| 2025 | CNSM | Malicious Domain Names Detection with DeepDGA, a Hybrid Character and Word Embeddings Deep Learning Architecture. | Lucas Torrealba Aravena, Pedro Casas, Diego Garca, Javier Bustos-Jimnez, Ivana Bachmann |
| 2025 | CNSM | TSGFM - Graph Neural Networks for Zero-Shot Time Series Forecasting in Network Monitoring. | Hamid Latif-Martnez, Juan Vanerio, Pedro Casas, Jos Surez-Varela, Albert Cabellos-Aparicio, Pere Barlet-Ros |
| 2024 | CNSM | Agree to Disagree: Exploring Consensus of XAI Methods for ML-based NIDS. | Katharina Dietz, Mehrdad Hajizadeh, Johannes Schleicher, Nikolas Wehner, Stefan Geiler, Pedro Casas, Michael Seufert, Tobias Hofeld |
| 2024 | CNSM | Certainly Uncertain: Demystifying ML Uncertainty for Active Learning in Network Monitoring Tasks. | Katharina Dietz, Mehrdad Hajizadeh, Nikolas Wehner, Stefan Geiler, Pedro Casas, Michael Seufert, Tobias Hofeld |
| 2024 | ICNP | Detecting Attacks at Switching Speed: Ai/Ml and Active Learning for in-Network Monitoring in Data Planes. | Beln Brandino, Pedro Casas, Eduardo Grampn |
| 2023 | CNSM | Dom2Vec - Detecting DGA Domains Through Word Embeddings and AI/ML-Driven Lexicographic Analysis. | Lucas Torrealba Aravena, Pedro Casas, Javier Bustos-Jimnez, Germn Capdehourat, Mislav Findrik |
| 2023 | IECON | Should I Sample it or Not? Improving Quality Assurance Efficiency Through Smart Active Sampling. | Clemens Heistracher, Pedro Casas, Stefan Stricker, Axel Weienfeld, Daniel Schall, Jana Kemnitz |
| 2023 | NetSoft | Phish Me If You Can - Lexicographic Analysis and Machine Learning for Phishing Websites Detection with PHISHWEB. | Lucas Torrealba Aravena, Pedro Casas, Javier Bustos-Jimnez, Germn Capdehourat, Mislav Findrik |
| 2022 | CoNEXT | GROWS: improving decentralized resource allocation in wireless networks through graph neural networks. | Martn Randall, Pablo Belzarena, Federico Larroca, Pedro Casas |
| 2022 | IMC | Untitled record | Lucas Torrealba Aravena, Javier Bustos-Jimnez, Pedro Casas |
| 2022 | IMC | Steps towards continual learning in multivariate time-series anomaly detection using variational autoencoders. | Gastn Garca Gonzlez, Pedro Casas, Alicia Fernndez, Gabriel Gmez |
| 2022 | NetSoft | 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 |
| 2021 | CNSM | How are your Apps Doing? QoE Inference and Analysis in Mobile Devices. | Nikolas Wehner, Michael Seufert, Joshua Schler, Pedro Casas, Tobias Hofeld |
| 2021 | IM | Quality that Matters: QoE Monitoring in Education Service Provider (ESP) Networks. | Nikolas Wehner, Michael Seufert, Viktoria Wieser, Pedro Casas, Germn Capdehourat |
| 2020 | CNSM | Mind the (QoE) Gap: On the Incompatibility of Web and Video QoE Models in the Wild. | Michael Seufert, Nikolas Wehner, Viktoria Wieser, Pedro Casas, Germn Capdehourat |
| 2020 | CNSM | 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 Schler, Shengming Cai, Hao Shi, Jinchun Xu, Tobias Hofeld, Dario Rossi |
| 2020 | NOMS | Two Decades of AI4NETS - AI/ML for Data Networks: Challenges & Research Directions. | Pedro Casas |
| 2020 | NOMS | 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 Sttz, Bernhard Haslhofer |
| 2020 | SIGCOMM | Network anomaly detection with net-GAN, a generative adversarial network for analysis of multivariate time-series. | Gastn Garca Gonzlez, Pedro Casas, Alicia Fernndez, Gabriel Gmez |
| 2020 | SIGCOMM | RAL: reinforcement active learning for network traffic monitoring and analysis. | Sarah Wassermann, Thibaut Cuvelier, Pedro Casas |
| 2020 | SIGCOMM | How good is your mobile (web) surfing?: speed index inference from encrypted traffic. | Sarah Wassermann, Pedro Casas, Michael Seufert, Nikolas Wehner, Joshua Schler, Tobias Hossfeld |
| 2019 | CCS | 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 |
| 2019 | CNSM | ADAM & RAL: Adaptive Memory Learning and Reinforcement Active Learning for Network Monitoring. | Sarah Wassermann, Thibaut Cuvelier, Pavol Mulinka, Pedro Casas |
| 2019 | CoNEXT | EXPLAIN-IT: Towards Explainable AI for Unsupervised Network Traffic Analysis. | Andrea Morichetta, Pedro Casas, Marco Mellia |
| 2019 | ICIN | Stream-based Machine Learning for Real-time QoE Analysis of Encrypted Video Streaming Traffic. | Michael Seufert, Pedro Casas, Nikolas Wehner, Li Gang, Kuang Li |
| 2019 | ICIN | QUICker or not? -an Empirical Analysis of QUIC vs TCP for Video Streaming QoE Provisioning. | Michael Seufert, Raimund Schatz, Nikolas Wehner, Pedro Casas |
| 2019 | INFOCOM | Features that Matter: Feature Selection for On-line Stalling Prediction in Encrypted Video Streaming. | Michael Seufert, Pedro Casas, Nikolas Wehner, Li Gang, Kuang Li |
| 2019 | MOBICOM | Internet-QoE 2019: 4th Internet-QoE Workshop on QoE-based Analysis and Management of Data Communication Networks. | Pedro Casas, Florian Wamser, Fabin E. Bustamante, David R. Choffnes |
| 2019 | MOBICOM | 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 |
| 2019 | QoMEX | 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 |
| 2019 | SP | MLSEC - Benchmarking Shallow and Deep Machine Learning Models for Network Security. | Pedro Casas, Gonzalo Marn, Germn Capdehourat, Maciej Korczynski |
| 2019 | SP | Deep in the Dark - Deep Learning-Based Malware Traffic Detection Without Expert Knowledge. | Gonzalo Marn, Pedro Casas, Germn Capdehourat |
| 2019 | WiOpt | Online Detection of Stalling and Scrubbing in Adaptive Video Streaming. | Lorenzo Maggi, Jrmie Leguay, Michael Seufert, Pedro Casas |
| 2018 | CNSM | A Fair Share for All: Novel Adaptation Logic for QoE Fairness of HTTP Adaptive Video Streaming. | Michael Seufert, Nikolas Wehner, Pedro Casas, Florian Wamser |
| 2018 | CNSM | 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 |
| 2018 | EDBT | MLNET - Machine Learning Models for Network Analytics. | Pedro Casas |
| 2018 | ICDCS | Enhancing Machine Learning Based QoE Prediction by Ensemble Models. | Pedro Casas, Michael Seufert, Nikolas Wehner, Anika Schwind, Florian Wamser |
| 2018 | ICDCS | Studying the Impact of HAS QoE Factors on the Standardized QoE Model P.1203. | Michael Seufert, Nikolas Wehner, Pedro Casas |
| 2018 | QoMEX | Streaming Characteristics of Spotify Sessions. | Anika Schwind, Florian Wamser, Thomas Gensler, Phuoc Tran-Gia, Michael Seufert, Pedro Casas |
| 2018 | WCNC | Machine learning models for wireless network monitoring and analysis. | Pedro Casas |
| 2018 | SIGCOMM | RawPower: Deep Learning based Anomaly Detection from Raw Network Traffic Measurements. | Gonzalo Marn, Pedro Casas, Germn Capdehourat |
| 2018 | SIGCOMM | Stream-based Machine Learning for Network Security and Anomaly Detection. | Pavol Mulinka, Pedro Casas |
| 2018 | SIGCOMM | Adaptive Network Security through Stream Machine Learning. | Pavol Mulinka, Pedro Casas |
| 2018 | SIGCOMM | BIGMOMAL: Big Data Analytics for Mobile Malware Detection. | Sarah Wassermann, Pedro Casas |
| 2017 | CNSM | GML learning, a generic machine learning model for network measurements analysis. | Pedro Casas, Juan Martin Vanerio, Kensuke Fukuda |
| 2017 | QoMEX | 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 |
| 2017 | QoMEX | 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 |
| 2017 | SIGCOMM | Ensemble-learning Approaches for Network Security and Anomaly Detection. | Juan Martin Vanerio, Pedro Casas |
| 2017 | SIGCOMM | NETPerfTrace: Predicting Internet Path Dynamics and Performance with Machine Learning. | Sarah Wassermann, Pedro Casas, Thibaut Cuvelier, Benoit Donnet |
| 2017 | WiMob | Super learning for anomaly detection in cellular networks. | Pedro Casas, Juan Martin Vanerio |
| 2016 | CCS | 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 |
| 2016 | GLOBECOM | The Beauty of Consistency in Radio-Scheduling Decisions. | Eirini Liotou, Raimund Schatz, Andreas Sackl, Pedro Casas, Dimitris Tsolkas, Nikos I. Passas, Lazaros F. Merakos |
| 2016 | IWCMC | Detecting and diagnosing anomalies in cellular networks using Random Neural Networks. | Pedro Casas, Alessandro D'Alconzo, Pierdomenico Fiadino, Christian Callegari |
| 2016 | LCN | On the Analysis of Internet Paths with DisNETPerf, a Distributed Paths Performance Analyzer. | Sarah Wassermann, Pedro Casas, Benoit Donnet, Guy Leduc, Marco Mellia |
| 2016 | MOBICOM | When smartphones become the enemy: unveiling mobile apps anomalies through clustering techniques. | Pedro Casas, Pierdomenico Fiadino, Alessandro D'Alconzo |
| 2016 | SIGCOMM | Big-DAMA: Big Data Analytics for Network Traffic Monitoring and Analysis. | Pedro Casas, Alessandro D'Alconzo, Tanja Zseby, Marco Mellia |
| 2016 | SIGCOMM | An Educated Guess on QoE in Operational Networks through Large-Scale Measurements. | Pedro Casas, Bruno Gardlo, Raimund Schatz, Marco Mellia |
| 2016 | SIGCOMM | Looking for Network Latency Clusters in the LAC Region. | Agustin Formoso, Pedro Casas |
| 2016 | SIGCOMM | WhatsApp Calling: a Revised Analysis on WhatsApp's Architecture and Calling Service. | Juan Martin Vanerio, Pedro Casas |
| 2015 | CNSM | Taming QoE in cellular networks: From subjective lab studies to measurements in the field. | Pedro Casas, Bruno Gardlo, Michael Seufert, Florian Wamser, Raimund Schatz |
| 2015 | ICDE | Cache-oblivious scheduling of shared workloads. | Arian Br, Lukasz Golab, Stefan Ruehrup, Mirko Schiavone, Pedro Casas |
| 2015 | IWCMC | On the analysis of QoE in cellular networks: From subjective tests to large-scale traffic measurements. | Pedro Casas, Martn Varela, Pierdomenico Fiadino, Mirko Schiavone, Helena Rivas, Raimund Schatz |
| 2015 | IWCMC | Towards automatic detection and diagnosis of Internet service anomalies via DNS traffic analysis. | Pierdomenico Fiadino, Alessandro D'Alconzo, Mirko Schiavone, Pedro Casas |
| 2015 | IWCMC | 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 |
| 2015 | MOBICOM | 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 |
| 2015 | MOBICOM | 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 |
| 2015 | Networking | Online Social Networks anatomy: On the analysis of Facebook and WhatsApp in cellular networks. | Pierdomenico Fiadino, Pedro Casas, Mirko Schiavone, Alessandro D'Alconzo |
| 2015 | QoMEX | Quantifying the impact of network bandwidth fluctuations and outages on Web QoE. | Andreas Sackl, Pedro Casas, Raimund Schatz, Lucjan Janowski, Ralf Irmer |
| 2015 | SIGCOMM | 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 |
| 2015 | SIGCOMM | Challenging Entropy-based Anomaly Detection and Diagnosis in Cellular Networks. | Pierdomenico Fiadino, Alessandro D'Alconzo, Mirko Schiavone, Pedro Casas |
| 2014 | CNSM | On the analysis of QoE-based performance degradation in YouTube traffic. | Pedro Casas, Alessandro D'Alconzo, Pierdomenico Fiadino, Arian Br, Alessandro Finamore |
| 2014 | CoNEXT | Diagnosing Device-Specific Anomalies in Cellular Networks. | Mirko Schiavone, Peter Romirer-Maierhofer, Pierdomenico Fiadino, Pedro Casas |
| 2014 | IWCMC | DBStream: An online aggregation, filtering and processing system for network traffic monitoring. | Arian Br, Pedro Casas, Lukasz Golab, Alessandro Finamore |
| 2014 | IWCMC | Coping with 0-day attacks through Unsupervised Network Intrusion Detection. | Pedro Casas, Johan Mazel, Philippe Owezarski |
| 2014 | IWCMC | Who to blame when YouTube is not working? detecting anomalies in CDN-provisioned services. | Alessandro D'Alconzo, Pedro Casas, Pierdomenico Fiadino, Arian Br, Alessandro Finamore |
| 2014 | IWCMC | Characterizing web services provisioning via CDNs: The case of Facebook. | Pierdomenico Fiadino, Alessandro D'Alconzo, Pedro Casas |
| 2014 | PAM | Understanding HTTP Traffic and CDN Behavior from the Eyes of a Mobile ISP. | Pedro Casas, Pierdomenico Fiadino, Arian Br |
| 2014 | SIGCOMM | Vivisecting whatsapp through large-scale measurements in mobile networks. | Pierdomenico Fiadino, Mirko Schiavone, Pedro Casas |
| 2013 | IM | Quality of experience in remote virtual desktop services. | Pedro Casas, Michael Seufert, Sebastian Egger, Raimund Schatz |
| 2013 | IWCMC | Mini-IPC: A minimalist approach for HTTP traffic classification using IP addresses. | Pedro Casas, Pierdomenico Fiadino |
| 2013 | WCNC | Monitoring YouTube QoE: Is Your Mobile Network Delivering the Right Experience to your Customers? | Pedro Casas, Raimund Schatz, Tobias Hofeld |
| 2012 | GLOBECOM | YouTube & Facebook Quality of Experience in mobile broadband networks. | Pedro Casas, Andreas Sackl, Sebastian Egger, Raimund Schatz |
| 2011 | CNSM | Sub-Space clustering, Inter-Clustering Results Association & anomaly correlation for unsupervised network anomaly detection. | Johan Mazel, Pedro Casas, Yann Labit, Philippe Owezarski |
| 2011 | IWCMC | On the use of Sub-Space Clustering & Evidence Accumulation for traffic analysis & classification. | Pedro Casas, Johan Mazel, Philippe Owezarski |
| 2011 | Networking | UNADA: Unsupervised Network Anomaly Detection Using Sub-space Outliers Ranking. | Pedro Casas, Johan Mazel, Philippe Owezarski |
| 2010 | IWCMC | On the use of random neural networks for traffic matrix estimation in large-scale IP networks. | Pedro Casas, Sandrine Vaton |