Deakin IoT Traffic Dataset

This dataset comprises network traffic collected from 24 Internet of Things (IoT) devices over a span of 119 days, capturing a total of over 110 million packets. The devices represent 19 distinct types and were monitored in a controlled environment under normal operating conditions, reflecting a variety of functions and behaviors typical of consumer IoT products (<b>pcapIoT</b>). The packet capture (pcap) files preserve complete packet information across all protocol layers, including ARP, TCP, HTTP, and various application-layer protocols. Raw pcap files (<b>pcapFull</b>) are also provided, which contain traffic from 36 non-IoT devices present in the network. To facilitate device-specific analysis, a CSV file is included that maps each IoT device to its unique MAC address. This mapping simplifies the identification and filtering of packets belonging to each device within the pcap files. 3 extra CSV (<b>CSVs</b>) files provide metadate about the states that the devices were in at different times. Additionally, Python scripts (<b>Scripts</b>) are provided to assist in extracting and processing packets. These scripts include functionalities such as packet filtering based on MAC addresses and protocol-specific data extraction, serving as practical examples for data manipulation and analysis techniques. This dataset is valuable for researchers interested in network behavior analysis, anomaly detection, and the development of IoT-specific network policies. It enables the study and differentiation of network behaviors based on device functions and supports behavior-based profiling to identify irregular activities or potential security threats.

本数据集包含在119天观测周期内从24台物联网（Internet of Things, IoT）设备采集的网络流量，总计捕获超过1.1亿个数据包。本次采集涉及19种不同类型的设备，均在受控实验环境中于正常运行工况下完成监测，覆盖消费级物联网产品常见的各类功能与行为特征（<b>pcapIoT</b>）。数据包捕获（Packet Capture, pcap）文件保留了全协议层的完整数据包信息，涵盖地址解析协议（ARP）、传输控制协议（TCP）、超文本传输协议（HTTP）及各类应用层协议。同时提供原始pcap文件（<b>pcapFull</b>），其中包含网络中36台非物联网设备产生的流量数据。为便于开展设备级分析，数据集附带一份CSV映射文件，可将每台物联网设备与其唯一的媒体访问控制（Media Access Control, MAC）地址进行关联，该映射表可简化pcap文件中各设备对应数据包的识别与筛选流程。另有3份附加CSV（<b>CSVs</b>）文件，提供设备在不同时段的状态元数据。此外还附带Python脚本（<b>Scripts</b>），用于辅助数据包的提取与处理工作，这些脚本具备基于MAC地址的数据包筛选、协议专属数据提取等功能，可作为数据处理与分析技术的实操示范案例。本数据集对于关注网络行为分析、异常检测及物联网专用网络策略开发的研究人员而言极具应用价值，其支持基于设备功能开展网络行为的研究与区分，并可助力基于行为画像的异常活动识别或潜在安全威胁检测工作。