micro: Reviewed ON-OFF privacy

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Manos Katsomallos 2021-09-02 18:24:16 +03:00
parent 0650b710b5
commit 1ff242fb53
3 changed files with 59 additions and 1 deletions

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@ -82,7 +82,11 @@
\cite{ye2017trajectory} & (sequential) & & & & & & \\ \hdashline
\hyperlink{cao2017quantifying}{\textbf{Cao et al.}} & finite/ & streaming & global & user/ & dependence & perturbation & differential \\
\cite{cao2017quantifying,cao2018quantifying} & infinite & & & ($w$-)event & (temporal) & (Laplace) & privacy \\
\cite{cao2017quantifying,cao2018quantifying} & infinite & & & ($w$-)event & (temporal) & (Laplace) & privacy \\ \hdashline
\hyperlink{naim2019off}{\emph{ON-OFF privacy}} & infinite & streaming & local & event & dependence & randomization & - \\
\cite{naim2019off, ye2019preserving} & & & & & (serial) & & \\
\cite{ye2020off, ye2021off} & & & & & & & \\
\bottomrule

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@ -1674,6 +1674,41 @@
publisher = {Springer}
}
@inproceedings{naim2019off,
title={ON-OFF privacy with correlated requests},
author={Naim, Carolina and Ye, Fangwei and El Rouayheb, Salim},
booktitle={2019 IEEE International Symposium on Information Theory (ISIT)},
pages={817--821},
year={2019},
organization={IEEE}
}
@inproceedings{ye2019preserving,
title={Preserving ON-OFF privacy for past and future requests},
author={Ye, Fangwei and Naim, Carolina and El Rouayheb, Salim},
booktitle={2019 IEEE Information Theory Workshop (ITW)},
pages={1--5},
year={2019},
organization={IEEE}
}
@article{ye2020off,
title={ON-OFF Privacy in the Presence of Correlation},
author={Ye, Fangwei and Naim, Carolina and Rouayheb, Salim El},
journal={arXiv preprint arXiv:2004.04186},
year={2020}
}
@article{ye2021off,
title={ON-OFF Privacy Against Correlation Over Time},
author={Ye, Fangwei and Naim, Carolina and El Rouayheb, Salim},
journal={IEEE Transactions on Information Forensics and Security},
volume={16},
pages={2104--2117},
year={2021},
publisher={IEEE}
}
@article{warner1965randomized,
title = {Randomized response: A survey technique for eliminating evasive answer bias},
author = {Warner, Stanley L},

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@ -416,3 +416,22 @@ According to the technique's intuition, stronger correlations result in higher p
However, the loss is smaller when the dimension of the transition matrix, which is extracted according to the modeling of the correlations (here it is Markov chain), is larger due to the fact that larger transition matrices tend to be uniform, resulting in weaker data dependence.
The authors investigate briefly all of the possible privacy levels; however, the solutions that they propose are suitable only for the event-level.
Last but not least, the technique requires the calculation of the temporal privacy loss for every individual within the data set which might prove computationally inefficient in real-time scenarios.
% ON-OFF privacy with correlated requests
% Preserving ON-OFF Privacy for Past and Future Requests
% ON-OFF Privacy in the Presence of Correlation
% ON-OFF Privacy Against Correlation Over Time
% - microdata
% - infinite
% - streaming
% - dependence
% - event
% - ON-OFF privacy
% - randomization
% - serial (Markov chain with N states)
\hypertarget{naim2019off}{Naim et al.}~\cite{naim2019off, ye2019preserving, ye2020off, ye2021off} proposed the notion of \emph{ON-OFF privacy} according to which, users require privacy protection only at certain timestamps over time.
They investigate the privacy risk due to the correlation between a user's requests when toggling the privacy protection ON and OFF.
The goal is to minimize the information throughput and always answer users' requests while protecting their requests to online services when privacy is set to ON.
They model the dependence between requests using a Markov chain, which is publicly known, where each state represents an available service.
Setting privacy to ON, the user obfuscates their original query by randomly sending requests to (and receiving answers from) a subset of all of the available services.
Although this randomization step makes the original query indistinguishable while making sure that the users always get the information that they need, there is no clear quantification of the privacy guarantee that the scheme offers over time.