A user perspective for end-to-end quality of service evaluation in multimedia networks. - Pedro Casas; Pablo Belzarena; Ignacio Irigaray; Diego Guerra (LANC, 2007)

Optimal volume anomaly detection in network traffic flows. - Lionel Fillatre; Igor V. Nikiforov; Pedro Casas; Sandrine Vaton (EUSIPCO, 2008)

Volume Anomaly Detection in Data Networks: An Optimal Detection Algorithm vs. the PCA Approach. - Pedro Casas; Lionel Fillatre; Sandrine Vaton; Igor V. Nikiforov (FITraMEn, 2008)

Multi Hour Robust Routing and Fast Load Change Detection for Traffic Engineering. - Pedro Casas; Lionel Fillatre; Sandrine Vaton (ICC, 2008)

Robust routing vs dynamic load-balancing a comprehensive study and new directions. - Pedro Casas; Federico Larroca; Jean-Louis Rougier; Sandrine Vaton (DRCN, 2009)

Robust Routing Mechanisms for Intradomain Traffic Engineering in Dynamic Networks. - Pedro Casas; Federico Larroca; Sandrine Vaton (LANOMS, 2009)

Efficient methods for traffic matrix modeling and on-line estimation in large-scale IP networks. - Pedro Casas; Sandrine Vaton; Lionel Fillatre; Thierry Chonavel (ITC, 2009)

On the use of random neural networks for traffic matrix estimation in large-scale IP networks. - Pedro Casas; Sandrine Vaton (IWCMC, 2010)

Optimal volume anomaly detection and isolation in large-scale IP networks using coarse-grained measurements. - Pedro Casas; Sandrine Vaton; Lionel Fillatre; Igor V. Nikiforov (Comput. Networks, 2010)

End-to-end quality of service-based admission control using the fictitious network analysis. - Pablo Belzarena; Paola Bermolen; Pedro Casas; María Simon (Comput. Commun., 2010)

Sub-Space clustering, Inter-Clustering Results Association & anomaly correlation for unsupervised network anomaly detection. - Johan Mazel; Pedro Casas; Yann Labit; Philippe Owezarski (CNSM, 2011)

On the use of Sub-Space Clustering & Evidence Accumulation for traffic analysis & classification. - Pedro Casas; Johan Mazel; Philippe Owezarski (IWCMC, 2011)

UNADA: Unsupervised Network Anomaly Detection Using Sub-space Outliers Ranking. - Pedro Casas; Johan Mazel; Philippe Owezarski (Networking (1), 2011)

Steps Towards Autonomous Network Security: Unsupervised Detection of Network Attacks. - Pedro Casas; Johan Mazel; Philippe Owezarski (NTMS, 2011)

MINETRAC: Mining flows for unsupervised analysis & semi-supervised classification. - Pedro Casas; Johan Mazel; Philippe Owezarski (ITC, 2011)

Sub-Space Clustering and Evidence Accumulation for Unsupervised Network Anomaly Detection. - Johan Mazel; Pedro Casas; Philippe Owezarski (TMA, 2011)

Reactive Robust Routing: Anomaly Localization and Routing Reconfiguration for Dynamic Networks. - Pedro Casas; Lionel Fillatre; Sandrine Vaton; Igor V. Nikiforov (J. Netw. Syst. Manag., 2011)

YouTube & Facebook Quality of Experience in mobile broadband networks. - Pedro Casas; Andreas Sackl; Sebastian Egger; Raimund Schatz (GLOBECOM Workshops, 2012)

Passive YouTube QoE Monitoring for ISPs. - Raimund Schatz; Tobias Hoßfeld; Pedro Casas (IMIS, 2012)

Taming traffic dynamics: Analysis and improvements. - Pedro Casas; Federico Larroca; Jean-Louis Rougier; Sandrine Vaton (Comput. Commun., 2012)

Unsupervised Network Intrusion Detection Systems: Detecting the Unknown without Knowledge. - Pedro Casas; Johan Mazel; Philippe Owezarski (Comput. Commun., 2012)

Knowledge-independent traffic monitoring: Unsupervised detection of network attacks. - Pedro Casas; Johan Mazel; Philippe Owezarski (IEEE Netw., 2012)

A first look at quality of experience in Personal Cloud Storage services. - Pedro Casas; Hans Ronald Fischer; Stefan Suette; Raimund Schatz (ICC Workshops, 2013)

Quality of experience in remote virtual desktop services. - Pedro Casas; Michael Seufert; Sebastian Egger; Raimund Schatz (IM, 2013)

Mini-IPC: A minimalist approach for HTTP traffic classification using IP addresses. - Pedro Casas; Pierdomenico Fiadino (IWCMC, 2013)

IP mining: Extracting knowledge from the dynamics of the Internet addressing space. - Pedro Casas; Pierdomenico Fiadino; Arian Bär (ITC, 2013)

Monitoring YouTube QoE: Is Your Mobile Network Delivering the Right Experience to your Customers? - Pedro Casas; Raimund Schatz; Tobias Hoßfeld (WCNC, 2013)

YOUQMON: a system for on-line monitoring of YouTube QoE in operational 3G networks. - Pedro Casas; Michael Seufert; Raimund Schatz (SIGMETRICS Perform. Evaluation Rev., 2013)

Large-scale network traffic monitoring with DBStream, a system for rolling big data analysis. - Arian Bär; Alessandro Finamore; Pedro Casas; Lukasz Golab; Marco Mellia (IEEE BigData, 2014)

Characterizing Microsoft Lync Online in mobile networks: a Quality of Experience perspective. - Pedro Casas; Andreas Sackl; Sebastian Egger; Raimund Schatz (CloudNet, 2014)

On the analysis of QoE-based performance degradation in YouTube traffic. - Pedro Casas; Alessandro D'Alconzo; Pierdomenico Fiadino; Arian Bär; Alessandro Finamore (CNSM, 2014)

Diagnosing Device-Specific Anomalies in Cellular Networks. - Mirko Schiavone; Peter Romirer-Maierhofer; Pierdomenico Fiadino; Pedro Casas (CoNEXT Student Workshop, 2014)

YouTube all around: Characterizing YouTube from mobile and fixed-line network vantage points. - Pedro Casas; Pierdomenico Fiadino; Arian Bär; Alessandro D'Alconzo; Alessandro Finamore; Marco Mellia (EuCNC, 2014)

DBStream: An online aggregation, filtering and processing system for network traffic monitoring. - Arian Bär; Pedro Casas; Lukasz Golab; Alessandro Finamore (IWCMC, 2014)

Coping with 0-day attacks through Unsupervised Network Intrusion Detection. - Pedro Casas; Johan Mazel; Philippe Owezarski (IWCMC, 2014)

Who to blame when YouTube is not working? detecting anomalies in CDN-provisioned services. - Alessandro D'Alconzo; Pedro Casas; Pierdomenico Fiadino; Arian Bär; Alessandro Finamore (IWCMC, 2014)

Characterizing web services provisioning via CDNs: The case of Facebook. - Pierdomenico Fiadino; Alessandro D'Alconzo; Pedro Casas (IWCMC, 2014)

Understanding HTTP Traffic and CDN Behavior from the Eyes of a Mobile ISP. - Pedro Casas; Pierdomenico Fiadino; Arian Bär (PAM, 2014)

Vivisecting whatsapp through large-scale measurements in mobile networks. - Pierdomenico Fiadino; Mirko Schiavone; Pedro Casas (SIGCOMM, 2014)

On the detection of network traffic anomalies in content delivery network services. - Pierdomenico Fiadino; Alessandro D'Alconzo; Arian Bär; Alessandro Finamore; Pedro Casas (ITC, 2014)

YouTube in the move: Understanding the performance of YouTube in cellular networks. - Pedro Casas; Pierdomenico Fiadino; Andreas Sackl; Alessandro D'Alconzo (Wireless Days, 2014)

mPlane: an intelligent measurement plane for the internet. - Brian Trammell; Pedro Casas; Dario Rossi 001; Arian Bär; Zied Ben-Houidi; Ilias Leontiadis; Tivadar Szemethy; Marco Mellia (IEEE Commun. Mag., 2014)

Quality of Experience in Cloud services: Survey and measurements. - Pedro Casas; Raimund Schatz (Comput. Networks, 2014)

When YouTube Does not Work - Analysis of QoE-Relevant Degradation in Google CDN Traffic. - Pedro Casas; Alessandro D'Alconzo; Pierdomenico Fiadino; Arian Bär; Alessandro Finamore; Tanja Zseby (IEEE Trans. Netw. Serv. Manag., 2014)

Taming QoE in cellular networks: From subjective lab studies to measurements in the field. - Pedro Casas; Bruno Gardlo; Michael Seufert; Florian Wamser; Raimund Schatz (CNSM, 2015)

QoMOSN - On the analysis of traffic and Quality of Experience in Mobile Online Social Networks. - Pedro Casas; Pierdomenico Fiadino; Mirko Schiavone (EuCNC, 2015)

YoMoApp: A tool for analyzing QoE of YouTube HTTP adaptive streaming in mobile networks. - Florian Wamser; Michael Seufert; Pedro Casas; Ralf Irmer; Phuoc Tran-Gia; Raimund Schatz (EuCNC, 2015)

MTRAC - discovering M2M devices in cellular networks from coarse-grained measurements. - Arian Bär; Philipp Svoboda; Pedro Casas (ICC, 2015)

On the quest for new KPIs in mobile networks: The impact of throughput fluctuations on QoE. - Pedro Casas; Andreas Sackl; Raimund Schatz; Lucjan Janowski; John Turk; Ralf Irmer (ICC Workshops, 2015)

Cache-oblivious scheduling of shared workloads. - Arian Bär; Lukasz Golab; Stefan Ruehrup; Mirko Schiavone; Pedro Casas (ICDE, 2015)

On the analysis of QoE in cellular networks: From subjective tests to large-scale traffic measurements. - Pedro Casas; Martín Varela 001; Pierdomenico Fiadino; Mirko Schiavone; Helena Rivas; Raimund Schatz (IWCMC, 2015)

Towards automatic detection and diagnosis of Internet service anomalies via DNS traffic analysis. - Pierdomenico Fiadino; Alessandro D'Alconzo; Mirko Schiavone; Pedro Casas (IWCMC, 2015)

YouTube QoE on mobile devices: Subjective analysis of classical vs. adaptive video streaming. - Michael Seufert; Florian Wamser; Pedro Casas; Ralf Irmer; Phuoc Tran-Gia; Raimund Schatz (IWCMC, 2015)

Demo: On the Monitoring of YouTube QoE in Cellular Networks from End-devices. - Michael Seufert; Florian Wamser; Pedro Casas; Ralf Irmer; Phuoc Tran-Gia; Raimund Schatz (S3@MobiCom, 2015)

Poster: Understanding YouTube QoE in Cellular Networks with YoMoApp: A QoE Monitoring Tool for YouTube Mobile. - Florian Wamser; Michael Seufert; Pedro Casas; Ralf Irmer; Phuoc Tran-Gia; Raimund Schatz (MobiCom, 2015)

Online Social Networks anatomy: On the analysis of Facebook and WhatsApp in cellular networks. - Pierdomenico Fiadino; Pedro Casas; Mirko Schiavone; Alessandro D'Alconzo (Networking, 2015)

Quantifying the impact of network bandwidth fluctuations and outages on Web QoE. - Andreas Sackl; Pedro Casas; Raimund Schatz; Lucjan Janowski; Ralf Irmer (QoMEX, 2015)

Exploring QoE in Cellular Networks: How Much Bandwidth do you Need for Popular Smartphone Apps? - Pedro Casas; Raimund Schatz; Florian Wamser; Michael Seufert; Ralf Irmer (AllThingsCellular@SIGCOMM, 2015)

Challenging Entropy-based Anomaly Detection and Diagnosis in Cellular Networks. - Pierdomenico Fiadino; Alessandro D'Alconzo; Mirko Schiavone; Pedro Casas (SIGCOMM, 2015)

RCATool - A Framework for Detecting and Diagnosing Anomalies in Cellular Networks. - Pierdomenico Fiadino; Alessandro D'Alconzo; Mirko Schiavone; Pedro Casas (ITC, 2015)

Vivisecting WhatsApp in Cellular Networks: Servers, Flows, and Quality of Experience. - Pierdomenico Fiadino; Mirko Schiavone; Pedro Casas (TMA, 2015)

Hunting attacks in the dark: clustering and correlation analysis for unsupervised anomaly detection. - Johan Mazel; Pedro Casas; Romain Fontugne; Kensuke Fukuda; Philippe Owezarski (Int. J. Netw. Manag., 2015)

POSTER: (Semi)-Supervised Machine Learning Approaches for Network Security in High-Dimensional Network Data. - Pedro Casas; Alessandro D'Alconzo; Giuseppe Settanni; Pierdomenico Fiadino; Florian Skopik (CCS, 2016)

The Beauty of Consistency in Radio-Scheduling Decisions. - Eirini Liotou; Raimund Schatz; Andreas Sackl; Pedro Casas; Dimitris Tsolkas; Nikos I. Passas; Lazaros F. Merakos (GLOBECOM Workshops, 2016)

Detecting and diagnosing anomalies in cellular networks using Random Neural Networks. - Pedro Casas; Alessandro D'Alconzo; Pierdomenico Fiadino; Christian Callegari (IWCMC, 2016)

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)

When smartphones become the enemy: unveiling mobile apps anomalies through clustering techniques. - Pedro Casas; Pierdomenico Fiadino; Alessandro D'Alconzo (ATC@MobiCom, 2016)

Big-DAMA: Big Data Analytics for Network Traffic Monitoring and Analysis. - Pedro Casas; Alessandro D'Alconzo; Tanja Zseby; Marco Mellia (LANCOMM@SIGCOMM, 2016)

An Educated Guess on QoE in Operational Networks through Large-Scale Measurements. - Pedro Casas; Bruno Gardlo; Raimund Schatz; Marco Mellia (Internet-QoE@SIGCOMM, 2016)

Looking for Network Latency Clusters in the LAC Region. - Agustin Formoso; Pedro Casas (LANCOMM@SIGCOMM, 2016)

WhatsApp Calling: a Revised Analysis on WhatsApp's Architecture and Calling Service. - Juan Martin Vanerio; Pedro Casas (LANCOMM@SIGCOMM, 2016)

Machine-Learning Based Approaches for Anomaly Detection and Classification in Cellular Networks. - Pedro Casas; Pierdomenico Fiadino; Alessandro D'Alconzo (TMA, 2016)

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

DBStream: A holistic approach to large-scale network traffic monitoring and analysis. - Arian Bär; Pedro Casas; Alessandro D'Alconzo; Pierdomenico Fiadino; Lukasz Golab; Marco Mellia; Erich Schikuta (Comput. Networks, 2016)

Modeling the YouTube stack: From packets to quality of experience. - Florian Wamser; Pedro Casas; Michael Seufert; Christian Moldovan; Phuoc Tran-Gia; Tobias Hoßfeld (Comput. Networks, 2016)

Next to You: Monitoring Quality of Experience in Cellular Networks From the End-Devices. - Pedro Casas; Michael Seufert; Florian Wamser; Bruno Gardlo; Andreas Sackl; Raimund Schatz (IEEE Trans. Netw. Serv. Manag., 2016)

Grasping Popular Applications in Cellular Networks With Big Data Analytics Platforms. - Pierdomenico Fiadino; Pedro Casas; Alessandro D'Alconzo; Mirko Schiavone; Arian Bär (IEEE Trans. Netw. Serv. Manag., 2016)

Network security and anomaly detection with Big-DAMA, a big data analytics framework. - Pedro Casas; Francesca Soro; Juan Martin Vanerio; Giuseppe Settanni; Alessandro D'Alconzo (CloudNet, 2017)

GML learning, a generic machine learning model for network measurements analysis. - Pedro Casas; Juan Martin Vanerio; Kensuke Fukuda (CNSM, 2017)

Improving QoE prediction in mobile video through machine learning. - Pedro Casas; Sarah Wassermann (NOF, 2017)

Predicting QoE in cellular networks using machine learning and in-smartphone measurements. - Pedro Casas; Alessandro D'Alconzo; Florian Wamser; Michael Seufert; Bruno Gardlo; Anika Schwind; Phuoc Tran-Gia; Raimund Schatz (QoMEX, 2017)

Unsupervised QoE field study for mobile YouTube video streaming with YoMoApp. - Michael Seufert; Nikolas Wehner; Florian Wamser; Pedro Casas; Alessandro D'Alconzo; Phuoc Tran-Gia (QoMEX, 2017)

Ensemble-learning Approaches for Network Security and Anomaly Detection. - Juan Martin Vanerio; Pedro Casas (Big-DAMA@SIGCOMM, 2017)

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

Concept and implementation of video QoE measurements in a mobile broadband testbed. - Anika Schwind; Michael Seufert; Ozgu Alay; Pedro Casas; Phuoc Tran-Gia; Florian Wamser (TMA, 2017)

Super learning for anomaly detection in cellular networks. - Pedro Casas; Juan Martin Vanerio (WiMob, 2017)

Evaluating music mastering quality using machine learning. - Mark Shtern; Pedro Casas; Vassilios Tzerpos (CASCON, 2018)

Hi-Clust: Unsupervised Analysis of Cloud Latency Measurements Through Hierarchical Clustering. - Pavol Mulinka; Pedro Casas; Lukas Kencl (CloudNet, 2018)

A Fair Share for All: Novel Adaptation Logic for QoE Fairness of HTTP Adaptive Video Streaming. - Michael Seufert; Nikolas Wehner; Pedro Casas; Florian Wamser (CNSM, 2018)

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)

MLNET - Machine Learning Models for Network Analytics. - Pedro Casas (EDBT/ICDT Workshops, 2018)

Enhancing Machine Learning Based QoE Prediction by Ensemble Models. - Pedro Casas; Michael Seufert; Nikolas Wehner; Anika Schwind; Florian Wamser (ICDCS, 2018)

Studying the Impact of HAS QoE Factors on the Standardized QoE Model P.1203. - Michael Seufert; Nikolas Wehner; Pedro Casas (ICDCS, 2018)

Streaming Characteristics of Spotify Sessions. - Anika Schwind; Florian Wamser; Thomas Gensler; Phuoc Tran-Gia; Michael Seufert; Pedro Casas (QoMEX, 2018)

RawPower: Deep Learning based Anomaly Detection from Raw Network Traffic Measurements. - Gonzalo Marín; Pedro Casas; Germán Capdehourat (SIGCOMM Posters and Demos, 2018)

Stream-based Machine Learning for Network Security and Anomaly Detection. - Pavol Mulinka; Pedro Casas (Big-DAMA@SIGCOMM, 2018)

Adaptive Network Security through Stream Machine Learning. - Pavol Mulinka; Pedro Casas (SIGCOMM Posters and Demos, 2018)

BIGMOMAL: Big Data Analytics for Mobile Malware Detection. - Sarah Wassermann; Pedro Casas (WTMC@SIGCOMM, 2018)

On the Analysis of Network Measurements Through Machine Learning: The Power of the Crowd. - Pedro Casas (TMA, 2018)

App for Dynamic Crowdsourced QoE Studies of HTTP Adaptive Streaming on Mobile Devices. - Michael Seufert; Nikolas Wehner; Pedro Casas (TMA, 2018)

You Tube QoE Monitoring with YoMoApp: A Web-Based Data Interface for Researchers. - Florian Wamser; Nikolas Wehner; Michael Seufert; Pedro Casas; Phuoc Tran-Gia (TMA, 2018)

Distributed Internet Paths Performance Analysis Through Machine Learning. - Sarah Wassermann; Pedro Casas (TMA, 2018)

Anycaston the Move: A Look at Mobile Anycast Performance. - Sarah Wassermann; John P. Rula; Fabian E. Bustamante; Pedro Casas (TMA, 2018)

Machine learning models for wireless network monitoring and analysis. - Pedro Casas (WCNC Workshops, 2018)

DeepSec meets RawPower - Deep Learning for Detection of Network Attacks Using Raw Representations. - Gonzalo Marín; Pedro Casas; Germán Capdehourat (SIGMETRICS Perform. Evaluation Rev., 2018)

Machine Learning Models for YouTube QoE and User Engagement Prediction in Smartphones. - Sarah Wassermann; Nikolas Wehner; Pedro Casas (SIGMETRICS Perform. Evaluation Rev., 2018)

Should I (re)Learn or Should I Go(on)?: Stream Machine Learning for Adaptive Defense against Network Attacks. - Pedro Casas; Pavol Mulinka; Juan Martin Vanerio (MTD@CCS, 2019)

Continuous and Adaptive Learning over Big Streaming Data for Network Security. - Pavol Mulinka; Pedro Casas; Juan Martin Vanerio (CloudNet, 2019)

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

EXPLAIN-IT: Towards Explainable AI for Unsupervised Network Traffic Analysis. - Andrea Morichetta 002; Pedro Casas; Marco Mellia (Big-DAMA@CoNEXT, 2019)

Stream-based Machine Learning for Real-time QoE Analysis of Encrypted Video Streaming Traffic. - Michael Seufert; Pedro Casas; Nikolas Wehner; Li Gang; Kuang Li (ICIN, 2019)

QUICker or not? -an Empirical Analysis of QUIC vs TCP for Video Streaming QoE Provisioning. - Michael Seufert; Raimund Schatz; Nikolas Wehner; Pedro Casas (ICIN, 2019)

Features that Matter: Feature Selection for On-line Stalling Prediction in Encrypted Video Streaming. - Michael Seufert; Pedro Casas; Nikolas Wehner; Li Gang; Kuang Li (INFOCOM Workshops, 2019)

Internet-QoE 2019: 4th Internet-QoE Workshop on QoE-based Analysis and Management of Data Communication Networks. - Pedro Casas; Florian Wamser; Fabián E. Bustamante; David R. Choffnes (MobiCom, 2019)

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)

On the Analysis of YouTube QoE in Cellular Networks through in-Smartphone Measurements. - Sarah Wassermann; Pedro Casas; Michael Seufert; Florian Wamser (WMNC, 2019)

Is QUIC becoming the New TCP? On the Potential Impact of a New Protocol on Networked Multimedia QoE. - Michael Seufert; Raimund Schatz; Nikolas Wehner; Bruno Gardlo; Pedro Casas (QoMEX, 2019)

MLSEC - Benchmarking Shallow and Deep Machine Learning Models for Network Security. - Pedro Casas; Gonzalo Marín; Germán Capdehourat; Maciej Korczynski (IEEE Symposium on Security and Privacy Workshops, 2019)

Deep in the Dark - Deep Learning-Based Malware Traffic Detection Without Expert Knowledge. - Gonzalo Marín; Pedro Casas; Germán Capdehourat (IEEE Symposium on Security and Privacy Workshops, 2019)

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)

Online Detection of Stalling and Scrubbing in Adaptive Video Streaming. - Lorenzo Maggi; Jérémie Leguay; Michael Seufert; Pedro Casas (WiOpt, 2019)

Considering User Behavior in the Quality of Experience Cycle: Towards Proactive QoE-Aware Traffic Management. - Michael Seufert; Sarah Wassermann; Pedro Casas (IEEE Commun. Lett., 2019)

A Survey on Big Data for Network Traffic Monitoring and Analysis. - Alessandro D'Alconzo; Idilio Drago; Andrea Morichetta 002; Marco Mellia; Pedro Casas (IEEE Trans. Netw. Serv. Manag., 2019)

A Fair Share for All: TCP-Inspired Adaptation Logic for QoE Fairness Among Heterogeneous HTTP Adaptive Video Streaming Clients. - Michael Seufert; Nikolas Wehner; Pedro Casas (IEEE Trans. Netw. Serv. Manag., 2019)

Mind the (QoE) Gap: On the Incompatibility of Web and Video QoE Models in the Wild. - Michael Seufert; Nikolas Wehner; Viktoria Wieser; Pedro Casas; Germán Capdehourat (CNSM, 2020)

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 Schüler; Shengming Cai; Hao Shi 002; Jinchun Xu; Tobias Hoßfeld; Dario Rossi 001 (CNSM, 2020)

Preface on the 5th International Workshop on Traffic Measurements for Cybersecurity. - Maciej Korczynski; Wojciech Mazurczyk; Pedro Casas (EuroS&P Workshops, 2020)

WhatsThat? On the Usage of Hierarchical Clustering for Unsupervised Detection & Interpretation of Network Attacks. - Pavol Mulinka; Kensuke Fukuda; Pedro Casas; Lukas Kencl (EuroS&P Workshops, 2020)

Scoring High: Analysis and Prediction of Viewer Behavior and Engagement in the Context of 2018 FIFA WC Live Streaming. - Nikolas Wehner; Michael Seufert; Sebastian Egger-Lampl; Bruno Gardlo; Pedro Casas; Raimund Schatz (ACM Multimedia, 2020)

HUMAN - Hierarchical Clustering for Unsupervised Anomaly Detection & Interpretation. - Pavol Mulinka; Pedro Casas; Kensuke Fukuda; Lukas Kencl (NOF, 2020)

Two Decades of AI4NETS - AI/ML for Data Networks: Challenges & Research Directions. - Pedro Casas (NOMS, 2020)

All that Glitters is not Bitcoin - Unveiling the Centralized Nature of the BTC (IP) Network. - Sami Ben Mariem; Pedro Casas; Matteo Romiti; Benoit Donnet; Rainer Stütz; Bernhard Haslhofer (NOMS, 2020)

Network anomaly detection with net-GAN, a generative adversarial network for analysis of multivariate time-series. - Gastón García González; Pedro Casas; Alicia Fernández; Gabriel Gómez 001 (SIGCOMM Posters and Demos, 2020)

RAL: reinforcement active learning for network traffic monitoring and analysis. - Sarah Wassermann; Thibaut Cuvelier; Pedro Casas (SIGCOMM Posters and Demos, 2020)

How good is your mobile (web) surfing?: speed index inference from encrypted traffic. - Sarah Wassermann; Pedro Casas; Michael Seufert; Nikolas Wehner; Joshua Schüler; Tobias Hossfeld (SIGCOMM Posters and Demos, 2020)

DeepMAL - Deep Learning Models for Malware Traffic Detection and Classification. - Gonzalo Marín; Pedro Casas; Germán Capdehourat (CoRR, 2020)

White Paper on Crowdsourced Network and QoE Measurements - Definitions, Use Cases and Challenges. - Tobias Hoßfeld; Stefan Wunderer; André Beyer; Andrew Hall; Anika Schwind; Christian Gassner; Fabrice Guillemin; Florian Wamser; Krzysztof Wascinski; Matthias Hirth; Michael Seufert; Pedro Casas; et al. (CoRR, 2020)

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 Trans. Netw. Serv. Manag., 2020)

Where is the Light(ning) in the Taproot Dawn? Unveiling the Bitcoin Lightning (IP) Network. - Pedro Casas; Matteo Romiti; Peter Holzer; Sami Ben Mariem; Benoit Donnet; Bernhard Haslhofer (CloudNet, 2021)

How are your Apps Doing? QoE Inference and Analysis in Mobile Devices. - Nikolas Wehner; Michael Seufert; Joshua Schüler; Pedro Casas; Tobias Hoßfeld (CNSM, 2021)

Quality that Matters: QoE Monitoring in Education Service Provider (ESP) Networks. - Nikolas Wehner; Michael Seufert; Viktoria Wieser; Pedro Casas; Germán Capdehourat (IM, 2021)

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 Schüler; Tobias Hossfeld (WMNC, 2021)

Content Matters: Clustering Web Pages for QoE Analysis With WebCLUST. - Luis Roberto Jiménez; Marta Solera Delgado; Matías Toril; Carolina Gijón; Pedro Casas (IEEE Access, 2021)

On the Usage of Generative Models for Network Anomaly Detection in Multivariate Time-Series. - Gastón García González; Pedro Casas; Alicia Fernández; Gabriel Gómez 001 (SIGMETRICS Perform. Evaluation Rev., 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)

Adaptive and Reinforcement Learning Approaches for Online Network Monitoring and Analysis. - Sarah Wassermann; Thibaut Cuvelier; Pavol Mulinka; Pedro Casas (IEEE Trans. Netw. Serv. Manag., 2021)

Fingerprinting Web Pages and Smartphone Apps from Encrypted Network Traffic with WebScanner. - Pedro Casas; Nikolas Wehner; Sarah Wassermann; Michael Seufert (CloudNet, 2022)

GROWS: improving decentralized resource allocation in wireless networks through graph neural networks. - Martín Randall; Pablo Belzarena; Federico Larroca; Pedro Casas (GNNet@CoNEXT, 2022)

DC-VAE, Fine-grained Anomaly Detection in Multivariate Time-Series with Dilated Convolutions and Variational Auto Encoders. - Gastón García González; Sergio Martinez Tagliafico; Alicia Fernández; Gabriel Gómez 001; José Acuña; Pedro Casas (EuroS&P Workshops, 2022)

PHISHWEB: a progressive, multi-layered system for phishing websites detection. - Lucas Torrealba Aravena; Javier Bustos-Jiménez; Pedro Casas (IMC, 2022)

Steps towards continual learning in multivariate time-series anomaly detection using variational autoencoders. - Gastón García González; Pedro Casas; Alicia Fernández; Gabriel Gómez 001 (IMC, 2022)

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)

Deep Reinforcement Learning and Graph Neural Networks for Efficient Resource Allocation in 5G Networks. - Martín Randall; Pablo Belzarena; Federico Larroca; Pedro Casas (LATINCOM, 2022)

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)

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)

Smart Active Sampling to enhance Quality Assurance Efficiency. - Clemens Heistracher; Stefan Stricker; Pedro Casas; Daniel Schall 001; Jana Kemnitz (CoRR, 2022)

Dom2Vec - Detecting DGA Domains Through Word Embeddings and AI/ML-Driven Lexicographic Analysis. - Lucas Torrealba Aravena; Pedro Casas; Javier Bustos-Jiménez; Germán Capdehourat; Mislav Findrik (CNSM, 2023)

Fake it till you Detect it: Continual Anomaly Detection in Multivariate Time-Series using Generative AI. - Gastón García González; Pedro Casas; Alicia Fernández (EuroS&P Workshops, 2023)

Should I Sample it or Not? Improving Quality Assurance Efficiency Through Smart Active Sampling. - Clemens Heistracher; Pedro Casas; Stefan Stricker; Axel Weißenfeld; Daniel Schall 001; Jana Kemnitz (IECON, 2023)

Phish Me If You Can - Lexicographic Analysis and Machine Learning for Phishing Websites Detection with PHISHWEB. - Lucas Torrealba Aravena; Pedro Casas; Javier Bustos-Jiménez; Germán Capdehourat; Mislav Findrik (NetSoft, 2023)

Not all DGAs are Born the Same - Improving Lexicographic based Detection of DGA Domains through AI/ML. - Lucas Torrealba Aravena; Pedro Casas; Javier Bustos-Jiménez; Germán Capdehourat; Mislav Findrik (TMA, 2023)

Deep Generative Replay for Multivariate Time-Series Monitoring with Variational Autoencoders. - Gastón García González; Pedro Casas; Alicia Fernández (TMA, 2023)

TELCO. - Gastón García González; Sergio Martinez Tagliafico; Alicia Fernández; Gabriel Gómez 001; José Acuña; Pedro Casas (IEEE DataPort, 2023)

Agree to Disagree: Exploring Consensus of XAI Methods for ML-based NIDS. - Katharina Dietz 001; Mehrdad Hajizadeh; Johannes Schleicher; Nikolas Wehner; Stefan Geißler; Pedro Casas; Michael Seufert; Tobias Hoßfeld (CNSM, 2024)

Certainly Uncertain: Demystifying ML Uncertainty for Active Learning in Network Monitoring Tasks. - Katharina Dietz 001; Mehrdad Hajizadeh; Nikolas Wehner; Stefan Geißler; Pedro Casas; Michael Seufert; Tobias Hoßfeld (CNSM, 2024)

On the Quest for Foundation Generative-AI Models for Anomaly Detection in Time-Series Data. - Gastón García González; Pedro Casas; Emilio Martínez; Alicia Fernández (EuroS&P Workshops, 2024)

Detecting Attacks at Switching Speed: Ai/Ml and Active Learning for in-Network Monitoring in Data Planes. - Belén Brandino; Pedro Casas; Eduardo Grampín (ICNP, 2024)

More than Words is What you Need - Detecting DGA and Phishing Domains with Dom2Vec Word Embeddings. - Lucas Torrealba Aravena; Pedro Casas; Javier Bustos-Jiménez; Mislav Findrik (TMA, 2024)

HALIDS: a Hardware-Assisted Machine Learning IDS for in-Network Monitoring. - Belén Brandino; Eduardo Grampín; Katharina Dietz 001; Nikolas Wehner; Michael Seufert; Tobias Hoßfeld; Pedro Casas (TMA, 2024)

Timeless Foundations: Exploring DC-VAEs as Foundation Models for Time Series Analysis. - Gastón García González; Pedro Casas; Emilio Martínez; Alicia Fernández (TMA, 2024)

One Model to Find Them All Deep Learning for Multivariate Time-Series Anomaly Detection in Mobile Network Data. - Gastón García González; Sergio Martinez Tagliafico; Alicia Fernández; Gabriel Gómez Sena; José Acuña; Pedro Casas (IEEE Trans. Netw. Serv. Manag., 2024)

Marina: Realizing ML-Driven Real-Time Network Traffic Monitoring at Terabit Scale. - Michael Seufert; Katharina Dietz 001; Nikolas Wehner; Stefan Geißler; Joshua Schüler; Manuel Wolz; Andreas Hotho; Pedro Casas; Tobias Hoßfeld; Anja Feldmann (IEEE Trans. Netw. Serv. Manag., 2024)

Hunting Review Bombs with BRIDGE - A Bipartite Graph Neural Network Approach to Abuse Detection. - Gonzalo Sobarzo Abufon; Juan Vanerio; Javier Bustos-Jiménez; Pedro Casas (EuroS&P (Workshops), 2025)

User Association in Wireless Networks with Distributed GNN-Based Reinforcement Learning. - Martín Randall; Santiago Paternain; Pedro Casas; Federico Larroca; Pablo Belzarena (NTMS, 2025)

TSGFM - Towards a Graph Foundation Model for Time Series Analysis in Network Monitoring. - Hamid Latif-Martínez; Pedro Casas; José Suárez-Varela; Albert Cabellos-Aparicio; Pere Barlet-Ros (TMA, 2025)

Do We Really Need Reference-Based Phishing Detection? Unleashing the Power of GNN. - Tailai Song; Pedro Casas; Michela Meo (TMA, 2025)

FREKit: A Flexible Simulator for Probabilistic Congestion and Rerouting in Multi-Protocol Networks. - Juan Vanerio; Pedro Casas; Stefan Schmid 001 (TMA, 2025)

Towards Intelligent Resource Allocation in Highly-Distributed Content Delivery Networks Using Graph Neural Networks. - Juan Vanerio; Pedro Casas; Stefan Schmid 001 (TMA, 2025)

Exploring the application of Time Series Foundation Models to network monitoring tasks. - Nikolas Wehner; Pedro Casas; Katharina Dietz 001; Stefan Geißler; Tobias Hoßfeld; Michael Seufert (Comput. Networks, 2025)

Towards Foundation Auto-Encoders for Time-Series Anomaly Detection. - Gastón García González; Pedro Casas; Emilio Martínez; Alicia Fernández (CoRR, 2025)