ACHIEVING k-ANONYMITY PRIVACY PROTECTION USING GENERALIZATION AND SUPPRESSION

2002 ◽  
Vol 10 (05) ◽  
pp. 571-588 ◽  
Author(s):  
LATANYA SWEENEY
Keyword(s):  
Real World ◽  
Privacy Protection ◽  
External Information ◽  
The Real ◽  
External Data ◽  
A Value ◽  
Minimal Distortion ◽  
Formal Presentation

Often a data holder, such as a hospital or bank, needs to share person-specific records in such a way that the identities of the individuals who are the subjects of the data cannot be determined. One way to achieve this is to have the released records adhere to k-anonymity, which means each released record has at least (k-1) other records in the release whose values are indistinct over those fields that appear in external data. So, k-anonymity provides privacy protection by guaranteeing that each released record will relate to at least k individuals even if the records are directly linked to external information. This paper provides a formal presentation of combining generalization and suppression to achieve k-anonymity. Generalization involves replacing (or recoding) a value with a less specific but semantically consistent value. Suppression involves not releasing a value at all. The Preferred Minimal Generalization Algorithm (MinGen), which is a theoretical algorithm presented herein, combines these techniques to provide k-anonymity protection with minimal distortion. The real-world algorithms Datafly and μ-Argus are compared to MinGen. Both Datafly and μ-Argus use heuristics to make approximations, and so, they do not always yield optimal results. It is shown that Datafly can over distort data and μ-Argus can additionally fail to provide adequate protection.

The Deluge

Mirror Worlds ◽  
1991 ◽  
Author(s):  
David Gelernter
Keyword(s):  
Data Processing ◽  
Real World ◽  
Data Gathering ◽  
Middle Region ◽  
Raw Data ◽  
The Real ◽  
External Data ◽  
The World ◽  
Initial Question ◽  
The Subject

we’ve installed the foundation piles and are ready to start building Mirror worlds. In this chapter we discuss (so to speak) the basement, in the next chapter we get to the attic, and the chapter after that fills in the middle region and glues the whole thing together. The basement we are about to describe is filled with lots of a certain kind of ensemble program. This kind of program, called a Trellis, makes the connection between external data and internal mirror-reality. The Trellis is, accordingly, a key player in the Mirror world cast. It’s also a good example of ensemble programming in general, and, I’ll argue, a highly significant gadget in itself. The hulking problem with which the Trellis does battle on the Mirror world’s behalf is a problem that the real world, too, will be confronting directly and in person very soon. Floods of data are pounding down all around us in torrents. How will we cope? what will we do with all this stuff? when the encroaching electronification of the world pushes the downpour rate higher by a thousand or a million times or more, what will we do then? Concretely: I’m talking about realtime data processing. The subject in this chapter is fresh data straight from the sensor. we’d like to analyze this fresh data in “realtime”—to achieve some understanding of data values as they emerge. Raw data pours into a Mirror world and gets refined by a data distillery in the basement. The processed, refined, one-hundredpercent pure stuff gets stored upstairs in the attic, where it ferments slowly into history. (In the next chapter we move upstairs.) Trellis programs are the topic here: how they are put together, how they work. But there’s an initial question that’s too important to ignore. we need to take a brief trip outside into the deluge, to establish what this stuff is and where it’s coming from. Data-gathering instruments are generally electronic. They are sensors in the field, dedicated to the non-stop, automatic gathering of measurements; or they are full-blown infomachines, waiting for people to sit down, log on and enter data by hand.

A Survey of Managing the Evolution of Data Warehouses

2010 ◽  
pp. 894-928 ◽  
Author(s):  
Robert Wrembel
Keyword(s):  
Data Warehouse ◽  
Real World ◽  
Data Sources ◽  
Index Structures ◽  
Data Warehouses ◽  
The Real ◽  
External Data ◽  
Structure Changes

Methods of designing a data warehouse (DW) usually assume that its structure is static. In practice, however, a DW structure changes among others as the result of the evolution of external data sources and changes of the real world represented in a DW. The most advanced research approaches to this problem are based on temporal extensions and versioning techniques. This article surveys challenges in designing, building, and managing data warehouses whose structure and content evolve in time. The survey is based on the so-called Multiversion Data Warehouse (MVDW). In details, this article presents the following issues: the concept of the MVDW, a language for querying the MVDW, a framework for detecting changes in data sources, a structure for sharing data in the MVDW, index structures for indexing data in the MVDW.

Privacy Disclosure in the Real World

2022 ◽  
Vol 16 (1) ◽  
pp. 0-0
Keyword(s):  
Network Security ◽  
Real World ◽  
Privacy Protection ◽  
Information Disclosure ◽  
The Real ◽  
Public Figures ◽  
Measurement Algorithm ◽  
Privacy Measurement

Privacy protection is a hot topic in network security, many scholars are committed to evaluating privacy information disclosure by quantifying privacy, thereby protecting privacy and preventing telecommunications fraud. However, in the process of quantitative privacy, few people consider the reasoning relationship between privacy information, which leads to the underestimation of privacy disclosure and privacy disclosure caused by malicious reasoning. This paper completes an experiment on privacy information disclosure in the real world based on WordNet ontology .According to a privacy measurement algorithm, this experiment calculates the privacy disclosure of public figures in different fields, and conducts horizontal and vertical analysis to obtain different privacy disclosure characteristics. The experiment not only shows the situation of privacy disclosure, but also gives suggestions and method to reduce privacy disclosure.

scholarly journals Realistic Mathematics Education (RME) untuk Meningkatkan Kemampuan Pemecahan Masalah Matematis Siswa di Indonesia

Jurnal Elemen ◽  
2021 ◽  
Vol 7 (2) ◽  
pp. 450-462
Author(s):  
I Wayan Widana ◽  
Keyword(s):  
Problem Solving ◽  
Real World ◽  
Effect Size ◽  
Mathematical Problem ◽  
Learning Model ◽  
Medium Effect ◽  
Control Group ◽  
Control Group Design ◽  
The Real ◽  
A Value

Problem-solving ability in the real world is the main competency that students must possess in the 21st century. RME can bridge abstract mathematical concepts obtained in the classroom with the real world. This research is a meta-analytic study aimed at analyzing the effect of the RME learning model on problem-solving abilities. The data was obtained from a search of scientific articles that have been published in Science and Technology Index (SINTA) 2, 3, and 4 accredited journals and national proceedings in the period 2016-2021 and is an experimental study with a non-equivalent pre-test and post-test control group design. The research samples that matched the exclusion and inclusion criteria were seven units. The data were analyzed using the JASP V-0.11 application. The results of the heterogeneity test with a value of Q=10.277 and p=0.113>0.05. The combined effect size model used is the fixed effect model. The results showed that the average effect size was 0.42 in the medium effect category. The Funnel Plot and Egger's Test tests with a value of z=0.075 and p=0.940>0.05 indicated no publication bias. In conclusion, the RME learning model affects students' mathematical problem-solving abilities with moderate influence. The results of this study contribute to strengthening the findings of previous studies.

k-ANONYMITY: A MODEL FOR PROTECTING PRIVACY

2002 ◽  
Vol 10 (05) ◽  
pp. 557-570 ◽  
Author(s):  
LATANYA SWEENEY
Keyword(s):  
Real World ◽  
Privacy Protection ◽  
Structured Data ◽  
World Systems ◽  
The Real ◽  
Specific Field ◽  
Private Data ◽  
Privately Held

Consider a data holder, such as a hospital or a bank, that has a privately held collection of person-specific, field structured data. Suppose the data holder wants to share a version of the data with researchers. How can a data holder release a version of its private data with scientific guarantees that the individuals who are the subjects of the data cannot be re-identified while the data remain practically useful? The solution provided in this paper includes a formal protection model named k-anonymity and a set of accompanying policies for deployment. A release provides k-anonymity protection if the information for each person contained in the release cannot be distinguished from at least k-1 individuals whose information also appears in the release. This paper also examines re-identification attacks that can be realized on releases that adhere to k-anonymity unless accompanying policies are respected. The k-anonymity protection model is important because it forms the basis on which the real-world systems known as Datafly, μ-Argus and k-Similar provide guarantees of privacy protection.

Current Issues: Evidence-Based Practice for the Real World: Thoughts on Clinical Education in Communication Disorders

2010 ◽  
Vol 20 (3) ◽  
pp. 100-105 ◽  
Author(s):  
Anne K. Bothe
Keyword(s):  
Clinical Education ◽  
Real World ◽  
Evidence Based Practice ◽  
Communication Disorders ◽  
University Faculty ◽  
Evidence Based ◽  
Speech Language Pathology ◽  
Basic Principles ◽  
The Real ◽  
Language Pathology

This article presents some streamlined and intentionally oversimplified ideas about educating future communication disorders professionals to use some of the most basic principles of evidence-based practice. Working from a popular five-step approach, modifications are suggested that may make the ideas more accessible, and therefore more useful, for university faculty, other supervisors, and future professionals in speech-language pathology, audiology, and related fields.

The Real-World Fellowship

2006 ◽  
Vol 40 (7) ◽  
pp. 47
Author(s):  
LEE SAVIO BEERS
Keyword(s):  
Real World ◽  
The Real
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