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.