privacy
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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This repo contains the results and analysis data used in the experiment reported in the paper "Anycast and Third-party Libraries: A Recipe for a Privacy Disaster?" (under revision).
To this end, we conducted an experiment where we analyzed the personal data transfers of more than 5,500 Android apps, further identifying the libraries triggering the transfers and the destinations’ geolocation. The results show that 90% of third-party libraries and 98.65% of apps integrating them potentially fail to meet the requirements for international personal data transfers.
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The Transport-level pAcket RouTing ANalysis Tool for Cloud-native Applications (TARTAN) Dataset contains TARTAN/HiPerConTracer Traceroute runs between an endpoint in Oslo, Norway and the public Comprehensive TeX Archive Network (CTAN, https://www.ctan.org) and Comprehensive R Archive Network (CRAN, https://cran.r-project.org) mirror we
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Human activity recognition, which involves recognizing human activities from sensor data, has drawn a lot of interest from researchers and practitioners as a result of the advent of smart homes, smart cities, and smart systems. Existing studies on activity recognition mostly concentrate on coarse-grained activities like walking and jumping, while fine-grained activities like eating and drinking are understudied because it is more difficult to recognize fine-grained activities than coarse-grained ones.
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