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Improving Web QoE Monitoring for Encrypted Network Traffic through Time Series Modeling

, , , , , и . ACM SIGMETRICS Performance Evaluation Review, 48 (4): 37-40 (марта 2021)

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Stellio Casas

Marçal Casas Cartagena

Gilbert Casasus

Benno Pedrotti

Corella Susana Casas Delucchi

 

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Machine-Learning Based Approaches for Anomaly Detection and Classification in Cellular Networks., , и . TMA, IFIP, (2016)DeepSec meets RawPower - Deep Learning for Detection of Network Attacks Using Raw Representations., , и . SIGMETRICS Perform. Evaluation Rev., 46 (3): 147-150 (2018)Considering User Behavior in the Quality of Experience Cycle: Towards Proactive QoE-aware Traffic Management, , и . IEEE Communications Letters, 23 (7): 1145-1148 (июля 2019)Should I (re)Learn or Should I Go(on)?: Stream Machine Learning for Adaptive Defense against Network Attacks., , и . MTD@CCS, стр. 79-88. ACM, (2019)Preface on the 5th International Workshop on Traffic Measurements for Cybersecurity., , и . EuroS&P Workshops, стр. 521. IEEE, (2020)Demystifying user-based active learning for network monitoring tasks, , , , и . (2023)YouTube all around: Characterizing YouTube from mobile and fixed-line network vantage points., , , , , и . EuCNC, стр. 1-5. IEEE, (2014)Network security and anomaly detection with Big-DAMA, a big data analytics framework., , , , и . CloudNet, стр. 16-22. IEEE, (2017)On the use of Sub-Space Clustering & Evidence Accumulation for traffic analysis & classification., , и . IWCMC, стр. 1016-1021. IEEE, (2011)Detecting and diagnosing anomalies in cellular networks using Random Neural Networks., , , и . IWCMC, стр. 351-356. IEEE, (2016)