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13 changes: 0 additions & 13 deletions docs/publications/bake-it-heat-leakage-eprint23.md

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13 changes: 13 additions & 0 deletions docs/publications/chypnosis.md
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title: "Chypnosis: Undervolting-based Static Side-channel Attacks"
paper_url: "https://ieeexplore.ieee.org/abstract/document/11573501"
year: 2026
---

![Chypnosis paper logo](/img/research/Chypnosis.jpeg)

Chypnosis is an undervolting attack that indirectly stops a target circuit's clock while preserving its stored data. By rapidly dropping the supply voltage, it can prevent both clock-monitoring defenses and voltage-sensor response mechanisms from clearing sensitive state. Demonstrations across multiple FPGAs, the OpenTitan alert handler, laser logic state imaging, and impedance analysis show that secrets can still be recovered from protected cryptographic hardware. The work also proposes and validates an improved FPGA-compatible clock-detection countermeasure.

*Mitard, K., Monfared, S.K., Dana, F.K., Dumitru, R., Yarom, Y., and Tajik, S.*

**[Read the paper](https://ieeexplore.ieee.org/abstract/document/11573501)**
13 changes: 0 additions & 13 deletions docs/publications/gate-level-sca-ranking-tetc23.md

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13 changes: 0 additions & 13 deletions docs/publications/goblin-acns24.md

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13 changes: 0 additions & 13 deletions docs/publications/leakyohm-ccs23.md

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13 changes: 13 additions & 0 deletions docs/publications/telescope.md
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title: "Telescope: Top-Down Hierarchical Pre-silicon Side-channel Leakage Assessment in System-on-Chip Design"
paper_url: "https://dl.acm.org/doi/full/10.1145/3708821.3736216"
year: 2025
---

![Telescope paper logo](/img/research/Telescope.png)

Telescope is a top-down framework for assessing side-channel leakage before silicon is available. It traces leakage across architecture, microarchitecture, and gate levels to reveal how software-level behavior propagates into hardware—and where leakage progressively appears, emerges, or disappears. Evaluations on the PicoRV32 and IBEX RISC-V processors demonstrate how this cross-level view can scale to practical leakage debugging and verification.

*Liu, Z., Malnicof, A., Roy, A., and Schaumont, P.*

**[Read the paper](https://dl.acm.org/doi/full/10.1145/3708821.3736216)**
13 changes: 13 additions & 0 deletions docs/publications/uncertainty-estimation.md
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title: "Uncertainty Estimation in Neural Network-enabled Side-channel Analysis and Links to Explainability"
paper_url: "https://tches.iacr.org/index.php/TCHES/article/view/12908"
year: 2026
---

![Uncertainty estimation paper logo](/img/research/Uncertainty.png)

This work introduces a Rényi entropy-based framework for measuring uncertainty in neural network-assisted side-channel analysis and explaining its effect on key recovery. It separates model-related and data-related uncertainty, uses matrix-based Rényi measures to approximate high-dimensional leakage distributions, and combines Shapley-value explanations with uncertainty estimates to identify influential trace features. Experiments show that predictive uncertainty strongly correlates with established attack metrics such as key rank.

*Nouraniboosjin, S., and Ganji, F.*

**[Read the paper](https://tches.iacr.org/index.php/TCHES/article/view/12908)**
10 changes: 0 additions & 10 deletions news/2022-12-09-ches-impedance-sensing.md

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10 changes: 0 additions & 10 deletions news/2023-05-25-jolt-rowhammer-ieeesp.md

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12 changes: 0 additions & 12 deletions news/2023-10-23-goblin-timing-attack.md

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10 changes: 0 additions & 10 deletions news/2023-11-10-leakyohm-ccs-2023.md

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