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De-anonymization

Known as: De-anonymisation, Deanonymisation, Deanonymization 
De-anonymization (also spelt as deanonymization) is a strategy in data mining in which anonymous data is cross-referenced with other sources of data… Expand
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Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2015
2015
We analyse the performance of several clustering algorithms in the digital peerto-peer currency Bitcoin. Clustering in Bitcoin… Expand
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Highly Cited
2015
Highly Cited
2015
In this paper, we analyze and systematize the state-of-the-art graph data privacy and utility techniques. Specifically, we… Expand
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Highly Cited
2014
Highly Cited
2014
We present a novel de-anonymization attack on mobility trace data and social data. First, we design an Unified Similarity (US… Expand
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Highly Cited
2014
Highly Cited
2014
In this paper, we study the quantification, practice, and implications of structural data (e.g., social data, mobility traces) De… Expand
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Highly Cited
2013
Highly Cited
2013
With the advent of GPS-equipped devices, a massive amount of location data is being collected, raising the issue of the privacy… Expand
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Highly Cited
2013
Highly Cited
2013
We perform a comprehensive measurement analysis of Silk Road, an anonymous, international online marketplace that operates as a… Expand
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Highly Cited
2011
Highly Cited
2011
This paper describes the winning entry to the IJCNN 2011 Social Network Challenge run by Kaggle.com. The goal of the contest was… Expand
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Highly Cited
2010
Highly Cited
2010
Social networking sites such as Facebook, LinkedIn, and Xing have been reporting exponential growth rates and have millions of… Expand
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Highly Cited
2009
Highly Cited
2009
Operators of online social networks are increasingly sharing potentially sensitive information about users and their… Expand
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Highly Cited
2008
Highly Cited
2008
We present a new class of statistical de- anonymization attacks against high-dimensional micro-data, such as individual… Expand
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