``Privacy, anonymity, big data in the social sciences,'' Commun. ACM, vol. 57, no. 9, pp. 56-63, Sep. 2014.Daries, J. P. et al. Privacy, anonymity, and big data in the social sciences. Communications of the ACM 57, 56-63 (2014)....
Initially, confidential data are id... DH Chen,JB Kerr,SA Owen - US 被引量: 59发表: 2001年 Securing Anonymous Communication Channels under the Selective DoS Attack Anonymous communication systems are subject to selective denial-of-service (DoS) attacks. Selective DoS attacks lower anonymity as ...
Enhancing data utility in differential privacy via microaggregation-based k-anonymity This is in contrast with k-anonymity mechanisms, which make no assumptions on the uses of anonymized data while focusing on preserving data utility from ... J Soria-Comas,J Domingo-Ferrer,David Sanchez,... - ...
and, particularly, when the data usage is ill-defined or not defined at all. Privacy models for this type of release are k-anonymity [16,17], privacy for re-identification [18,19], and local differential privacy [20,21]. There are three main families of masking methods. Perturbative ...
DarkFi DarkFi is a new Layer 1 blockchain, designed with anonymity at the forefront. It offers flexible private primitives that can be wielded to create any kind of application GitHub testnet, february 2023 No Manta Network On-Chain Privacy for Web 3, DeFi and more ✨️**ZK* GitHub te...
Generalization is an approach to perform input perturbation, which preserves privacy by generalizing non-sensitive data to less specific forms such that the data meet a certain privacy model, such as k-anonymity [14], l-diversity [5], t-closeness [15] and Anatomy [16]. However, generalized ...
data privacy 美 英 un.数据保密 网络保密性 英汉 网络释义 un. 1. 数据保密 例句 更多例句筛选
In this way; a high degree of energy saving is realized within the given limits of information loss. Our analysis shows that the proposed method achieves the desired privacy levels with low information loss and with considerable energy saving. 展开 关键词: Anonymity Wireless Sensor Networks Data ...
In this paper we make two contributions to facilitate effective and efficient CBCR and crime data mining as well as to address the user privacy concern. The first is a practical framework for mobile CBCR and the second, is a hybrid k-anonymity algorithm to guarantee privacy preservation of the...
Submitting the token as part of a separate follow-up study instead of the main study, allowed us to correctly identify students for the purpose of crediting points while at the same time preserving their anonymity in main survey. Section 5.4 discusses this aspect in more detail. The ...