TESSERACT

Framework for fair and sound evaluations of ML classifiers.

News

  • Dec 2024: TESSERACT selected as a finalist for [ACSAC's Artifacts Competition and Impact Award ](https://www.acsac.org/2024/program/artifacts_competition/)
  • Feb 2024: A preprint of TESSERACT (Extended Version) has been published on arXiv.
  • Jan 2019: TESSERACT accepted at USENIX Security 2019.
  • Oct 2018: Talk on TESSERACT accepted for USENIX Enigma 2019! More details soon.
  • Oct 2018: We are presenting our poster on TESSERACT's implementation at ACM CCS 2018.
    See you in Toronto, Canada!

Access

Tesseract is publicly available on GitHub. Prior to migrating to GitHub, Tesseract was hosted privately on BitBucket, and its access was given to the following institutions (alphabetical order):
  1. ANSSI - the French Network and Information Security Agency
  2. Boise State University, USA
  3. Birla Institute of Technology and Science, Pilani, India
  4. Capital One, USA
  5. Carnegie Mellon University, USA
  6. Czech Technical University, Czech Republic
  7. Deakin University, Australia
  8. Federal University of Paraná (UFPR), Brazil
  9. Georgia Tech, USA
  10. Huazhong University of Science and Technology (HUST), China
  11. King's College London, UK
  12. TU Dublin, Institute of Technology Blanchardstown, Ireland
  13. Nanjing University, Software Institute, China
  14. National Institute of Technology, Rourkela, India
  15. New York University, USA
  16. Northwest University, China
  17. Osaka University, Japan
  18. Rice University, USA
  19. Royal Holloway, University of London, UK
  20. Institute for Information Industry, Taiwan
  21. SnT - University of Luxembourg
  22. Swinburne University of Technology, Australia
  23. The Interdisciplinary Center Herzliya (IDC), Israel
  24. The MITRE Corporation, USA
  25. Tsinghua University, China
  26. TU Braunschweig, Germany
  27. TU Munich, Germany
  28. University of Bari Aldo Moro, Italy
  29. Universidad Carlos III de Madrid, Spain
  30. University of Cagliari, Italy
  31. University of Jinan, China
  32. University of New South Wales, Australia
  33. University of Toronto, Canada
  34. VIT Bhopal, India
  35. Washington State University, USA

Papers

TESSERACT: Eliminating Experimental Bias in Malware Classification across Space and Time (Extended Version)
Zeliang Kan, Shae McFadden, Daniel Arp, Feargus Pendlebury, Fabio Pierazzi, Roberto Jordaney, Johannes Kinder, and Lorenzo Cavallaro
arXiv · arXiv, 2024
@article{kan2024tesseract,
title={TESSERACT: Eliminating Experimental Bias in Malware Classification across Space and Time (Extended Version)},
author={Kan, Zeliang and McFadden, Shae and Arp, Daniel and Pendlebury, Feargus and Jordaney, Roberto and Kinder, Johannes and Pierazzi, Fabio and Cavallaro, Lorenzo},
journal={arXiv preprint arXiv:2402.01359},
year={2024}
}
INSOMNIA: Towards Concept-Drift Robustness in Network Intrusion Detection
Giuseppina Andresini and Feargus Pendlebury and Fabio Pierazzi and Corrado Loglisci and Annalisa Appice and Lorenzo Cavallaro
AISec · 14th ACM Workshop on Artificial Intelligence and Security, 2021
@inproceedings{andresini2021insomnia,
author = {Giuseppina Andresini and Feargus Pendlebury and Fabio Pierazzi and Corrado Loglisci and Annalisa Appice and Lorenzo Cavallaro},
title = {{INSOMNIA}: Towards Concept-Drift Robustness in Network Intrusion Detection},
journal = {{ACM} Workshop on Artificial Intelligence and Security ({AISec})},
year = {2021},
}
TESSERACT: Eliminating Experimental Bias in Malware Classification across Space and Time
Feargus Pendlebury*, Fabio Pierazzi*, Roberto Jordaney, Johannes Kinder, and Lorenzo Cavallaro
USENIX Sec · 28th USENIX Security Symposium, 2019
@inproceedings{pendlebury2019tesseract,
author = {Feargus Pendlebury* and Fabio Pierazzi* and Roberto Jordaney and Johannes Kinder and Lorenzo Cavallaro},
title = {{TESSERACT: Eliminating Experimental Bias in Malware Classification across Space and Time}},
booktitle = {28th USENIX Security Symposium},
year = {2019},
address = {Santa Clara, CA},
publisher = {USENIX Association},
note = {USENIX Sec}
}
POSTER: Enabling Fair ML Evaluations for Security
Feargus Pendlebury*, Fabio Pierazzi*, Roberto Jordaney, Johannes Kinder, Lorenzo Cavallaro
ACM CCS · 25th ACM Conference on Computer and Communications Security, 2018

Talks

Fabio Pierazzi presents TESSERACT at USENIX Security 2019.
Lorenzo Cavallaro gives a preview of the work at USENIX Enigma 2019.

People

  • Feargus Pendlebury, Ph.D. Student, King's College London & Royal Holloway, University of London
  • Zeliang Kan, Ph.D. Student, King's College London & University College London, UK
  • Shae McFadden, Ph.D. Student, King's College London & UCL & The Alan Turing Institute, UK
  • Fabio Pierazzi, Associate Professor, University College London (UCL), UK.
  • Roberto Jordaney, Royal Holloway, University of London, UK
  • Johannes Kinder, Full Professor of Computer Science, LU Munich, Germany
  • Lorenzo Cavallaro, Full Professor of Computer Science, University College London (UCL), UK