Design and Analysis for Multiple Sensitive Values-Oriented Personalized Randomized Response
SONG Hai-na1,2, LUO Tao1,2, HAN Xin-yu1,2, LI Jian-feng1,2
1. Beijing Laboratory of Advanced Information Networks, Beijing University of Posts and Telecommunications, Beijing 100876, China;
2. Beijing Key Laboratory of Network System Architecture and Convergence, Beijing University of Posts and Telecommunications, Beijing 100876, China
Abstract：In actual dada collection,the sensitivity of different sensitive information is different so that the concrete privacy need is different,too.However,the existing local privacy preservation model based on randomized response (RR),which is called conventional randomized response (CRR) for convenience,focuses on a universal approach that exerts the same amount of preservation for all sensitivity values,without catering for their concrete privacy needs.As a result,it may be offering insufficient protection to a subset of people with relatively higher privacy needs,while applying excessive privacy control to another subset with relatively lower privacy needs.Based on this,a new framework which is called personalized randomized response (PRR) is proposed based on the concept of CRR for multiple sensitive values-oriented personalized privacy preservation.The PRR technique considers personalized privacy needs,introduces sensitive value weights for different sensitive values,and then introduces the weights into the decision of RR for satisfying all sensitivity values' privacy needs,and thus,attains personalized privacy preservation.Both theoretical derivation and simulation experiment reveal that the estimate error of statistics of PRR mechanism is smaller than that of the CRR mechanism for a certain subjective degree of privacy leakage,that is,the quality of statistics obtained by PRR mechanism is higher than that of the CRR model while guaranteeing personalized privacy protection for a given subjective degree privacy preservation.
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2019, Vol. 47 
