Clustering has both the effect of making matching algorithms more vulnerable to errors, and the potential to dramatically reduce the number of seeds needed to ...

This result readily reveals the strong beneficial impact of clustering on network de- anonymization. Somehow surprisingly, the minimum seed set size.

Clustering has both the effect of making matching algorithms more vulnerable to errors, and the potential to dramatically reduce the number of seeds needed to ...

By analyzing the measurement on real datasets, we find that some data can potentially be de-anonymized accurately and the other can be de-anonymized in a coarse ...

Impact of Clustering on the Performance of Network De-anonymization. Authors: Chiasserini, Carla Fabiana; Garetto, Michele; Leonardi, Emilio ...

Bibliographic details on Impact of Clustering on the Performance of Network De-anonymization.

Nov 21, 2024 · It is shown that mapping address clusters to IP addresses has better performance than mapping Bitcoin addresses to IP addresses separately ...

To protect the privacy of users in online social networks, researchers have proposed various anonymous protection technologies, including k-anonymity [6] and ...

Oct 22, 2024 · In this paper, we present a comprehensive analysis of clustering-based anonymization mechanisms (CAMs) that have been recently proposed to preserve both ...

De-identification that moves points an average distance of 0.25 km lowers the spatial cluster detection sensitivity by less than 4% and lowers the detection ...