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Related Concept Videos

Statistical Analysis: Overview01:11

Statistical Analysis: Overview

When we take repeated measurements on the same or replicated samples, we will observe inconsistencies in the magnitude. These inconsistencies are called errors. To categorize and characterize these results and their errors, the researcher can use statistical analysis to determine the quality of the measurements and/or suitability of the methods.
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...
Multiple Comparison Tests01:13

Multiple Comparison Tests

Multiple comparison test, abbreviated as MCT, is a post hoc analysis generally performed after comparing multiple samples with one or more tests. An MCT will help identify a significantly different sample among multiple samples or a factor among multiple factors.
It would be easy to compare two samples using a significance alpha level of 0.05. In other words, there is only one sample pair to be compared. However, it would be difficult to identify a significantly different sample if the number...
Quantifying and Rejecting Outliers: The Grubbs Test01:02

Quantifying and Rejecting Outliers: The Grubbs Test

Sometimes, a data set can have a recorded numerical observation that greatly  deviates from the rest of the data. Assuming that the data is normally distributed, a statistical method called the Grubbs test can be used to determine whether the observation is truly an outlier.  To perform a two-tailed Grubbs test, first, calculate the absolute difference between the outlier and the mean. Then, calculate the ratio between this difference and the standard deviation of the sample. This number is...
Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
Wilcoxon Signed-Ranks Test for Matched Pairs01:09

Wilcoxon Signed-Ranks Test for Matched Pairs

The Wilcoxon signed-rank test for matched pairs evaluates the null hypothesis by combining the ranks of differences with their signs. It essentially tests whether the median of the differences in a population of matched pairs is zero. Since the test incorporates more information than the sign test, it generally yields more trustable conclusions. This test also does not require the data to follow a normal distribution, but two conditions must be met for it to be applicable: (1) the data must...
Routh-Hurwitz Criterion II01:19

Routh-Hurwitz Criterion II

In the application of the Routh-Hurwitz criterion, two specific scenarios can arise that complicate stability analysis.
The first scenario occurs when a singular zero appears in the first column of the Routh table. This situation creates a division by zero issues. To resolve this, a small positive or negative number, denoted as epsilon (∈), is substituted for the zero. The stability analysis proceeds by assuming a sign for ∈. If ∈ is positive, any sign change in the first column of the Routh...

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Related Experiment Videos

Quantifying the Correctness, Computational Complexity, and Security of Privacy-Preserving String Comparators for

Elizabeth Durham1, Yuan Xue, Murat Kantarcioglu

  • 1Department of Biomedical Informatics, Vanderbilt University, 2525 West End Avenue, Nashville, TN 37203, USA.

An International Journal on Information Fusion
|August 21, 2012
PubMed
Summary

Privacy-preserving record linkage (PPRL) uses specialized string comparators to match records without revealing sensitive data. Partitioning and encoding strings offers high accuracy but lower security compared to mapping methods.

Related Experiment Videos

Area of Science:

  • Computer Science
  • Data Science
  • Information Security

Background:

  • Record linkage integrates data from disparate sources, preventing duplication and enhancing analysis.
  • Privacy-preserving record linkage (PPRL) enables matching records without disclosing sensitive identifiers, crucial for healthcare and business.
  • Existing research lacks comprehensive comparisons of privacy-preserving string comparators (PPSCs) in real-world applications.

Purpose of the Study:

  • To conduct a principled and comprehensive evaluation of six PPSCs.
  • To assess PPSCs based on correctness, computational complexity, and security.
  • To analyze the trade-offs between these properties using a real-world dataset.

Main Methods:

  • Evaluation of six PPSCs on a publicly available dataset from the North Carolina voter registration database.
  • Analysis of record linkage prediction accuracy.
  • Assessment of computational complexity and security levels for each PPSC.

Main Results:

  • PPSCs that partition, encode, and compare strings demonstrated high accuracy in record linkage.
  • A trade-off was observed: these accurate methods exhibited lower security.
  • PPSCs mapping strings to a reduced dimensional space offered better security but potentially lower accuracy.

Conclusions:

  • The choice of PPSC involves balancing accuracy, computational cost, and security requirements.
  • Partitioning/encoding PPSCs are suitable when high accuracy is paramount and security trade-offs are acceptable.
  • Mapping-based PPSCs are preferable when enhanced security is a primary concern.