Dataset Generation for ML Personal Tracker Detection

State: Open
Published: 2023-06-04

This work focuses on the collection of BLE packets through passive sniffing to generate a large dataset which can be analyzed through ML approaches. The aim of this work is to collect a large enough dataset through sniffing to see if there are any patterns in the data that could identify specific BLE devices, such as AirTags. 

This work includes:

Helpful Sources:
  • https://petsymposium.org/2020/files/papers/issue1/popets-2020-0003.pdf
  • https://arxiv.org/pdf/1904.10600.pdf
  • https://ieeexplore.ieee.org/abstract/document/8638232
  • https://ieeexplore.ieee.org/document/8795319
  • https://arxiv.org/pdf/2211.01963.pdf
  • https://scholar.afit.edu/cgi/viewcontent.cgi?article=6008&context=etd
40% Design, 40% Implementation, 20% Documentation

Supervisors: Katharina O. E. Müller

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