Biblio
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LL-ATPG: Logic-Locking Aware Test Using Valet Keys in an Untrusted Environment. 2021 IEEE International Test Conference (ITC). :180—189.
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2021. The ever-increasing cost and complexity of cutting-edge manufacturing and test processes have migrated the semiconductor industry towards a globalized business model. With many untrusted entities involved in the supply chain located across the globe, original intellectual property (IP) owners face threats such as IP theft/piracy, tampering, counterfeiting, reverse engineering, and overproduction. Logic locking has emerged as a promising solution to protect integrated circuits (ICs) against supply chain vulnerabilities. It inserts key gates to corrupt circuit functionality for incorrect key inputs. A logic-locked chip test can be performed either before or after chip activation (becoming unlocked) by loading the unlocking key into the on-chip tamperproof memory. However, both pre-activation and post-activation tests suffer from lower test coverage, higher test cost, and critical security vulnerabilities. To address the shortcomings, we propose LL-ATPG, a logic-locking aware test method that applies a set of valet (dummy) keys based on a target test coverage to perform manufacturing test in an untrusted environment. LL-ATPG achieves high test coverage and minimizes test time overhead when testing the logic-locked chip before activation without sharing the unlocking key. We perform security analysis of LL-ATPG and experimentally demonstrate that sharing the valet keys with the untrusted foundry does not create additional vulnerability for the underlying locking method.
A Faster Hardware Implementation of the AES S-box. 2021 IEEE 28th Symposium on Computer Arithmetic (ARITH). :123—130.
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2021. In this paper, we propose a very fast, yet compact, AES S-box, by applying two techniques to a composite field \$GF((2ˆ4)ˆ2)\$ fast AES S-box. The composite field fast S-box has three main components, namely the input transformation matrix, the inversion circuit, and the output transformation matrix. The core inversion circuit computes the multiplicative inverse over the composite field \$GF((2ˆ4)ˆ2)\$ and consists of three arithmetic blocks over subfield \$GF(2ˆ4)\$, namely exponentiation, subfield inverter, and output multipliers. For the first technique, we consider multiplication of the input of the composite field fast S-box by 255 nonzero 8-bit binary field elements. The multiplication constant increases the variety of the input and output transformation matrices of the S-box by a factor of 255, hence increasing the search space of the logic minimization algorithm correspondingly. For the second technique, we reduce the delay of the composite field fast S-box, by combining the output multipliers and the output transformation matrix. Moreover, we modify the architecture of the input transformation matrix and re-design the exponentiation block and the subfield inverter for lower delay and area. We find that 8 unique binary transformation matrices could be used to change from the binary field \$GF(2ˆ8)\$ to the composite field \$GF((2ˆ4)ˆ2)\$ at the input of the composite field S-box. We use Matla \$\textbackslashtextbackslashmathbfb\$ ® to derive all \$(255\textbackslashtextbackslashtimes 8=2040)\$ new input transformation matrices. We search the matrices for the fastest and lowest complexity implementation and the minimal one is selected for the proposed fast S-box. The proposed fast S-box is 24% faster (with 5% increase in area) than the composite field fast design and 10% faster (with about 1% increase in area) than the fastest S-box available in the literature, to the best of our knowledge.
Skew-Tent Map Based CMOS Random Number Generator with Chaotic Sampling. 2021 19th IEEE International New Circuits and Systems Conference (NEWCAS). :1—4.
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2021. Random number generators (RNGs) has an extensive application area from cryptography to simulation software. Piecewise linear one-dimensional (PL1D) maps are commonly preferred structures used as the basis of RNGs due to their theoretically proven chaotic behavior and ease of implementation. In this work, a skew-tent map based RNG is designed by using the chaotic sampling method in TSMC 180 nm CMOS process. Simulation data of the designed RNG is validated by the statistical randomness tests of the FIPS-140-2 and NIST 800-22 suites. The proposed RNG has three key features: the generated bitstreams can fulfill the randomness tests without using any post processing methods; the proposed RNG has immunity against external interference thanks to the chaotic sampling method; and higher bitrates (4.8 Mbit/s) can be achieved with relatively low power consumption (9.8 mW). Thus, robust RNG systems can be built for high-speed security applications with low power by using the proposed architecture.
Data-driven fault model development for superconducting logic. 2020 IEEE International Test Conference (ITC). :1—5.
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2020. Superconducting technology is being seriously explored for certain applications. We propose a new clean-slate method to derive fault models from large numbers of simulation results. For this technology, our method identifies completely new fault models – overflow, pulse-escape, and pattern-sensitive – in addition to the well-known stuck-at faults.
Analog cellular neural network for application in physical unclonable functions. 2016 IEEE International Symposium on Circuits and Systems (ISCAS). :2635–2638.
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2016. In this paper an analog cellular neural network is proposed with application in physical unclonable function design. Dynamical behavior of the circuit and its high sensitivity to the process variation can be exploited in a challenge-response security system. The proposed circuit can be used as unclonable core module in the secure systems for applications such as device identification/authentication and secret key generation. The proposed circuit is designed and simulated in 45-nm bulk CMOS technology. Monte Carlo simulation for this circuit, results in unpolarized Gaussian-shaped distribution for Hamming Distance between 4005 100-bit PUF instances.