Robert Dumitru (Ruhr University Bochum and The University of Adelaide), Thorben Moos (UCLouvain), Andrew Wabnitz (Defence Science and Technology Group), Yuval Yarom (Ruhr University Bochum)

In recent years a new class of side-channel attacks has emerged. Instead of targeting device emissions during dynamic computation, adversaries now frequently exploit the leakage or response behaviour of integrated circuits in a static state. Members of this class include Static Power Side-Channel Analysis (SCA), Laser Logic State Imaging (LLSI) and Impedance Analysis (IA). Despite relying on different physical phenomena, they all enable the extraction of sensitive information from circuits in a static state with high accuracy and low noise -- a trait that poses a significant threat to many established side-channel countermeasures.

In this work, we point out the shortcomings of existing solutions and derive a simple yet effective countermeasure. We observe that in order to realise their full potential, static side-channel attacks require the targeted data to remain unchanged for a certain amount of time. For some cryptographic secrets this happens naturally, for others it requires stopping the target circuit's clock. Our proposal, called Borrowed Time, hinders an attacker's ability to leverage such idle conditions, even if full control over the global clock signal is obtained. For that, by design, key-dependent data may only be present in unprotected temporary storage (e.g. flip-flops) when strictly needed. Borrowed Time then continuously monitors the target circuit and upon detecting an idle state, securely wipes sensitive contents.

We demonstrate the need for our countermeasure and its effectiveness by mounting practical static power SCA attacks against cryptographic systems on FPGAs, with and without Borrowed Time. In one case we attack a masked implementation and show that it is only protected with our countermeasure in place. Furthermore we demonstrate that secure on-demand wiping of sensitive data works as intended, affirming the theory that the technique also effectively hinders LLSI and IA.

View More Papers

Recurrent Private Set Intersection for Unbalanced Databases with Cuckoo...

Eduardo Chielle (New York University Abu Dhabi), Michail Maniatakos (New York University Abu Dhabi)

Read More

RACONTEUR: A Knowledgeable, Insightful, and Portable LLM-Powered Shell Command...

Jiangyi Deng (Zhejiang University), Xinfeng Li (Zhejiang University), Yanjiao Chen (Zhejiang University), Yijie Bai (Zhejiang University), Haiqin Weng (Ant Group), Yan Liu (Ant Group), Tao Wei (Ant Group), Wenyuan Xu (Zhejiang University)

Read More

Evaluating Machine Learning-Based IoT Device Identification Models for Security...

Eman Maali (Imperial College London), Omar Alrawi (Georgia Institute of Technology), Julie McCann (Imperial College London)

Read More

BARBIE: Robust Backdoor Detection Based on Latent Separability

Hanlei Zhang (Zhejiang University), Yijie Bai (Zhejiang University), Yanjiao Chen (Zhejiang University), Zhongming Ma (Zhejiang University), Wenyuan Xu (Zhejiang University)

Read More