Towards Statistically Strong Source Anonymity for Sensor Networks

By Yi Yang, Min Shao, Sencun Zhu, Guohong Cao. IEEE INFOCOM 2008 - The 27th Conference on Computer Communications, 2008

298 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications

View Paper: https://www.semanticscholar.org/paper/520dd5f96de5a0ff1bd4380291a68a633e5109d5

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Isabel Wagner
2. David Eckhoff
3. Bhavani M. Thuraisingham

In Computer Networks and Communications

1. Isabel Wagner
2. Sajal K. Das
3. David Eckhoff
4. Bhavani M. Thuraisingham

Citations in the corpus

• Technical Privacy Metrics (2015, background): “ed in Section Metric Original Domain Reference 5.8.1 Confidence interval width Databases [7] 5.8.2 (t,δ)privacy violation Databases [76] 5.8.3 Statistically strong event unobservability Communication [126] 5.8.4 Size of uncertainty region Location [31] 5.8.5 Accuracy of obfuscated region Location [1”
• Privacy preservation in wireless sensor networks: A state-of-the-art survey (2009, methodology): “In the following, we discuss four existing techniques, flooding [18], Random walk [18,28], dummy injection [18,24,29], and fake data sources [21], against the disclosure of the location of data source in WSNs.”