| A Survey on Big Data for Network Traffic Monitoring and Analysis | 5 | 0.43 | 2019 |
| Call Detail Records for Human Mobility Studies: Taking Stock of the Situation in the \"Always Connected Era\" | 1 | 0.34 | 2017 |
| A method for identifying compromised clients based on DNS traffic analysis. | 7 | 0.44 | 2017 |
| POSTER: (Semi)-Supervised Machine Learning Approaches for Network Security in High-Dimensional Network Data. | 2 | 0.43 | 2016 |
| Machine learning, data mining and Big Data frameworks for network monitoring and troubleshooting. | 0 | 0.34 | 2016 |
| Unveiling network and service performance degradation in the wild with mplane. | 7 | 0.51 | 2016 |
| When smartphones become the enemy: unveiling mobile apps anomalies through clustering techniques. | 0 | 0.34 | 2016 |
| Machine-Learning Based Approaches for Anomaly Detection and Classification in Cellular Networks. | 1 | 0.35 | 2016 |
| Mining agile DNS traffic using graph analysis for cybercrime detection. | 5 | 0.44 | 2016 |
| DBStream: A holistic approach to large-scale network traffic monitoring and analysis. | 4 | 0.42 | 2016 |
| Big-DAMA: Big Data Analytics for Network Traffic Monitoring and Analysis. | 1 | 0.40 | 2016 |
| Grasping Popular Applications in Cellular Networks With Big Data Analytics Platforms. | 2 | 0.36 | 2016 |
| On the ground truth problem of malicious DNS traffic analysis | 14 | 0.79 | 2015 |
| RCATool - A Framework for Detecting and Diagnosing Anomalies in Cellular Networks | 4 | 0.41 | 2015 |
| Device-Specific Traffic Characterization for Root Cause Analysis in Cellular Networks. | 5 | 0.47 | 2015 |
| Challenging Entropy-based Anomaly Detection and Diagnosis in Cellular Networks. | 1 | 0.39 | 2015 |
| Online Social Networks anatomy: On the analysis of Facebook and WhatsApp in cellular networks | 5 | 0.40 | 2015 |
| On the detection of network traffic anomalies in content delivery network services | 7 | 0.57 | 2014 |
| When YouTube Does not Work—Analysis of QoE-Relevant Degradation in Google CDN Traffic | 21 | 0.80 | 2014 |
| Characterizing web services provisioning via CDNs: The case of Facebook | 6 | 0.51 | 2014 |
| YouTube in the move: Understanding the performance of YouTube in cellular networks | 8 | 0.51 | 2014 |
| YouTube all around: Characterizing YouTube from mobile and fixed-line network vantage points | 1 | 0.37 | 2014 |
| On the analysis of QoE-based performance degradation in YouTube traffic | 1 | 0.37 | 2014 |
| Botnet detection revisited: Theory and practice of finding malicious P2P networks via Internet connection graphs | 3 | 0.48 | 2013 |
| On the optimality of max-min fairness in resource allocation. | 8 | 0.73 | 2012 |
| COMINDIS - COllaborative Monitoring with MINimum DISclosure (Poster) | 0 | 0.34 | 2011 |
| Collaborative Network Defense with Minimum Disclosure. | 1 | 0.39 | 2011 |
| The Logarithmic Nature of QoE and the Role of the Weber-Fechner Law in QoE Assessment | 96 | 5.34 | 2010 |
| A review of DoS attack models for 3G cellular networks from a system-design perspective | 13 | 0.71 | 2010 |
| Distribution-based anomaly detection in 3G mobile networks: from theory to practice | 17 | 1.24 | 2010 |
| Performance of Markov models for frame-level errors in IEEE 802.11 wireless LANs | 6 | 0.46 | 2009 |
| A distribution-based approach to anomaly detection and application to 3G mobile traffic | 18 | 1.39 | 2009 |
| Network-Wide Measurements of TCP RTT in 3G | 25 | 2.03 | 2009 |
| Exploiting Cellular Networks For Road Traffic Estimation: A Survey And A Research Roadmap | 26 | 1.98 | 2009 |
| Modeling of call dropping in well-established cellular networks | 9 | 0.54 | 2007 |
