*.pcap
This dataset consists of network packet traces collected in 2023 on the 5G infrastructure deployed at Chalmers University of Technology.
The dataset includes 1,912 pcap files, distributed across 8 folders. Each pcap file captures 1 minute of encrypted network traffic generated by one of the following 8 popular mobile applications:
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DALHOUSIE NIMS LAB BENIGN DATASET 2024-2 dataset comprises data captured from Consumer IoT devices, depicting three primary real-life states (Power-up, Idle, and Active) experienced by everyday users. Our setup focuses on capturing realistic data through these states, providing a comprehensive understanding of Consumer IoT devices.
The dataset comprises of nine popular IoT devices namely
Amcrest Camera
Smarter Coffeemaker
Ring Doorbell
Amazon Echodot
Google Nestcam
Google Nestmini
Kasa Powerstrip
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This project aims to generate smart home IoT datasets (especially Zigbee traffic data) in order to support research on smart home IoT network and device profiling, behaviour modelling, characterization, and security analysis. The Zigbee traffic data is captured in a real house with two Zigbee networks containing over 25 Zigbee devices which monitor the daily activities inside the house. The captured Ethernet traffic data from Home Assistant also contains the status data of several non-Zigbee IoT devices such as printers, a smart thermostat, and entertainment devices.
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This dataset presents real-world IoT device traffic captured under a scenario termed "Active," reflecting typical usage patterns encountered by everyday users. Our methodology emphasizes the collection of authentic data, employing rigorous testing and system evaluations to ensure fidelity to real-world conditions while minimizing noise and irrelevant capture.
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This dataset results from a month-long cloud-based Internet Background Radiation observation conducted in May 2023.
A sensor fleet comprised of 26 EC2 compute instances was deployed within Amazon Web Services across their 26 commercially available regions, 1 sensor per region.
The dataset contains 21,856,713 incoming packets, out of which 17,008,753 are TCP datagrams, 3,076,855 are ICMP packets and the remainder, 1,770,418 are UDP messages.
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Electric power systems are comprised of cyber and physical components that are crucial to grid resiliency. Data from both components should be collected when modeling power systems: data from communication networks and intrusion detection systems; physical telemetry from sensors and field devices.
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Smart grid, an application of Internet of Things (IoT) is modern power grid that encompasses power and communication network from generation to utilization . Home Area Network (HAN), Field or Neighborhood Area Network (FAN/NAN) and Wide Area network (NAN) using Wireless LAN and Wireless/Wired WAN protocols are employed from generation to utilization . Advanced Metering Infrastructure, a utilization side infrastructure facilitates communication between smart meters and the server where energy efficient protocols are mandate to support smart grid .
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In this dataset, we provide detailed traffic stream data for the Spot robot, including both the Spot robot control traffic stream and the Spot video stream. The Spot robot traffic streams provide realistic traffic data for communication network evaluations, e.g., for measurements with the TSN FlexText testbed. Furthermore, we share data for the tactile internet including audio, video, and robotic communication. Finally, the dataset includes generic data streams for three different intervals (0.2ms, 0.3ms, and 0.5ms) with two different Ethernet frame sizes.
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Maximum capture length for interface 0: 65000
First timestamp: 1186262976.484933000
Last timestamp: 1186263276.484931000
Unknown encapsulation: 0
IPv4 bytes: 2768247216
IPv4 pkts: 45954067
IPv4 flows: 2860519
Unique IPv4 addresses: 7075
Unique IPv4 source addresses: 7065
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This dataset provides wireless measurements from two industrial testbeds: iV2V (industrial Vehicle-to-Vehicle) and iV2I+ (industrial Vehicular-to-Infrastructure plus sensor).
iV2V covers 10h of sidelink communication scenarios between 3 Automated Guided Vehicles (AGVs), while iV2I+ was conducted for around 16h at an industrial site where an autonomous cleaning robot is connected to a private cellular network.
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