Download Report IEEE DataPort : Flow-Level Encrypted Instant Messaging Application (IMA) Traffic Dataset for Multiclass Classification - 2025

CSV by Ritwick Mondal
Information
Format: CSV Publisher: IEEE DataPort Publication Date of the Electronic Edition: 12/21/2025
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ISBN: 10.21227/ngk9-8g46
Description
This dataset provides a curated collection of encrypted network traffic designed to support research on Instant Messaging Application (IMA) traffic analysis. Due to privacy and ethical constraints, publicly available datasets containing labelled IMA traffic remain scarce. To address this limitation, the dataset is constructed from raw packet capture (PCAP) files collected in a controlled experimental environment and includes traffic generated by six widely used IMAs—WhatsApp, Discord, Signal, Facebook Messenger, Microsoft Teams, and Telegram—alongside non-IMA traffic such as web browsing, YouTube streaming, Gmail usage, and background system activity. In total, ten PCAP files are included, comprising both IMA and non-IMA traffic sources.The raw PCAP files were processed using Tranalyzer2 to extract flow-level representations suitable for encrypted traffic analysis. Feature extraction was configured to capture a comprehensive range of flow characteristics, including statistical, temporal, transport-layer, TLS-related, entropy-based, and packet distribution attributes. Each PCAP was processed independently, and the resulting flow records were exported into structured CSV files. A total of 202 flow-level features were extracted per flow instance.Following feature extraction, categorical labels were appended to each flow record to identify the originating application. The labelled flow records from all PCAP files were then merged into a unified dataset supporting multiclass traffic analysis. By providing flow-level features derived directly from raw encrypted traffic, this dataset enables reproducible experimentation and facilitates further research in encrypted network traffic characterization and analysis.
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