WASP NEST

About the Project

Autonomous systems are expected to form the backbone of tomorrow's smart, networked, information-driven world. Our ability to trust these systems requires them to be secure at all levels, including the physical implementation. However, an increasing number of attacks exploiting low-level hardware vulnerabilities (e.g. Spectre, Meltdown, Foreshadow, TLBleed, PortSmash, NetSpectre, and StarBleed) highlight the lack of widely used, economically viable methods for ensuring tamper resistance.

One of the most common types of attacks on physical implementations are side-channel attacks. Side-channel attacks exploit non-primary, physically measurable information such as power consumption, electromagnetic emissions, or timing, to extract sensitive data. These attacks are particularly powerful when enhanced by machine learning techniques. Machine learning enables attackers to identify correlations in leakage without a heavy theoretical analysis of the targeted system.

This WASP NEST project aims to both develop novel side-channel attack techniques and design effective countermeasures, especially focusing on autonomous systems.

Research Objectives

• Advance understanding of possibilities and limitations of AI-driven side-channel attacks.
• Investigate new classes of remote side-channel attacks.
• Develop effective countermeasures against side-channel attacks.
• Assess the side-channel resistance of Trusted Execution Environments (TEE).

Research Team

The project is led by Prof. Elena Dubrova (KTH) in collaboration with Prof. Carl-Mikael Zetterling (KTH), Prof. Thomas Johansson (LTH), and Prof. Christian Gehrmann (LTH). It involves four PhD students: Yanning Ji (KTH), Sönke Jendral (KTH), Maggie Trân (LTH), and Markus Berthilsson (LTH).

Publications

1. Sönke Jendral, John Preuß Mattsson, and Elena Dubrova. A Single-Trace Fault Injection Attack on Hedged Module Lattice Digital Signature Algorithm (ML-DSA). In Proceedings of Workshop on Fault Detection and Tolerance in Cryptography (FDTC’2024), Halifax, Canada, Sept. 4, 2024, pp. 34-43. DOI: 10.1109/FDTC64268.2024.00013
2. Sönke Jendral and Elena Dubrova. MAYO Key Recovery by Fixing Vinegar Seeds. IACR Communications in Cryptology, vol. 1, no. 4, Jan. 13, 2025. DOI: 10.62056/ab0ljbkrz
3. Sönke Jendral and Elena Dubrova. Single-Trace Side-Channel Attacks on MAYO Exploiting Leaky Modular Multiplication. Cryptology ePrint Archive, Paper 2024/1850. 2024. https://eprint.iacr.org/2024/1850
4. Sönke Jendral and Elena Dubrova. Side-Channel and Fault Injection Attacks on VOLEitH Signature Schemes: A Case Study of Masked FAEST. Cryptology ePrint Archive, Paper 2025/378. 2025. https://eprint.iacr.org/2025/378
5. Yanning Ji, Elena Dubrova, and Ruize Wang. Is Your Bluetooth Chip Leaking Secrets via RF Signals? Real World Crypto (RWC’2025), Sofia, Bulgaria, March 26-28, 2025. https://eprint.iacr.org/2025/559
6. Yanning Ji, Elena Dubrova, and Ruize Wang. Screaming Channels Revisited: Encryption Key Recovery from AES-CCM Accelerator. In Proceedings of the IEEE International Symposium on Circuits and Systems (ISCAS'2025), London, UK, May 25-28, 2025.
7. Yanning Ji, Elena Dubrova, and Ruize Wang. Is Your Chip Leaking Secrets via RF Signals? In Proceedings of the IEEE International Symposium on Multiple-Valued Logic (ISMVL’2025), Montreal, Canada, June 5-6, 2025.
8. Elena Dubrova. Solving AES-SAT Using Side-Channel Hints: A Practical Assessment. In Proceedings of the IEEE International Symposium on Multiple-Valued Logic (ISMVL’2025), Montreal, Canada, June 5–6, 2025. https://eprint.iacr.org/2024/2079

Contact

Email: dubrova@kth.se

Affiliation: KTH The Royal Institute of Technology