MIRAGE: Mobile-app Traffic Capture and Ground-truth Creation

Network traffic analysis, i.e. the umbrella of procedures for distilling information from network traffic, represents the enabler for highly-valuable profiling information, other than being the workhorse for several key network management tasks. While it is currently being revolutionized in its nature by the rising share of traffic generated by mobile and hand-held devices, existing design solutions are mainly evaluated on private traffic traces, and only a few public datasets are available, thus clearly limiting repeatability and further advances on the topic.To this end, we have designed and implemented MIRAGE, a reproducible architecture for mobile-app traffic capture and ground-truth creation. The outcome of this system is MIRAGE-2019, a human-generated dataset for mobile traffic analysis (with associated ground-truth) having the goal of advancing the state-of-the-art in mobile app traffic analysis.MIRAGE-2019 is expected to be capitalized by the networking community for different tasks related to mobile traffic analysis.

网络流量分析，即从网络流量中提取信息的各类流程的总称，既是多项关键网络管理任务的核心支撑手段，同时也是高价值画像信息的重要赋能基础。尽管当前移动与手持设备产生的流量占比持续攀升，正从本质上推动网络流量分析领域发生深刻变革，但现有设计方案大多仅基于私有流量轨迹开展评估，可用的公开数据集数量极少，这无疑限制了该领域研究的可复现性与进一步发展。为此，我们设计并实现了MIRAGE——一款面向移动应用流量采集与真实标签（ground-truth）生成的可复现架构。该系统的产出成果为MIRAGE-2019：一份人工构建的移动流量分析数据集（附带关联真实标签），其研发目标是推动移动应用流量分析领域的前沿研究水平提升。MIRAGE-2019有望为网络领域科研社区所利用，支撑其开展各类与移动流量分析相关的研究任务。

搜集汇总

背景与挑战

背景概述

MIRAGE-2019是一个人类生成的移动流量分析数据集，包含真实数据，旨在推动移动应用流量分析领域的发展。数据集涵盖了超过280名实验者使用40个移动应用在3种不同设备上产生的流量数据。