TMA'22: Best Paper Award

Best Paper Award at TMA 2022

Our publication "Active TLS Stack Fingerprinting: Characterizing TLS Server Deployments at Scale" has been awarded with the Best Paper Award at the Network Traffic Measurement and Analysis Conference (TMA 2022).

The publication is a collaboration with Claas Grohnfeldt, Michele Russo, and Daniele Sgandurra from AI4Sec, Huawei Technologies Munich.

The publication investigates how large-scale server fingerprinting can be achieved by utilizing TLS meta data. We propose an approach and show the feasibility based on a Content Delivery Network (CDN) and Command and Control (CnC) server detection. We extended the TUM goscanner with active TLS fingerprinting capabilites and open-sourced our measurement data and code under the publication website.

2022-06-01

Markus Sosnowski, Johannes Zirngibl, Patrick Sattler, Georg Carle, Claas Grohnfeldt, Michele Russo, Daniele Sgandurra, “Active TLS Stack Fingerprinting: Characterizing TLS Server Deployments at Scale,” in Proc. Network Traffic Measurement and Analysis Conference (TMA), Jun. 2022. Best Paper Award [Pdf] [Slides] [Homepage] [Rawdata] [Bib]