Work

The effect of ECG data variability on side-channel attack success rate in wearable devices

Year: 2025

Type: article

Abstract: As the connectivity and number of health monitoring devices has increased dramatically in recent years, various security issues have become a serious threat to the integrity of patient data. Side-channel attacks are particularly dangerous for these devices because they do not rely on the mathematical complexity of the cryptographic algorithm, but instead exploit physical information leakage. In this work, we analyze electromagnetic and power side-channel attacks on portable electrocardiogram (ECG) monitoring devices. Unlike other work that uses random data, we analyze attacks based on real ECG data and show that the data distribution significantly affects the success rate of the attacks. We build a wearable ECG garment that records a single-lead ECG and sends it to a low-power microcontroller for encryption using AES. The results show that the first-round attack success rate is strongly influenced by the number of bits used to encrypt each ECG sample and the intensity level of the patient’s physical activity. More intense activity produces more artifacts in the ECG that increase the overall signal variability. An increase in variability generally results in an 86% reduction in the number of power samples required for an attack. The final attack also shows a dependence on input variability, but to a lesser extent. Input data with higher variability reduces the number of traces required for this attack by up to 50%, and the attack only becomes unsuccessful in the presence of extremely high levels of noise during the ECG recording. Based on these results, mitigation measures that exploit a change in signal variability are proposed. • A low-cost platform is designed to explore vulnerabilities to side-channel attacks. • The low variability of biomedical signals makes side-channel attacks difficult. • The signal quality in wearable monitors affects vulnerability to attacks. • Data encoding before encryption in low-power devices is a promising countermeasure.

Source: Integration

DOI: 10.1016/j.vlsi.2025.102385

Authors: Pablo Perez-Tirador, Ruzica Jevtic, Carmen Cabezaolias, Teresa Romero, Abraham Otero, Gabriel Caffarena

Institutions: Universidad San Pablo CEU, Universidad Politécnica de Madrid

Language: English

Topic: Cryptographic Implementations and Security

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: hybrid

Estimated APC paid: $2,230