Effective Concurrent Attack Detection Framework through Laser Fault Informed Balanced Optical Neural Network Observation

Silicon Photonics-based AI Accelerators (SPAAs) have been considered as promising AI accelerators achieving high energy efficiency and low latency. While many researchers focus on improving SPAAs’ energy efficiency and latency, their physical security has only recently received attention. While it is essential to deliver strong optical neural network inferencing approaches, their success and adoption are predicated on their ability to deliver a secure execution environment. Towards this end, this paper extends PrometheusFree to PrometheusFreev2 , an optical neural network framework that is capable of concurrent detection of laser fault injection attacks. This paper first presents an illustrative threat of laser fault injection attacks on SPAAs, capable of subjecting the optical neural network to misclassifications. PrometheusFreev2 then addresses this threat by developing techniques for concurrent detection of the laser fault injection attacks. Furthermore, PrometheusFreev2 introduces an application of the Wavelength Division Perturbation (WDP) technique where wavelength-dependent Vector Matrix Multiplication (VMM) results are utilized to boost fault attack detection accuracy. This article goes on to introduce a novel optical vulnerability that overpowers the PrometheusFree detection capability, the swapping attack that exploits an architectural vulnerability of SPAAs. To address this practical and critical attack, PrometheusFreev2 features a dummy padding technique which injects random values to weight matrices to improve attack detectability. Simulation results show that PrometheusFreev2 achieves over 92% attack-caused misprediction recall as the use of the WDP technique squashes the attack success rate by 31–47% on average by using three wavelengths. Compared with prior art, PrometheusFreev2 constricts the average attack success ratio to 0.030, yielding a 92.8–95.0% reduction. The experimental results confirm the superiority of the concurrent detection and the boost in attack detection abilities imparted by the WDP and the dummy padding approaches.