Abstract
We ask the question – how can websites and data aggregators continually release updated statistics, and meanwhile preserve each individual user’s privacy? Given a stream of 0’s and 1’s, we propose a differentially private continual counter that outputs at every time step the approximate number of 1’s seen thus far. Our counter construction has error that is only poly-log in the number of time steps. We can extend the basic counter construction to allow websites to continually give top-k and hot items suggestions while preserving users’ privacy.
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Hubert Chan, TH., Shi, E., Song, D. (2010). Private and Continual Release of Statistics. In: Abramsky, S., Gavoille, C., Kirchner, C., Meyer auf der Heide, F., Spirakis, P.G. (eds) Automata, Languages and Programming. ICALP 2010. Lecture Notes in Computer Science, vol 6199. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14162-1_34
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DOI: https://doi.org/10.1007/978-3-642-14162-1_34
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-14161-4
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