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Service Usage Classification with Encrypted Internet Traffic in Mobile Messaging Apps
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-540-24668-8_21openalex-snapshot
Flow Clustering Using Machine Learning Techniques
inferredcites →https://doi.org/10.1007/978-3-540-45231-7_26openalex-snapshot
Fuzzy Clustering Based Segmentation of Time-Series
inferredcites →https://doi.org/10.1007/978-3-642-36516-4_7openalex-snapshot
Understanding Mobile App Usage Patterns Using In-App Advertisements
inferredcites →https://doi.org/10.1016/0098-1354(94)85029-1openalex-snapshot
Representation of process trends—IV. Induction of real-time patterns from operating data for diagnosis and supervisory control
inferredcites →https://doi.org/10.1016/j.comnet.2009.05.003openalex-snapshot
Support Vector Machines for TCP traffic classification
inferredcites →https://doi.org/10.1080/03610910701723971openalex-snapshot
Time Series Classification Based on Spectral Analysis
inferredcites →https://doi.org/10.1109/cisda.2009.5356534openalex-snapshot
Machine learning based encrypted traffic classification: Identifying SSH and Skype
inferredcites →https://doi.org/10.1109/icde.1996.492204openalex-snapshot
Approximate queries and representations for large data sequences
inferredcites →https://doi.org/10.1109/icdm.2001.989520openalex-snapshot
Time series segmentation for context recognition in mobile devices
inferredcites →https://doi.org/10.1109/icdm.2002.1183990openalex-snapshot
Estimating the number of segments in time series data using permutation tests
inferredcites →https://doi.org/10.1109/lcn.2005.35openalex-snapshot
Automated traffic classification and application identification using machine learning
inferredcites →https://doi.org/10.1109/sp.2012.28openalex-snapshot
Peek-a-Boo, I Still See You: Why Efficient Traffic Analysis Countermeasures Fail
inferredcites →https://doi.org/10.1109/tkde.2007.190737openalex-snapshot
Streaming Time Series Summarization Using User-Defined Amnesic Functions
inferredcites →https://doi.org/10.1109/tnn.2006.883010openalex-snapshot
Bayesian Neural Networks for Internet Traffic Classification
inferredcites →https://doi.org/10.1109/tnsm.2013.022713.120250openalex-snapshot
An Effective Network Traffic Classification Method with Unknown Flow Detection
inferredcites →https://doi.org/10.1109/tpds.2012.98openalex-snapshot
Network Traffic Classification Using Correlation Information
inferredcites →https://doi.org/10.1145/1028788.1028804openalex-snapshot
Transport layer identification of P2P traffic
inferredcites →https://doi.org/10.1145/1064212.1064220openalex-snapshot
Internet traffic classification using bayesian analysis techniques
inferredcites →https://doi.org/10.1145/1129582.1129589openalex-snapshot
Traffic classification on the fly
inferredcites →https://doi.org/10.1145/1162678.1162679openalex-snapshot
Traffic classification using clustering algorithms
inferredcites →https://doi.org/10.1145/1163593.1163596openalex-snapshot
A preliminary performance comparison of five machine learning algorithms for practical IP traffic flow classification
inferredcites →https://doi.org/10.1145/1298306.1298349openalex-snapshot
Network monitoring using traffic dispersion graphs (tdgs)
inferredcites →https://doi.org/10.1145/1544012.1544023openalex-snapshot
Internet traffic classification demystified
inferredcites →https://doi.org/10.1145/1814433.1814453openalex-snapshot
Diversity in smartphone usage
inferredcites →https://doi.org/10.1145/1999995.2000026openalex-snapshot
Profiling resource usage for mobile applications
inferredcites →https://doi.org/10.1145/2068816.2068847openalex-snapshot
Identifying diverse usage behaviors of smartphone apps
inferredcites →https://doi.org/10.1145/2390231.2390248openalex-snapshot
A quest for an Internet video quality-of-experience metric
inferredcites →https://doi.org/10.1145/2677046.2677048openalex-snapshot
Traffic Analysis of Encrypted Messaging Services
inferredcites →https://doi.org/10.1145/988672.988742openalex-snapshot
Accurate, scalable in-network identification of p2p traffic using application signatures
inferredcites →https://doi.org/10.1287/mnsc.1110.1350openalex-snapshot
An Empirical Analysis of User Content Generation and Usage Behavior on the Mobile Internet
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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A Location-Based Test for Jurisdiction over Data: The Consequences for Global Online Privacy
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Online Encrypted Traffic Classification Based on Lightweight Neural Networks *
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OTTer: A Scalable High-Resolution Encrypted Traffic Identification Engine
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Automated IoT Device Fingerprinting Through Encrypted Stream Classification
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A Configurable Agent to Advance Peers’ Productive Dialogue in MOOCs
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MAAN: A Multiple Attribute Association Network for Mobile Encrypted Traffic Classification
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Mobile Application Behavior Recognition Based on Dual-Domain Attention and Meta-learning
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Multi-granularity Mobile Encrypted Traffic Classification Based on Fusion Features
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The Dynamic Update of Mobile Apps: A Research Design with HMM Method
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Artificial Intelligence-Based Approaches for Anomaly Detection
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Research on Lightweight Learning in the Field of Traffic Analysis
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Only Header: a reliable encrypted traffic classification framework without privacy risk
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A survey on analyzing encrypted network traffic of mobile devices
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Seq2Path: a sequence-to-path-based flow feature fusion approach for encrypted traffic classification
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Machine Learning Based Classification Accuracy of Encrypted Service Channels: Analysis of Various Factors
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Privacy-Preserving Top-k Location-based Services Retrieval in Mobile Internet
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Data representation for CNN based internet traffic classification: a comparative study
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Hybridization of Mean Shift Clustering and Deep Packet Inspected Classification for Network Traffic Analysis
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Classifying encrypted traffic using adaptive fingerprints with multi-level attributes
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SFIM: Identify user behavior based on stable features
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A review on machine learning–based approaches for Internet traffic classification
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MIMETIC: Mobile encrypted traffic classification using multimodal deep learning
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App trajectory recognition over encrypted internet traffic based on deep neural network
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MATEC: A lightweight neural network for online encrypted traffic classification
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EC-GCN: A encrypted traffic classification framework based on multi-scale graph convolution networks
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BTG-RF: Recognizing Douyin payment behaviors based on behavioral traffic graph analysis
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Traffic burst relational graph attention network combined position encoding for traffic classification
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Let model keep evolving: Incremental learning for encrypted traffic classification
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Recognizing the content types of network traffic based on a hybrid DNN-HMM model
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Signature identification and user activity analysis on WhatsApp Web through network data
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How much training data is enough to move a ML-based classifier to a different network?
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Towards Video Flow Classification at a Million Encrypted Flows Per Second
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Customer Segmentation Using Mobile Phone Usage Data to Reveal Finance Application User’s Behavior
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Enhanced Encrypted Traffic Classification Through Packet-Flow Dual Views
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Malicious encrypted network traffic flow detection using enhanced optimal deep feature selection with DLSTM
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Effective and Real-time In-App Activity Analysis in Encrypted Internet Traffic Streams
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A Multi-Label Multi-View Learning Framework for In-App Service Usage Analysis
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Exploiting Diversity in Android TLS Implementations for Mobile App Traffic Classification
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Trigger relationship aware mobile traffic classification
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A Survey on Encrypted Network Traffic Analysis Applications, Techniques, and Countermeasures
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Hierarchical Multimodal LLMs with Semantic Space Alignment for Enhanced Time Series Classification
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A clustering-based analysis of DPI-labeled video flow characteristics in cellular networks
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A Survey on TLS-Encrypted Malware Network Traffic Analysis Applicable to Security Operations Centers
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Fast and Accurate Multi-Task Learning for Encrypted Network Traffic Classification
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Cloud Database Analysis of Instant Messaging Apps on Mobile Devices
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Efficient Fingerprinting Attack on Web Applications: An Adaptive Symbolization Approach
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Identifying WeChat Message Types without Using Traditional Traffic
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Hierarchical Identifier: Application to User Privacy Eavesdropping on Mobile Payment App
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A Relation-based Method for Robust Malicious Traffic Detection
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Identifying VoIP traffic in VPN tunnel via Flow Spatio-Temporal Features
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Mobile Traffic Classification through Physical Channel Fingerprinting: a Deep Learning Approach
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Data analytics for mobile traffic in 5G networks using machine learning techniques
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Dimensionnement d'un réseau cellulaire IoT en utilisant des techniques de géométrie stochastique et d'apprentissage automatique
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