My researches mainly focus on statistical learning. As cyber-security is a hard context (high throughput data, lack of ground truth), I try to develop unsupervised methods to mine streaming data.

Publications

Siffer, A., Fouque, P. A., Termier, A., & Largouet, C. (2020, December). Netspot: a simple Intrusion Detection System with statistical learning. In 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) (pp. 911-918). IEEE. [IEEE Xplore]

Siffer, A (2018, November). Intelligent thresholding. C&ESAR Conference. [cesar-conference.org]

Siffer, A., Fouque, P. A., Termier, A., & Largouët, C. (2018, July). Are your data gathered?. In Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (pp. 2210-2218). ACM. [HAL]

Siffer, A., Fouque, P. A., Termier, A., & Largouet, C. (2017, August). Anomaly detection in streams with extreme value theory. In Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 1067-1075). ACM [HAL]

Talks

• Network Anomaly Detection
  3rd France-Japan Meeting on Cybersecurity, April 2017, Tokyo

• Détection d’anomalies réseau
  Journées Nationales 2017 Pré-GDR Sécurité Informatique

Other

2020 – 1st place at ECW AI/Cyber challenge within Amossys

2017 – 2nd place at the research work presentation competition “Ma thèse 3.0” (European Cyber Week)