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 Viana 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: Mobile communications and networks security & privacy; Data-driven technologies for mobile communications; Attack, detection, and prevention; Data science and artificial intelligence for mobile communications
More detailed information: My CV (last updated on June 2024)
Latest News
(A selection of recent news — for the full list, see below)
- 03/25: Our paper “The Silent Signature: Behavior-based User Exposure in Mobility Data” is accepted to MDM 2025. Congrats to Lucas Felix for leading this exciting work!
- 02/25: Honored to serve on the TPC of Algotel 2025.
- 02/25: Presented our latest research on traffic–mobility dependencies at the STIC-AmSud LINT Workshop in Buenos Aires. Grateful for the continued collaboration with Latin American partners.
- 12/24: Delivered an invited talk at the ZTF Awards, sharing with 4000+ young students across Cameroon
- 11/24: Co-organized the FraudZen Hackathon at University of Yaoundé I, in partnership with Prof. Tapamo.
👉 See all news and updates on this page
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
Below is a list of 3 selected publications. For a full and updated list of publications and co-authors, please, kindly refer to the publication page.
- A. J. Kouam, A. C. Viana, P. Martins, C. Adjih, and A. Tchana. SigN: SIMBox Activity Detection Through Latency Anomalies at the Cellular Edge , 2025. DOI: 10.48550/arXiv.2502.01193
- A. J. Kouam, A. C. Viana, and A. Tchana. 2024. Battle of Wits: To What Extent Can Fraudsters Disguise Their Tracks in International bypass Fraud? In Proceedings of the 19th ACM Asia Conference on Computer and Communications Security (ASIA CCS ’24). DOI: 10.1145/3634737.3657023
- A. J. Kouam, A. C. Viana and A. Tchana, “SIMBox Bypass Frauds in Cellular Networks: Strategies, Evolution, Detection, and Future Directions,” in IEEE Communications Surveys \& Tutorials, vol. 23, no. 4, pp. 2295-2323, Fourthquarter 2021, DOI: 10.1109/COMST.2021.3100916. (Q1, Impact Factor: 34.4)
Reviewing
| Technical PC | ICNS’23, ICNS’24, EuroDW’24, ACSAC’24, WiMob’24, PAM’25, Algotel’25, TMA’25 |
| Shadow PC | Algotel&Cores’21 |
| Artefact Evaluation Committee | EuroSys’21, Usenix Sec’22, CoNext’22 |
| Journal External Reviews | – IEEE Open Journal of the Communications Society (2024) – Annals of Telecommunications (2024) – EPJ Data Science (2024) – IEEE Transactions on Network and Service Management (sub-reviewer, 2021) |
| Session chair | Machine 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:
- Co-organizer of the workshop “Was ist Informatik? Von der App auf dem Smartphone zum ersten eigenen Game” for the Girls’ day in Berlin (Mädchen-Zukunftstag)
- 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, Adversarial Machine Learning, Master, TU Berlin, Lecture, Winter 2024
- Instructor, Unusual Side Channels and Privacy Leaks, Bachelor, TU Berlin, Seminar, Winter 2024
- Instructor, Mobile Privacy and Security, Bachelor, TU Berlin, Seminar, Summer 2024
- Teaching Assistant, Networking, Bachelor, UP Saclay, Fall 2021
- MOOC Trainer, Fundamentals of Network Systems and Information, CAPES France, UP Saclay, 2021
- Teaching Assistant, Distributed Systems and virtualization, Master, Ecole Nationale Supérieure Polytechnique of Yaoundé, Fall 2019