Unveiling ECC Vulnerabilities: LSTM Networks for Operation Recognition in Side-Channel Attacks

2025-02-24

AI Summary

This work addresses a combined power-consumption and timing leakage in ECDSA scalar multiplication, arising from key-dependent conditional modular reduction. We propose a fine-grained side-channel analysis method based on Long Short-Term Memory (LSTM) networks. Evaluated on the micro-ecc implementation deployed on an STM32F415 embedded platform, our approach is the first to employ LSTM models to detect key-dependent modular reduction operations with high precision, enabling accurate operation localization and recovery of intermediate secret key bits—ultimately leading to full long-term private key reconstruction. Crucially, our experiments demonstrate that widely adopted countermeasures—including coordinate randomization—fail to mitigate this microarchitectural-level leakage. The study thus establishes a new empirical benchmark for ECC side-channel security assessment and provides concrete evidence of the vulnerability’s practical exploitability.

Technology Category

• Machine Learning: Large Multimodal Models (LMMs)
• Data Mining & Knowledge Management: Anomaly/Outlier Detection
• Computer Vision: Adversarial Attacks & Robustness

Application Category

• Security and Privacy: Large-scale security measurements
• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems
• Economics, Online Markets and Human Computation: Cost models of using LLMs in production systems

Abstract

We propose a novel approach for performing side-channel attacks on elliptic curve cryptography. Unlike previous approaches and inspired by the ``activity detection'' literature, we adopt a long-short-term memory (LSTM) neural network to analyze a power trace and identify patterns of operation in the scalar multiplication algorithm performed during an ECDSA signature, that allows us to recover bits of the ephemeral key, and thus retrieve the signer's private key. Our approach is based on the fact that modular reductions are conditionally performed by micro-ecc and depend on key bits. We evaluated the feasibility and reproducibility of our attack through experiments in both simulated and real implementations. We demonstrate the effectiveness of our attack by implementing it on a real target device, an STM32F415 with the micro-ecc library, and successfully compromise it. Furthermore, we show that current countermeasures, specifically the coordinate randomization technique, are not sufficient to protect against side channels. Finally, we suggest other approaches that may be implemented to thwart our attack.

Problem

• Identify operation patterns in ECC
• Recover ephemeral key bits
• Compromise STM32F415 device

Innovation

• LSTM for power trace analysis
• Recover key via operation patterns
• Tested on STM32F415 device