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Privstream: Differentially private event detection on data streams

Publication ,  Conference
Fanaeepour, M; Machanavajjhala, A
Published in: CODASPY 2019 - Proceedings of the 9th ACM Conference on Data and Application Security and Privacy
March 13, 2019

Event monitoring and detection in real-time systems is crucial. Protecting users’ data while reporting an event in almost real-time will increase the level of this challenge. In this work, we adopt the strong notion of differential privacy to private stream counting for event detection with the aim of minimizing false positive and false negative rates as our utility metrics.

Duke Scholars

Published In

CODASPY 2019 - Proceedings of the 9th ACM Conference on Data and Application Security and Privacy

DOI

Publication Date

March 13, 2019

Start / End Page

145 / 147
 

Citation

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Fanaeepour, M., & Machanavajjhala, A. (2019). Privstream: Differentially private event detection on data streams. In CODASPY 2019 - Proceedings of the 9th ACM Conference on Data and Application Security and Privacy (pp. 145–147). https://doi.org/10.1145/3292006.3302379
Fanaeepour, M., and A. Machanavajjhala. “Privstream: Differentially private event detection on data streams.” In CODASPY 2019 - Proceedings of the 9th ACM Conference on Data and Application Security and Privacy, 145–47, 2019. https://doi.org/10.1145/3292006.3302379.
Fanaeepour M, Machanavajjhala A. Privstream: Differentially private event detection on data streams. In: CODASPY 2019 - Proceedings of the 9th ACM Conference on Data and Application Security and Privacy. 2019. p. 145–7.
Fanaeepour, M., and A. Machanavajjhala. “Privstream: Differentially private event detection on data streams.” CODASPY 2019 - Proceedings of the 9th ACM Conference on Data and Application Security and Privacy, 2019, pp. 145–47. Scopus, doi:10.1145/3292006.3302379.
Fanaeepour M, Machanavajjhala A. Privstream: Differentially private event detection on data streams. CODASPY 2019 - Proceedings of the 9th ACM Conference on Data and Application Security and Privacy. 2019. p. 145–147.

Published In

CODASPY 2019 - Proceedings of the 9th ACM Conference on Data and Application Security and Privacy

DOI

Publication Date

March 13, 2019

Start / End Page

145 / 147