Security Analysis for SCONE Logic Locking
2026-07-03 • Cryptography and Security
Cryptography and Security
AI summaryⓘ
The authors analyze two versions of SCONE, a logic locking technique that adds extra encoded inputs to protect hardware designs. They find that the version without an encoding stage doesn't really add new security dimensions because the extra inputs are predictable linear functions, making the design easier to attack. For the version with the encoding stage, they develop a method to fully recover the encoding from the design itself, breaking its security. They validate their findings with experiments on standard benchmarks and propose a lightweight non-linear fix that avoids these vulnerabilities.
logic lockingencoded inputslinear encodingwhite-box attackblack-box attacknetlisthardware securityISCAS-85 benchmarksITC-99 benchmarksARM Cortex-M0
Authors
Akashdeep Saha, Mohammed Nabeel, Johann Knechtel, Michail Maniatakos, Ozgur Sinanoglu
Abstract
SCONE [DAC'25] expands a logic locking interface with additional encoded inputs derived from the original primary inputs, and admits two realizations: a \textit{with-ES} variant, where the critical encoding stage is implemented in hardware, and a \textit{without-ES} variant, where the locked design directly exposes an encoded interface of width $n+m$. We show that both realizations are vulnerable, but for different reasons. For the without-ES variant, we prove that, when the added encoded inputs are deterministic linear functions of the original inputs, the valid encoded-input space remains $n$-dimensional despite the nominal expansion to $n+m$ inputs. Hence, the widened interface does not yield $m$ additional or independent brute-force dimensions. For the with-ES variant, we present a polynomial-time white-box attack that exactly recovers the added-input count and the implemented linear encoding relation from the locked netlist, achieving 100\% recovery over all evaluated instances. We also develop a black-box procedure that certifies the same dimensionality collapse from valid encoded-input samples without reconstructing the hidden encoder. Experiments on ISCAS-85 and ITC-99 benchmarks validate both results, and we further demonstrate exact white-box recovery on an ARM Cortex-M0 RTL benchmark. Finally, we propose a lightweight non-linear mitigation and show that it does not exhibit the vulnerabilities identified in this paper under all representative attack sets considered in SCONE.