Improving the utility of locally differentially private protocols for longitudinal and multidimensional frequency estimates  

作　　者：Héber H.Arcolezi Jean-François Couchot Bechara Al Bouna Xiaokui Xiao 

机构地区：[1]Inria andÉcole Polytechnique(IPP),Palaiseau,France [2]Femto-ST Institute,Univ.Bourg.Franche-Comté,UBFC,CNRS,Belfort,France [3]TICKET Lab.,Antonine University Hadat-Baabda,Baabda,Lebanon [4]School of Computing,National University of Singapore,Singapore,Singapore

出　　处：《Digital Communications and Networks》2024年第2期369-379,共11页数字通信与网络（英文版）

基　　金：supported by the Agence Nationale de la Recherche(ANR)(contract“ANR-17-EURE-0002”);by the Region of Bourgogne Franche-ComtéCADRAN Project;supported by the European Research Council(ERC)project HYPATIA under the European Union's Horizon 2020 research and innovation programme.Grant agreement n.835294。

摘　　要：This paper investigates the problem of collecting multidimensional data throughout time(i.e.,longitudinal studies)for the fundamental task of frequency estimation under Local Differential Privacy(LDP)guarantees.Contrary to frequency estimation of a single attribute,the multidimensional aspect demands particular attention to the privacy budget.Besides,when collecting user statistics longitudinally,privacy progressively degrades.Indeed,the“multiple”settings in combination(i.e.,many attributes and several collections throughout time)impose several challenges,for which this paper proposes the first solution for frequency estimates under LDP.To tackle these issues,we extend the analysis of three state-of-the-art LDP protocols(Generalized Randomized Response–GRR,Optimized Unary Encoding–OUE,and Symmetric Unary Encoding–SUE)for both longitudinal and multidimensional data collections.While the known literature uses OUE and SUE for two rounds of sanitization(a.k.a.memoization),i.e.,L-OUE and L-SUE,respectively,we analytically and experimentally show that starting with OUE and then with SUE provides higher data utility(i.e.,L-OSUE).Also,for attributes with small domain sizes,we propose Longitudinal GRR(L-GRR),which provides higher utility than the other protocols based on unary encoding.Last,we also propose a new solution named Adaptive LDP for LOngitudinal and Multidimensional FREquency Estimates(ALLOMFREE),which randomly samples a single attribute to be sent with the whole privacy budget and adaptively selects the optimal protocol,i.e.,either L-GRR or L-OSUE.As shown in the results,ALLOMFREE consistently and considerably outperforms the state-of-the-art L-SUE and L-OUE protocols in the quality of the frequency estimates.

关 键 词：Local differential privacy Discrete distribution estimation Frequency estimation Multidimensional data Longitudinal studies 

分 类 号：TP309[自动化与计算机技术—计算机系统结构]