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Mobile Applications Fingerprinting using Locality-Sensitive Hashing
Saleh, Samer (2025) Mobile Applications Fingerprinting using Locality-Sensitive Hashing.
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| Abstract: | With the rapid growth in the number of mobile applications, monitoring their activity within a network has become increasingly challenging due to the substantial volume of traffic generated. Mobile application fingerprinting has emerged as a practical solution for identifying application behaviour through network traces, even when traffic is encrypted. This paper introduces an efficient approach using MinHash and Locality-Sensitive Hashing (LSH) to identify mobile application behaviours by comparing only traces with high similarity, which significantly reduces computational overhead while maintaining high accuracy and supporting the detection of previously unseen applications. We evaluated the proposed method through two experiments: application recognition and unseen application detection. In these experiments, we achieved an average accuracy of 83% on the ReCon dataset, while reducing comparison complexity from O(n^2) to O(n log n). |
| Item Type: | Essay (Bachelor) |
| Faculty: | EEMCS: Electrical Engineering, Mathematics and Computer Science |
| Subject: | 50 technical science in general |
| Programme: | Computer Science BSc (56964) |
| Link to this item: | https://purl.utwente.nl/essays/107385 |
| Export this item as: | BibTeX EndNote HTML Citation Reference Manager |
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