I am a Principal Research Scientist co-leading the AI for Cyberdefence (AICD) Research Center at the Alan Turing Institute, London, UK.

My research interests lie in the intersection of Systems Security and Machine Learning (i.e., ML4Sec). This includes autonomous network defence, large traffic analysis models, and active/adaptive adversaries. I am passionate about deep reinforcement learning and its applications in security problems.

In the past, I have worked on a variety of projects (see Publications and Scholar). Snappy is a fast-payment solution for slow permissionless blockchains. Myst is a high-assurance cryptographic hardware prototype which was the first trojan-resilient deployment that achieved performance similar to that of conventional hardware security modules used in production (CSAW 2018 Competition Finalist). Our study on ultrasound tracking received wide-spread attention and is considered the seminal work in this area. With Petr Svenda, we released the first open-source cryptographic library for JavaCards. Finally, I have published a stream of papers studying market fairness & manipulation as security problems.

I hold a PhD in the Information Security Group at University College London with Prof. George Danezis.

My research has been published in various top-tier conferences such as the ACM Conference on Computer and Communications Security (CCS), the Privacy Enhancing Technologies Symposium (PETs) and the Network & Distributed System Security Symposium (NDSS). I have been kindly supported by Oasis Labs, Binance Labs, the Allan & Nesta Ferguson Charitable Trust and the UCL Public Engagement Unit. I have also been honored to be in the 10-of-200 young researchers' list by the Heidelberg Laureate Forum, a recipient of the Werner Romberg Grant, as well as a finalist at the CSAW Europe 2018 Applied Research Competition.

Vasilios Mavroudis

vmavroudis at turing.ac.uk
Defence and Security programme
Alan Turing Institute
96 Euston Rd
London NW1 2DB
United Kingdom

Recent News

December 2019: Our paper on fast decentralized on-chain payments was accepted at NDSS 2020 and is a finalist for the Spark Award! August 2019: Our paper on neural net-based side-channel attacks was accepted at IACR Asiacrypt 2019! July 2019: Our paper with Refinitiv will appear at the ACM conference on Advances in Financial technologies! June 2019: I was awarded one of the three Oasis Labs' fellowships for 2019-2020! May 2019: Our project on market manipulation is live! Visit our website here: Tradescope Feb 2019: I will attend the 3rd AI Safety Camp to work on Intelligent Agent side-effects and ML Robustness! Feb 2019: Stream of works on "Market manipulation as a security problem" accepted on Eurosec 2019 and the 27th Workshop on Security Protocols! Jan 2019: My interview at the Heidelberg Laureate Forum is now online! [Link] Jan 2019: I am a fellow in the ConceptionX commercialization and entrepreneurship program! Jan 2019: I completed a 5-course Deep Learning Specialization on Coursera! [Link] [1, 2, 3, 4, 5] Nov 2018: I was awarded a grant from the generous Allan & Nesta Ferguson Charitable Trust! [Link] Oct 2018: Our paper ''High-Assurance Cryptographic Hardware from Untrusted Components'' is a finalist for the CSAW Europe Applied Research Award. [Link] Oct 2018: I'm quoted in ''Wired'' about our work on hardware trojans. [Link] Sep 2018: My interview on Süddeutsche Zeitung is online. [Link] Sep 2018: I am listed in the 10 out of 200 young scientists by Heidelberg Laureate Forum! [Link] Sep 2018: Our article on Javacard was published at Hackernoon! [Link] Aug 2018: Our "Cryptogame" session proposal has been accepted in Mozfest 2108. [Link] Aug 2018: Our "Cryptogame" project has been funded by the public engagement unit at UCL. [Link] July 2018: Received the Werner Romberg grant to attend the Heidelberg Laureate Forum! [Link] Jul 2018: Our write up on the JavaCard ecosystem was published by the Software Sustainability Institute and the Benthem's Gaze blog. [Link 1] [Link 2] Jun 2018: Thrilled to serve as a publications co-chair for the Privacy Enhancing Technologies symposium 2019. [Link] May 2018: Our preprint on verifiable data access is out. [Link] May 2018: Started my research visit at the systems security group in ETHz. [Link] Apr 2018: Cyber World Magazine features my article on the future of hardware-trojans and the security of chips in critical systems. [Link] Apr 2018: Presented our work on ultrasonic signals at Stanford security seminar. [Link] Apr 2018: More press coverage for our work on ultrasonic signals. [Link] Apr 2018: Presented with Giovanni Vigna (UCSB, Lastline) our work on the security of ultrasonic communications at RSA Conference. [Link] Mar 2018: Our preprint on tracking technologies found in the retail spaces is out. [Link] Feb 2018: Completed our cryptography masterclass for year-11 students. [Link]

Selected Projects


Encrypted Traffic Classification using High-dimensional Embeddings

This project studies the resilience of encrypted-communications schemes against adversaries that intent to breach the privacy of individual users. To evaluate widely-used schemes, we employ deep neural network models so as to map encrypted traffic traces into high-dimensional representations (see figure on the left). This enables us to generate a database of labeled traces that can then be used to classify unlabeled samples based on their proximity. Our results show that communication patterns suffice to reconstruct user activity with high accuracy and thus widely-deployed encrypted-communications systems offer weaker privacy guarantees than previously thought. This paper and the corresponding defence tools are currently under submission.


Information Leakage Classification with Deep Neural Networks

Near-field microprobes have the capability to isolate small regions of a chip surface and enable precise measurements with high spatial resolution. Being able to distinguish the activity of small regions has given rise to attacks that exploit the spatial dependencies of cryptographic algorithms in order to recover the secret key. This project introduces a set of techniques that allow security researchers to evaluate the leakage properties of any chip. We show that deep neural network models outperform previously proposed methods (e.g., difference of means, multivariate templates), especially in the context of single-shot classification and small memory regions. We validate the practicality of our proposed models by classifying the leakages from the SRAM of a modern ARM Cortex-M4 chip. Our results show that we were able to always distinguish the activity between 2 SRAM regions of 128 bytes each, while for 256 SRAM single-byte regions we achieve 32% accuracy.



MultiBallot: A Scheme for Privacy-preserving, Verifiable Statistics

Processing sensitive data for scientific purposes has the potential to bring substantial benefits both to individuals and society, however, it also requires strong guarantees that the data will not be used inappropriately. This project attempts to address some of the open challenges in the area: 1) effective ways to hold data processors accountable, 2) preserving the privacy of individuals and 3) protect the integrity of their data. For this purpose, we introduce MultiBallot, a privacy-preserving scheme that allows organizations to publish statistics derived from sensitive user data without breaching the privacy of the individual data subjects. Our scheme is based on ThreeBallot, a paper-voting design that allows voters to verify both the result of the elections (univariate operation) and that their individual vote was counted towards it. Our work extends this scheme and enables users to compute multivariate statistics on the published data. Moreover, MultiBallot can provide strong data integrity guarantees and public verifiability, when combined with a high-integrity data structure (e.g., a blockchain). These additional features make MultiBallot applicable in a wide range of data-processing scenarios such as healthcare statistics and communication records.



Leakage-Resilient Protocols for Cryptographic Operations

Cryptographic devices used in critical applications operate under the assumption that hardware components remain always compliant with their specifications. Consequently, components that contain intentional or unintentional errors (e.g., bugs, hardware trojans, backdoors) cannot reliably maintain any of their security properties. In this work, we relax this strict correctness requirement and demonstrate how trusted, high-assurance hardware can be built from untrusted and potentially malicious components. We employ more than a hundred COTS secure cryptocoprocessors, verified to FIPS140-2 Level 4 tamper-resistance standards, and use them to realize high-confidentiality random number generation, key derivation, public key decryption and signing. Our experiments show a reasonable computational overhead (less than 1% for both Decryption and Signing) and an exponential increase in backdoor-tolerance as more ICs are added.

[Paper] [Code]


Peer-reviewed & Preprints

Location, location, location: Revisiting modeling and exploitation for location-based side channel leakages. [PDF]
Andrikos C., Batina L., Chmielewski L., Lerman L., Mavroudis V., Papagiannopoulos K., Perin G., Rassias G., Sonnino A.,
25th Annual International Conference on the Theory and Application of Cryptology and Information Security, Asiacrypt 2019
Libra: Fair Order-Matching for Electronic Financial Exchanges. [PDF]
Mavroudis V., Melton H., Advances in Financial Technologies AFT 2019, October 2019
Bounded Temporal Fairness for FIFO Financial Markets. [PDF]
Mavroudis V., 26th International Workshop on Security Protocols SPW, April 2019
Market Manipulation as a Security Problem: Attacks and Defenses [PDF]
Mavroudis V., 12th European Workshop on Systems Security EuroSec, March 2019
Snappy: Fast Blockchain Payments [PDF]
Mavroudis V., , Wuest K., Dhar A., Kostiainen K., Capkun S., Network & Distributed System Security Symposium (NDSS), Feb 2020
Towards Low-level Cryptographic Primitives for JavaCards.
Mavroudis V., Svenda P., Oct 2018
VAMS: Verifiable Auditing of Access to Confidential Data.
Hicks A., Mavroudis V., Al-Bassam M., Meiklejohn S., Murdoch S., May 2018
Eavesdropping Whilst Youre Shopping: Balancing Personalisation and Privacy in Connected Retail Spaces [PDF]
Mavroudis V., Veale M. (Equal Contribution), PETRAS/IoTUK/IET Living in the IoT Conference, 2018.
A Touch of Evil: High-Assurance Cryptographic Hardware from Untrusted Components [PDF, ArXiv]
Mavroudis V., Cerulli A., Svenda P., Cvrcek D., Klinec D., Danezis G., 24th ACM Conference on Computer and Communications Security CCS, 2017.
CSAW 2018 Applied Research Competition Finalist.
On the Privacy and Security of the Ultrasound Tracking Ecosystem [PDF]
Mavroudis V., Hao S., Fratantonio Y., Maggi F., Kruegel C., Vigna G., Proceedings of the Privacy Enhancing Technologies Symposium PETs, 2017
Visual Analytics for Enhancing Supervised Attack Attribution in Mobile Networks [PDF]
Papadopoulos S., Mavroudis V., Drosou A., Tzovaras D., 29th International Symposium on Computer and Information Sciences, 2014

Technical Reports

The Ultrasound Tracking Ecosystem.
Vasilios Mavroudis, Shuang Hao, Yanick Fratantonio, Federico Maggi, Giovanni Vigna, and Christopher Kruegel. November 2016
Correlation Analysis and Abnormal Event Detection Module.
EU FP7 Project: Enhanced Network Security for Seamless Service Provisioning in the Smart Mobile Ecosystem
Anomaly detection based on real-time exploitation of billing systems.
EU FP7 Project: Enhanced Network Security for Seamless Service Provisioning in the Smart Mobile Ecosystem
Anomaly detection within femtocell architectures.
EU FP7 Project: Enhanced Network Security for Seamless Service Provisioning in the Smart Mobile Ecosystem
Network information sources.
EU FP7 Project: Enhanced Network Security for Seamless Service Provisioning in the Smart Mobile Ecosystem


Crux: Privacy-preserving Statistics for Tor, Information Security Group, University College London, UK, 2015.
Supervisor: George Danezis
Cassiopeia: Real-time mobile security monitoring system, Dept. of Applied Informatics, University of Macedonia, Greece, 2012.
Supervisor: Ioannis Mavridis


Libra: Fair Order-Matching for Electronic Financial Exchanges., Juels Group Research Meeting, Online/Cornell University, New York, US, 29 October 2019. [Link] Cryptographic Hardware from Untrusted Components, RISE Annual Conference, London, UK, 14 November 2018. [Link] A touch of Evil: Cryptographic Hardware from Untrusted Components (poster), CSAW 2018, Valence, France, 9 November 2018. Cryptogame: Pirates & Guardians of the Galaxy, London, UK, 27 October 2018. [Link] High-Assurance Cryptographic Hardware from Untrusted Components. Stanford Security Seminar, Palo Alto, US, 19 April 2018. [Link] The Good, the Bad and the Ugly of the Ultrasonic Communications Ecosystem. RSA Conference 2018, San Fransisco US, 17 April 2018. [Link] A witch-hunt for trojans in our chips. London Enterprise Tech Meetup, London, UK, 12 February 2018. [Link] Cryptographic Hardware from Untrusted Components. Cryptacus Workshop, Nijmegen, Netherlands, 16-18 November 2017. [Link] Cryptographic Hardware from Untrusted Components. IMDEA Software Inst., Madrid, Spain, 28 Sept 2017. [Link] Towards Trojan-tolerant Cryptographic Hardware. ZISC Seminar ETH, Zurich, Switzerland, 20 Sept 2017. [Link] OpenCrypto: Unchaining the JavaCard Ecosystem. Blackhat US, Las Vegas, US, 22-27 July 2017. [Link] Trojan-tolerant Hardware & Supply Chain Security in Practice. Defcon 25, Las Vegas, US, 27-30 July 2017. [Link] On the Privacy & Security of the Ultrasound Tracking Ecosystem. Computer Laboratory Security Seminar, Cambridge, UK, 21 February 2017. [Link] Talking Behind Your Back: On the Privacy & Security of the Ultrasound Tracking Ecosystem. Mozilla International Privacy Day, London, UK, 28 Jan 2017. [Link] Talking Behind Your Back: On the Privacy & Security of the Ultrasound Ecosystem. Information Security Seminar, UCL, London, UK, 19 January 2017. [Link] Talking Behind Your Back: Tough Love for the Ugly Ultrasound Tracking Ecosystem. Chaos Communication Congress, Hamburg, Germany, 27-30 Dec. 2016. [Link] Cross-device Tracking Canaries. Data Transparency Lab Conference 2016, New York, US, 17-19 Nov 2017. [Link] Talking Behind Your Back: Attacks and Countermeasures of Ultrasonic Cross-device Tracking. Blackhat Europe, London, UK, 3–4 November 2016. [Link][Slides] Cassiopeia: Mobile security monitoring. FOSS conference 2011, Greece.

Academic Service & Teaching

Publications co-chair for the Privacy Enhancing Technologies symposium 2019. Co-organizing the Hacking Seminars at UCL (2017-2018). Organizing the Information Security Seminars at UCL (2017-2018). External Reviewer for Privacy Enhancing Technologies Symposium (2017-2019). Teaching Assistant for Computer Security I module, Information Security MSc (Winter term 2017-2018). Guest Lecture on Acedemic Research, In2ScienceUK Organization (August 2017). Teaching Assistant for Computer Security II module, Information Security MSc (Spring term 2016-2017).