Short bio

I am a postdoctoral researcher at TU Berlin and member of the Machine Learning and Security group led by Pr. Konrad Rieck.

Prior to this, I successfully completed my PhD at INRIA Saclay and Ecole Polytechnique, France, under the guidance of Aline Carneiro and Alain Tchana. Following my doctoral studies, I furthered my research with an 8-month postdoctoral position at INRIA Saclay.

My primary research focus lies at the intersection of machine learning and security and privacy, with a particular emphasis on the individual. Thus, I investigate offensive and defensive AI models in fields where network users’ security and privacy may be impacted.

Throughout my academic journey, I had the pleasure of completing doctoral internships that significantly enriched my expertise. Under the guidance of Philippe Martins at Telecom Paris, I focused on experimental cellular signalling data processing within a Faraday Cage. Additionally, I collaborated with Luca Pappalardo at CNR Pisa, contributing to the modeling and generation of cellular Charging and eXtended Data Records (CDRs/XDRs).

I obtained a degree in computer engineering in 2019 from the École Polytechnique of Yaoundé in Cameroon.

Research interests: Data-driven network security, Human behavior in communication, Language processing and leveraging, AI Security and Privacy

More detailed information: My CV (last updated on 26 July 2023)

Latest News
  • 03/24: Glad to serve as External Reviewer at EPJ Data Science journal
  • 03/24: Our paper “Battle of Wits: To What Extent Can Fraudsters Disguise Their Tracks in International bypass Fraud?” is accepted to AsiaCCS 2024
  • 02/24: Glad to serve as part of the TPC of EuroSys Doctoral Workshop 2024
  • 01/24: Excited to start a new Post-Doc position at TU Berlin in the MLSec group.
  • 12/23: Glad to participate to the 2nd STIC-Amsud LINT workshop in Rio de Janeiro, Brazil
  • 10/23: Gave a talk at NetMob 2023 on our paper “SIMBox fraud: How well can they mimick your communication behavior ?”
  • 05/23: Gave a talk at CoRes 2023 on our paper “Signalisation cellulaire pour la detection des fraudes de contournement” and received the Best student paper award
  • 05/23: Successfully defended my PhD thesis entitled “Bypass frauds in cellular networks: understanding and mitigation“
Research projects
Machine Learning for Offensive Computer Security (MALFOY)

The security of digital systems is under constant threat of attacks. One way to improve cybersecurity is to predict how hackers could manipulate new technologies to break into existing systems. However, little is known about how cybercriminals might take advantage of the emerging field of machine learning. Funded by the European Research Council, the MALFOY project aims to determine how machine learning algorithms can be used to discover security weaknesses and perform computer attacks automatically. By taking the position of the attacker to explore offensive security techniques, the project will be able to construct effective defense mechanisms.

ERC project conducted in the TU Berlin MLSec group

Tackling International Bypass Frauds

International bypass frauds, also known as SIMBox frauds, rank among the most prevalent scams in cellular networks, placing in the top three phone system frauds. This fraud results in an annual global loss of $3.11 billion and threatens network users’ privacy and national security. Despite its widespread impact, SIMBox fraud remains a persistent challenge, continuously evading detection due to the continual refinement of fraudulent behavior. This project leverages ML through an analysis and formalization approach to understand the evolving fraud behavior in diverse cellular network traces, including Charging Data Records (CDRs) and signaling data. The ultimate goal is to develop effective strategies for detecting and mitigating this pervasive fraud.

Research axis of the MLSec Learning Network Systems Security (MLNS2) INRIA Associate Team

Complete and Privacy-preserving eXtended Data Records availability

Domain-wide recognized by their high value in human presence and activity studies, cellular network datasets (i.e., eXtended Data Records or XDRs), however, present accessibility, usability, and privacy issues. These hurdles hinder their effective utilization and impede research reproducibility. This project explores AI-powered strategies to make available to the community realistic xDRs being complete, i.e., including both traffic and mobility information. Notably, achieving the desired fine-grained granularity through per-individual data description poses a privacy challenge, which we thoroughly evaluate.

Research axis of the STIC-AmSud LINT Associate Team

Publications
List of publications

Reviewing
Technical PCICNS’23, ICNS’24, EuroDW’24, ACSAC’24
Shadow PCAlgotel&Cores’21
Artefact Evaluation CommitteeEuroSys’21, Usenix Sec’22, CoNext’22, Mobicom’24
Journal Reviews– IEEE Transactions on Network and Service Management (sub-reviewer, 2021)
– EPJ Data Science (2024)
Session chairMachine learning in and of Networks, CoNext’22 Student workshop, Rome, Italy
Popularization

I like sharing my research to a wider audience, especially with the hope to encourage young girls to get an interest in
computer science. See below some activities:

  • Women in CS Session Panelist, Computer Science Workshop, Ecole Polytechnique, Yaounde, Cameroon
  • WorkShop Leading at “Rendez-vous des Jeunes filles Mathématiciennes et Informaticiennes” 2021, 2022, INRIA Saclay
  • Talk : “What is the job of a researcher? Presentation of the INRIA Institute” (in French) at mathematics week, Acadamie de Créteil
  • Video Production: Wireless Communications in a video for Paris-Saclay Science Festival
  • Stand Animation at the science festival Institut Polytechnique Paris (IPP) : Welcoming the general public and explaining in an off-line style the concepts of algorithms and encryption

Teaching
  • Teaching Assistant, Networking, L2, UP Saclay, Fall 2021 (24 hours)
  • MOOC Trainer, Fundamentals of Network Systems and Information, CAPES France, UP Saclay, 2021
  • Teaching Assistant, Distributed Systems and virtualization, L3, Ecole Nationale Supérieure Polytechnique of Yaoundé, Fall 2019