency of voltage emergencies is dramatically increasing during the execution of power-noise attacks. Based on this observation, we propose a regression model that allows for a run-time estimation of the severity of voltage emergencies by monitoring the frequency of voltage emergencies and the operating frequency of the microprocessor. For mitigating the problem, during the execution of critical tasks that require protection, we propose a system which periodically evaluates the severity of voltage emergencies and adapts its operating frequency in order to honour a predefined severity constraint. We demonstrate the efficacy of the proposed run-time system.