Exploiting Process Variations to Secure Photonic NoC Architectures from Snooping Attacks
Not on the map. Why?
Abstract (arXiv)
The compact size and high wavelength-selectivity of microring resonators (MRs) enable photonic networks-on-chip (PNoCs) to utilize dense-wavelength-division-multiplexing (DWDM) in their photonic waveguides, and as a result, attain high bandwidth on-chip data transfers. Unfortunately, a Hardware Trojan in a PNoC can manipulate the electrical driving circuit of its MRs to cause the MRs to snoop data from the neighboring wavelength channels in a shared photonic waveguide, which introduces a serious security threat. This paper presents a framework that utilizes process variation-based authentication signatures along with architecture-level enhancements to protect against data-snooping Hardware Trojans during unicast as well as multicast transfers in PNoCs. Evaluation results indicate that our framework can improve hardware security across various PNoC architectures with minimal overheads of up to 14.2% in average latency and of up to 14.6% in energy-delay-product (EDP).
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 20 Jul 2020.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 1; 2022: 0; 2023: 0; 2024: 1; 2025: 0; 2026: 1.
3 papers.
- 2021BPLight-CNN: A Photonics-based Backpropagation Accelerator for Deep Learningcited by 4
- 2024Optical Computing for Deep Neural Network Acceleration: Foundations, Recent Developments, and Emerging Directionscited by 0
- 2026Hardware Trojan Threats to Multi-Chiplet Photonic Neural Network Acceleratorscited by 0
- 2026Hardware Trojan Threats to Multi-Chiplet Photonic Neural Network Accelerators6 Sep 2026
- 2024Optical Computing for Deep Neural Network Acceleration: Foundations, Recent Developments, and Emerging Directions30 Jul 2024
- 2021BPLight-CNN: A Photonics-based Backpropagation Accelerator for Deep Learning19 Feb 2021