Office BC 262


Research interests:

  • Information leakage estimation for security&privacy
  • Theory and foundations of Machine Learning
  • Methods for distribution-free confident prediction in supervised learning and anomaly detection (e.g., Conformal Predictors)
  • Traffic analysis, Machine Learning in adversarial conditions, and their formal analysis

Have a look at a list of recent projects.

I co-founded and play with the CTF team TU6PM.

I am a (happy) OpenBSD user, and I would highly encourage you become too.


Jul 25, 2019 My PhD thesis is now available online. Highlights here.
Feb 28, 2019 Our paper, “F-BLEAU: Fast Black-box Leakage Estimation”, has been accepted by the IEEE Symposium on Security and Privacy, 2019. It shows how to use ML methods for measuring the information leakage of a black-box system in a practical yet theoretically sound manner.
Dec 16, 2018 The code of fbleau for measuring the leakage of black box systems is now online and available for installation via crates.io.
Nov 6, 2018 A list of semester projects for EPFL MSc/PhD students is available at https://spring.epfl.ch/en/projects.
Sep 3, 2018 Work on Conformal Predictors' ensebles accepted by the Machine Learning journal (read more)


Some recent projects.


  1. F-BLEAU: Fast Black-box Leakage Estimation Cherubin, Giovanni, Chatzikokolakis, Konstantinos, and Palamidessi, Catuscia In IEEE Symposium on Security and Privacy (S&P) 2019 [Abs] [Paper] [Video]
  2. Black-box Security: Measuring Black-box Information Leakage via Machine Learning Cherubin, Giovanni PhD thesis 2019 [PDF]
  3. Majority vote ensembles of conformal predictors Cherubin, Giovanni Machine Learning 2018 [Paper] [Url]
  4. Exchangeability martingales for selecting features in anomaly detection Cherubin, Giovanni, Baldwin, Adrian, and Griffin, Jonathan In Proceedings of the Seventh Workshop on Conformal and Probabilistic Prediction and Applications 2018 [Abs] [Paper] [Url] [Slides] [Code]
  5. Bayes, not Naïve: Security Bounds on Website Fingerprinting Defenses Cherubin, Giovanni Proceedings on Privacy Enhancing Technologies 2017 Best student paper [Paper] [Slides] [Code] [Video]
  6. Website Fingerprinting Defenses at the Application Layer Cherubin, Giovanni, Hayes, Jamie, and Juarez, Marc Proceedings on Privacy Enhancing Technologies 2017 [Abs] [Paper] [Code]
  7. Hidden Markov Models with Confidence Cherubin, Giovanni, and Nouretdinov, Ilia In Conformal and Probabilistic Prediction with Applications - 5th International Symposium, COPA 2016 [Paper] [Slides]
  8. Conformal Clustering and Its Application to Botnet Traffic Cherubin, Giovanni, Nouretdinov, Ilia, Gammerman, Alexander, Jordaney, Roberto, Wang, Zhi, Papini, Davide, and Cavallaro, Lorenzo In Statistical Learning and Data Sciences (SLDS) 2015 Best student paper [Paper] [Slides]
  9. Bots detection by Conformal Clustering Cherubin, Giovanni MSc thesis, Royal Holloway University of London 2014 [PDF]


Selected invited talks.

  1. Measuring the Security of Machine Learning models 2019 Third ITU/WHO Workshop on "Artificial Intelligence for Health" [Slides]
  2. Measuring the Leakage of a Black-box using Machine Learning 2018 Alan Turing Institute, London [Slides] [Video]
  3. Bayes, not Naïve: Provable Security of Website Fingerprinting Defenses 2017 ISG Seminar, Royal Holloway University of London, UK [Slides]
  4. On the Security Against Machine Learning-based Attacks 2017 CDT Showcase, Evelyn Sharp Centre, Sunningdale Park [Slides]
  5. Bayes, not Naïve: Security Bounds on Website Fingerprinting Defenses 2017 Security Seminar, University of Cambridge [Url]
  6. Applications of Conformal Prediction in Information Security Problems 2016 CDT Showcase, Windsor Great Park, UK [Slides]
  7. Conformal Clustering and Bots Traffic 2015 CPRML Workshop 2015, Hyderabad, India [Slides]

Research Visits

Research Engineer, HP Labs Security Lab, Bristol (August-November 2017)
Supervisors: Jonathan Griffin, Adrian Baldwin

Research Visitor, École Polytechnique, Paris (May; November 2017)
Supervisors: Prof. Catuscia Palamidessi, Kostas Chatzikokolakis

Research Intern, Cornell Tech (June-September 2016)
Supervisor: Prof. Thomas Ristenpart

Academic Service

I have been teaching assistant for R programming for the courses on Machine Learning and Data Analysis at Royal Holloway University of London (2014-17). I was teaching assistant for the courses on C programming and Linear Algebra and Geometry at University of Pavia (2011-12).

I am a PC member for COPA 2018, PC member for PETS (2019-2020), and have been external reviewer for Neurocomputing, PETS, and Financial Cryptography.


  • 2017, Best Paper: Andreas Pfitzmann Best Student Paper Award at PETS: “Bayes, not Naïve: Security Bounds on Website Fingerprinting Defenses”
  • 2017, First place at Capture The Flag (CTF) security challenge organised by NCC Group at the Cambridge2Cambridge event
  • 2015, Best Paper: Best student paper award sponsored by HP at SLDS conference: “Conformal Clustering and Its Application to Botnet Traffic”
  • 2014, Best Finalist: Best MSc in Big Data finalist in memory of Prof. Alexey Chervonenkis (Royal Holloway University of London)

Short bio

I am a postdoc researcher at EPFL (Switzerland) with an EcoCloud grant, collaborating with Carmela Troncoso at the SPRING lab and Martin Jaggi at the MLO lab. I achieved a PhD in Machine Learning and Information Security from Royal Holloway University of London with the Centre of Doctoral Training (CDT), where I was supervised by Alex Gammerman and advised by Kenny Paterson. I received an MSc in Machine Learning from Royal Holloway University of London in 2014, and a BSc in Mechatronics and Computer Engineering from University of Pavia in 2013.

My current research aims at measuring systems’ leakage by using methods from the Machine Learning theory; I applied this to side channel attacks (e.g., traffic analysis). I also worked on extending methods for confident prediction (e.g., Conformal Predictors), particularly in the context of clustering, anomaly detection, and classifiers ensembling.