Encrypted Mobile Instant Messaging Traffic Dataset
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We collect encrypted traffic from six widely-used Instant Messaging Applications (IMAs) installed on an Android device for descriptive and statistical analysis. In particular, we collect traffic from: 1. Microsoft Teams, 2. Discord, 3. Facebook Messenger, 4. Signal, 5. Telegram, and 6. WhatsApp. The encrypted traffic collected from these applications are stored as individual `.pcap` file. For our research, we extract flows from these `.pcap` files using `tranalyzer` and build statistical models. Therefore, the flow dataset for each of the IMA are also contained with this dataset. Furthermore, we collect common encrypted mobile traffic that do not result from any IMA. We use such traffic to test if we can distinguish between IMA and non-IMA traffic. In particular, we collect traffic resulting from web-browsing, video streaming, and sending-emails. We also save any background traffic that does not correspond to any of these activities. These sets of encrypted traffic are also saved as `.pcap` files and their flow dataset are contained with this dataset. Lastly, we include the text conversations used to generate this dataset for any reproduction purposes.
本研究从部署于安卓(Android)设备上的六款主流即时通讯应用(Instant Messaging Applications,缩写IMAs)中采集加密流量,用于描述性与统计分析。具体而言,本次采集覆盖的应用包括:1. 微软(Microsoft)Teams,2. Discord,3. 脸书信使(Facebook Messenger),4. Signal,5. Telegram,6. WhatsApp。从上述应用采集到的加密流量将以独立的.pcap文件存储。本研究使用`tranalyzer`从上述.pcap文件中提取流量流,并构建统计模型,因此本数据集同时包含每一款IMAs对应的流量流数据集。此外,本研究还采集了非来自任何IMAs的通用加密移动流量,用于验证模型能否区分IMAs流量与非IMAs流量。具体而言,此类流量涵盖网页浏览、视频流媒体及电子邮件发送产生的流量,同时还留存了与上述活动均不相关的后台流量。此类加密流量集同样以.pcap文件格式存储,其对应的流量流数据集也包含在本数据集中。最后,为便于研究复现,本数据集还包含用于生成该流量集的文本对话数据。




