4 research outputs found
Privacy-aware Data Trading
The growing threat of personal data breach in data trading pinpoints an
urgent need to develop countermeasures for preserving individual privacy. The
state-of-the-art work either endows the data collector with the responsibility
of data privacy or reports only a privacy-preserving version of the data. The
basic assumption of the former approach that the data collector is trustworthy
does not always hold true in reality, whereas the latter approach reduces the
value of data. In this paper, we investigate the privacy leakage issue from the
root source. Specifically, we take a fresh look to reverse the inferior
position of the data provider by making her dominate the game with the
collector to solve the dilemma in data trading. To that aim, we propose the
noisy-sequentially zero-determinant (NSZD) strategies by tailoring the
classical zero-determinant strategies, originally designed for the
simultaneous-move game, to adapt to the noisy sequential game. NSZD strategies
can empower the data provider to unilaterally set the expected payoff of the
data collector or enforce a positive relationship between her and the data
collector's expected payoffs. Both strategies can stimulate a rational data
collector to behave honestly, boosting a healthy data trading market. Numerical
simulations are used to examine the impacts of key parameters and the feasible
region where the data provider can be an NSZD player. Finally, we prove that
the data collector cannot employ NSZD to further dominate the data market for
deteriorating privacy leakage.Comment: 10 pages, 11 figure
Privacy-Aware Data Trading
The growing threat of personal data breach in data trading pinpoints an urgent need to develop countermeasures for preserving individual privacy. The state-of-the-art work either endows the data collector with the responsibility of data privacy or reports only a privacy-preserving version of the data. The basic assumption of the former approach that the data collector is trustworthy does not always hold true in reality, whereas the latter approach reduces the value of data. In this paper, we investigate the privacy leakage issue from the root source. Specifically, we take a fresh look to reverse the inferior position of the data provider by making her dominate the game with the collector to solve the dilemma in data trading. To that aim, we propose the noisy-sequentially zero-determinant (NSZD) strategies by tailoring the classical zero-determinant strategies, originally designed for the simultaneous-move game, to adapt to the noisy sequential game. NSZD strategies can empower the data provider to unilaterally set the expected payoff of the data collector or enforce a positive relationship between her and the data collector's expected payoffs. Both strategies can stimulate a rational data collector to behave honestly, boosting a healthy data trading market. Numerical simulations are used to examine the impacts of key parameters and the feasible region where the data provider can be an NSZD player. Finally, we prove that the data collector cannot employ NSZD to further dominate the data market for deteriorating privacy leakage
プライバシーを考慮したデータ取引に関する研究
京都大学新制・課程博士博士(情報学)甲第24933号情博第844号京都大学大学院情報学研究科社会情報学専攻(主査)教授 伊藤 孝行, 教授 鹿島 久嗣, 教授 岡部 寿男, 阿部 正幸(NTT社会情報研究所)学位規則第4条第1項該当Doctor of InformaticsKyoto UniversityDGA