CS 526: Lectures, Handouts & Homeworks
2016-11-26 · Big data is a term used for very large data sets that have more varied and complex structure. These characteristics usually correlate with additional difficulties in storing, analyzing and applying further procedures or extracting results. Big data analytics is the term used to describe the process of researching massive amounts of complex data in order to reveal hidden patterns or identify Geolocation with respect to personal privacy for the Background Collecting data on the localization of users is a key issue for the MASK (Mobile Airways Sentinel networK: the Allergy Diary) App. Data anonymization is a method of sanitization for privacy. The European Commission’s Article 29 Working Party stated that geolocation information is personal data. To assess geolocation using the MASK method and to compare two anonymization methods in Differentially private data cubes | Proceedings of the Preserving privacy in on-line analytical processing data cubes. In Secure Data Management in Decentralized Systems, pages 355--380. 2007. Google Scholar Cross Ref 差分隐私保护综述-机器学习文档类资源-CSDN下载
SemiSupervised Learning - Fudan University
In recent years, a new definition of privacy called k-anonymity has gained popularity. In a k-anonymized dataset, each record is indistinguishable from at least k-1 other records with respect to certain "identifying" attributes. In this paper we show using two simple attacks that a k-anonymized dataset has some subtle, but severe privacy problems. Privacy in Data Mining - Computer Science & E 2019-4-4 · A. Machanavajjhala, D. Kifer, J. Gehrke, and M. Venkitasubramaniam. `l-diversity: privacy beyond k-anonymity. ICDE, 2006. P. Samarati and L. Sweeney. Generalizing data to provide anonymity when disclosing information. In Proc. of the 17th ACM SIGMOD-SIGACT-SIGART Symposium on the Principles of Database Systems, 188, 1998
2010-1-24 · Problem Space • Pre-existing privacy measures k-anonymity and l-diversity have flaws. • k-anonymity-each equivalence class has at least k records to protect against identity disclosure. • k-anonymity is vulnerable to homogeneity attacks and background knowledge attacks. • l-diversity: distribution of a sensitive attribute in each equivalence class has at
2019-8-25 · Automated Web Patrol with Strider HoneyMonkeys: Finding Web Sites That Exploit Browser Vulnerabilities Authors: Yi-Min Wang, Doug Beck, Xuxian Jiang, Roussi Roussev, Chad Verbowski, Shuo Chen, and Sam King SemiSupervised Learning - Fudan University 2004-6-20 · l-diversity的典型实现 l-diversity的实现可以建立在Incognito的基础上 基于Incognito的算法框架来实现l-diversity 只需要将测试数据概化结果是否满足k-anonymity的地方, 替换为测试是否满足l-diversity 实验数据及实验环境 实验数据 Adult database Lands end (p+, a)-sensitive k-anonymity A new enhanced … 2011-3-22 · Several models such as p-sensitive k -anonymity [15], l-diversity [7], (α, k )-anonymity [19] and t-closeness [6] were proposed in the literature in order to deal with the problem of k anonymity. The work presented in this paper is highly inspired by [15]. L-Diversity: Privacy Beyond k-Anonymity