[目的/意义] 与确定泄露的情境相比，个人数据以一定概率泄露的情境更为普遍。由此计量泄露概率情境下的用户个人隐私价值，提出隐私计量的新视角，计量结果对隐私分级保护也具有实际意义。[方法/过程] 基于多级价格表的方法，计量用户的金融风险回报率；基于用户的金融风险回报率，改造多级价格表的实现机制，引导用户在无隐私泄露概率方案和存在隐私泄露概率的方案中做出决策，测度用户在一定泄露概率情境下对其个人数据的价值认知。[结果/结论] 在泄露概率为30%的情境下，用户对其社交网络中的个人数据隐私价值认知约为89.5元；同时，在泄露概率为100%的情境下以接受意愿和支付意愿体现的个人数据隐私价值分别为124.1和93.8元。表明用户在泄露概率情境下对其个人数据隐私价值的认知取决于个人数据隐私价值本身和用户对泄露概率风险容忍度两个方面。
[Purpose/significance] Compared with the situation in which the probability of personal data leakage is 100 percent, the situation in which personal data is leaked with a certain probability is more common. Thus, this paper aims to measure users' personal data privacy value under the certain probability of privacy leakage, which puts forward a new perspective of privacy measurement and the measurement results are of practical significance to privacy classification protection.[Method/process] Based on the multiple price list, the user's return on financial risk is measured. Modified the implementation mechanism of multiple price list to elicit users' decisions between the risk-free scheme and the scheme with the probability of privacy leakage. Based on the above steps, value of privacy under leakage probability of users can be measured.[Result/conclusion] When the probability of privacy leakage is 30%, users' average VPLP in the social networks is about RMB 89.5; at the same time, when the probability of privacy leakage is 100%, users' average "willing to accept" and "willing to pay" of personal data in the social networks is about RMB 124.1 and RMB 93.8. Users' VPLP depends on the value of personal privacy itself and probability of privacy leakage.
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