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Sarah Wassermann
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2020 – today
- 2023
- [i2]Sarah Wassermann, Maxime Meyer, Sébastien Goutal, Damien Riquet:
Targeted Attacks: Redefining Spear Phishing and Business Email Compromise. CoRR abs/2309.14166 (2023) - 2022
- [c19]Pedro Casas
, Nikolas Wehner, Sarah Wassermann, Michael Seufert
Fingerprinting Web Pages and Smartphone Apps from Encrypted Network Traffic with WebScanner. CloudNet 2022: 1-9 - [c18]Pedro Casas
Not all Web Pages are Born the Same Content Tailored Learning for Web QoE Inference. M&N 2022: 1-6 - [c17]Pedro Casas
DeepCrypt - Deep Learning for QoE Monitoring and Fingerprinting of User Actions in Adaptive Video Streaming. NetSoft 2022: 259-263 - [c16]Pedro Casas, Sarah Wassermann, Michael Seufert, Nikolas Wehner, Olivia Dinica, Tobias Hossfeld:
X-Ray Goggles for the ISP: Improving in-Network Web and App QoE Monitoring with Deep Learning. TMA 2022 - 2021
- [j6]Nikolas Wehner, Michael Seufert
Improving Web QoE Monitoring for Encrypted Network Traffic through Time Series Modeling. SIGMETRICS Perform. Evaluation Rev. 48(4): 37-40 (2021) - [j5]Sarah Wassermann, Thibaut Cuvelier
Adaptive and Reinforcement Learning Approaches for Online Network Monitoring and Analysis. IEEE Trans. Netw. Serv. Manag. 18(2): 1832-1849 (2021) - [c15]Pedro Casas
Mobile Web and App QoE Monitoring for ISPs - from Encrypted Traffic to Speed Index through Machine Learning. WMNC 2021: 40-47 - 2020
- [j4]Sarah Wassermann, Michael Seufert
ViCrypt to the Rescue: Real-Time, Machine-Learning-Driven Video-QoE Monitoring for Encrypted Streaming Traffic. IEEE Trans. Netw. Serv. Manag. 17(4): 2007-2023 (2020) - [c14]Sarah Wassermann, Pedro Casas
Are you on Mobile or Desktop? On the Impact of End-User Device on Web QoE Inference from Encrypted Traffic. CNSM 2020: 1-9 - [c13]Sarah Wassermann, Pedro Casas, Michael Seufert
How good is your mobile (web) surfing?: speed index inference from encrypted traffic. SIGCOMM Posters and Demos 2020: 35-36 - [c12]Sarah Wassermann, Thibaut Cuvelier, Pedro Casas:
RAL: reinforcement active learning for network traffic monitoring and analysis. SIGCOMM Posters and Demos 2020: 55-56
2010 – 2019
- 2019
- [j3]Michael Seufert
Considering User Behavior in the Quality of Experience Cycle: Towards Proactive QoE-Aware Traffic Management. IEEE Commun. Lett. 23(7): 1145-1148 (2019) - [c11]Sarah Wassermann, Thibaut Cuvelier, Pavol Mulinka
ADAM & RAL: Adaptive Memory Learning and Reinforcement Active Learning for Network Monitoring. CNSM 2019: 1-9 - [c10]Sarah Wassermann, Michael Seufert
I See What you See: Real Time Prediction of Video Quality from Encrypted Streaming Traffic. Internet-QoE@MOBICOM 2019: 1-6 - [c9]Sarah Wassermann, Pedro Casas, Michael Seufert
On the Analysis of YouTube QoE in Cellular Networks through in-Smartphone Measurements. WMNC 2019: 71-78 - [c8]Sarah Wassermann, Michael Seufert
Let me Decrypt your Beauty: Real-time Prediction of Video Resolution and Bitrate for Encrypted Video Streaming. TMA 2019: 199-200 - [i1]Francesco Bronzino
Lightweight, General Inference of Streaming Video Quality from Encrypted Traffic. CoRR abs/1901.05800 (2019) - 2018
- [j2]Sarah Wassermann, Nikolas Wehner, Pedro Casas:
Machine Learning Models for YouTube QoE and User Engagement Prediction in Smartphones. SIGMETRICS Perform. Evaluation Rev. 46(3): 155-158 (2018) - [c7]Nikolas Wehner, Sarah Wassermann, Pedro Casas, Michael Seufert, Florian Wamser:
Beauty is in the Eye of the Smartphone Holder A Data Driven Analysis of YouTube Mobile QoE. CNSM 2018: 343-347 - [c6]Sarah Wassermann, Pedro Casas:
BIGMOMAL: Big Data Analytics for Mobile Malware Detection. WTMC@SIGCOMM 2018: 33-39 - [c5]Sarah Wassermann, Pedro Casas:
Distributed Internet Paths Performance Analysis Through Machine Learning. TMA 2018: 1-2 - [c4]Sarah Wassermann, John P. Rula, Fabian E. Bustamante, Pedro Casas:
Anycaston the Move: A Look at Mobile Anycast Performance. TMA 2018: 1-8 - 2017
- [c3]Pedro Casas, Sarah Wassermann:
Improving QoE prediction in mobile video through machine learning. NOF 2017: 1-7 - [c2]Sarah Wassermann, Pedro Casas, Thibaut Cuvelier
NETPerfTrace: Predicting Internet Path Dynamics and Performance with Machine Learning. Big-DAMA@SIGCOMM 2017: 31-36 - 2016
- [j1]Pedro Casas, Pierdomenico Fiadino, Sarah Wassermann, Stefano Traverso, Alessandro D'Alconzo, Edion Tego, Francesco Matera, Marco Mellia
Unveiling network and service performance degradation in the wild with mplane. IEEE Commun. Mag. 54(3): 71-79 (2016) - [c1]Sarah Wassermann, Pedro Casas, Benoit Donnet, Guy Leduc, Marco Mellia
On the Analysis of Internet Paths with DisNETPerf, a Distributed Paths Performance Analyzer. LCN Workshops 2016: 72-79
Coauthor Index
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