People

Sarah Wassermann

Sarah Wassermann

Institution:

Office:

43

Groups:

Former PhD student

Articles

Targeted Attacks: Redefining Spear Phishing and Business Email Compromise,
Sarah Wassermann, Maxime Meyer, Sebastien Goutal, Damien Riquet,
CoRR 2023

DeepCrypt - Deep Learning for QoE Monitoring and Fingerprinting of User Actions in Adaptive Video Streaming,
Pedro Casas, Michael Seufert, Sarah Wassermann, Bruno Gardlo, Nikolas Wehner, Raimund Schatz,
NetSoft 2022, Milan, Italy

Not all Web Pages are Born the Same Content Tailored Learning for Web QoE Inference,
Pedro Casas, Sarah Wassermann, Nikolas Wehner, Michael Seufert, Tobias Hossfeld,
M&N 2022, Padua, Italy

Fingerprinting Web Pages and Smartphone Apps from Encrypted Network Traffic with WebScanner,
Pedro Casas, Nikolas Wehner, Sarah Wassermann, Michael Seufert,
CloudNet 2022, Paris, France

X-Ray Goggles for the ISP: Improving in-Network Web and App QoE Monitoring with Deep Learning,
Pedro Casas, Sarah Wassermann, Michael Seufert, Nikolas Wehner, Olivia Dinica, Tobias Hossfeld,
TMA 2022, Enschede, Netherlands

Mobile Web and App QoE Monitoring for ISPs - from Encrypted Traffic to Speed Index through Machine Learning,
Pedro Casas, Sarah Wassermann, Nikolas Wehner, Michael Seufert, Joshua Schuler, Tobias Hossfeld,
WMNC 2021, Montréal, Canada

Are you on Mobile or Desktop? On the Impact of End-User Device on Web QoE Inference from Encrypted Traffic,
Sarah Wassermann ■, Pedro Casas, Zied Ben Houidi, Alexis Huet, Michael Seufert, Nikolas Wehner, Joshua Schuler, Shengming Cai, Hao Shi, Jinchun Xu, Tobias Hossfeld, Dario Rossi,
CNSM 2020, Izmir (virtual), Türkiye

RAL: reinforcement active learning for network traffic monitoring and analysis,
Sarah Wassermann ■, Thibaut Cuvelier, Pedro Casas,
SIGCOMM Posters and Demos 2020, New York / Virtual, United States

How good is your mobile (web) surfing?: speed index inference from encrypted traffic,
Sarah Wassermann ■, Pedro Casas, Michael Seufert, Nikolas Wehner, Joshua Schuler, Tobias Hossfeld,
SIGCOMM Posters and Demos 2020, New York, United States

ADAM & RAL: Adaptive Memory Learning and Reinforcement Active Learning for Network Monitoring,
Sarah Wassermann ■, Thibaut Cuvelier, Pavol Mulinka, Pedro Casas,
15th International Conference on Network and Service Management (CNSM) 2019, Halifax, Canada

I See What you See: Real Time Prediction of Video Quality from Encrypted Streaming Traffic,
Sarah Wassermann ■, Michael Seufert, Pedro Casas, Li Gang, Kuang Li,
Internet-QoE@MOBICOM 2019, Los Cabos, Mexico

RAL - Improving Stream-Based Active Learning by Reinforcement Learning,
Sarah Wassermann ■, Thibaut Cuvelier, Pedro Casas,
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD) Workshop on Interactive Adaptive Learning (IAL) 2019, Würzburg, Germany

On the Analysis of YouTube QoE in Cellular Networks through in-Smartphone Measurements,
Sarah Wassermann ■, Pedro Casas, Michael Seufert, Florian Wamser,
WMNC 2019, Paris, France

Let me Decrypt your Beauty: Real-time Prediction of Video Resolution and Bitrate for Encrypted Video Streaming,
Sarah Wassermann ■, Michael Seufert, Pedro Casas, Li Gang, Kuang Li,
TMA 2019, Paris, France

Lightweight, General Inference of Streaming Video Quality from Encrypted Traffic,
Francesco Bronzino ■, Paul Schmitt, Sara Ayoubi ■, Nick Feamster, Renata Teixeira ■, Sarah Wassermann ■, Srikanth Sundaresan,
CoRR 2019

ADAM & RAL: Adaptive Memory Learning and Reinforcement Active Learning for Network Monitoring,
Sarah Wassermann ■, Thibaut Cuvelier, Pavol Mulinka, Pedro Casas,
CNSM 2019

Remember the Good, Forget the Bad, do it Fast - Continuous Learning over Streaming Data,
Pavol Mulinka, Sarah Wassermann ■, Gonzalo Marín, Pedro Casas,
Continual Learning Workshop at NeurIPS 2018 2018, Montréal, Canada

Beauty is in the Eye of the Smartphone Holder A Data Driven Analysis of YouTube Mobile QoE,
Nikolas Wehner, Sarah Wassermann ■, Pedro Casas, Michael Seufert, Florian Wamser,
CNSM 2018, Rome, Italy

Distributed Internet Paths Performance Analysis Through Machine Learning,
Sarah Wassermann ■, Pedro Casas,
TMA 2018, Vienne, Austria

BIGMOMAL — Big Data Analytics for Mobile Malware Detection,
Sarah Wassermann ■, Pedro Casas,
ACM SIGCOMM 2018 Workshop on Traffic Measurements for Cybersecurity (WTMC 2018) 2018, Budapest, Hungary

Anycaston the Move: A Look at Mobile Anycast Performance,
Sarah Wassermann ■, John Rula, Fabian Bustamante, Pedro Casas,
TMA 2018, Vienne, Austria

BIGMOMAL: Big Data Analytics for Mobile Malware Detection,
Sarah Wassermann ■, Pedro Casas,
WTMC@SIGCOMM 2018

Improving QoE prediction in mobile video through machine learning,
Pedro Casas, Sarah Wassermann ■,
NOF 2017

NETPerfTrace: Predicting Internet Path Dynamics and Performance with Machine Learning,
Sarah Wassermann ■, Pedro Casas, Thibaut Cuvelier, Benoit Donnet,
Big-DAMA@SIGCOMM 2017

On the Analysis of Internet Paths with DisNETPerf, a Distributed Paths Performance Analyzer,
Sarah Wassermann, Pedro Casas, Benoit Donnet, Guy Leduc, Marco Mellia,
LCN Workshops 2016

Journal articles

Adaptive and Reinforcement Learning Approaches for Online Network Monitoring and Analysis,
Sarah Wassermann, Thibaut Cuvelier, Pavol Mulinka, Pedro Casas,
IEEE Transactions on Network and Service Management 2021

Improving Web QoE Monitoring for Encrypted Network Traffic through Time Series Modeling,
Nikolas Wehner, Michael Seufert, Joshua Schuler, Sarah Wassermann, Pedro Casas, Tobias Hossfeld,
SIGMETRICS Perform. Evaluation Rev. 2021, Milano, Italy

ViCrypt to the Rescue: Real-Time, Machine-Learning-Driven Video-QoE Monitoring for Encrypted Streaming Traffic,
Sarah Wassermann ■, Michael Seufert, Pedro Casas, Li Gang, Kuang Li,
IEEE Transactions on Network and Service Management 2020

Considering User Behavior in the Quality of Experience Cycle: Towards Proactive QoE-Aware Traffic Management,
Michael Seufert, Sarah Wassermann ■, Pedro Casas,
IEEE Communications Letters 2019

Machine Learning Models for YouTube QoE and User Engagement Prediction in Smartphones,
Sarah Wassermann ■, Nikolas Wehner, Pedro Casas,
SIGMETRICS Perform. Evaluation Rev. 2018, Toulouse, France

Unveiling network and service performance degradation in the wild with mplane,
Pedro Casas, Pierdomenico Fiadino, Sarah Wassermann, Stefano Traverso, Alessandro Dalconzo, Edion Tego, Francesco Matera, Marco Mellia,
IEEE Commun. Mag. 2016

Posters

Improving Stream-Based Active Learning with Reinforcement Learning,
Sarah Wassermann ■, Thibaut Cuvelier, Pedro Casas,
Women in Machine Learning (WiML) Workshop 2019 2019, Vancouver, Canada

Decrypting Video Quality from Encrypted Streaming Traffic,
Sarah Wassermann ■, Pedro Casas,
Women in Machine Learning (WiML) Workshop 2019 2019, Vancouver, Canada

ViCrypt: Real-time, Fine-grained Prediction of Video Quality from Encrypted Streaming Traffic,
Sarah Wassermann ■, Michael Seufert, Pedro Casas, Li Gang, Kuang Li,
ACM Internet Measurement Conference (IMC) 2019 2019, Amsterdam, Netherlands

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