High variability geographical obfuscation for location privacy

Wightman, Pedro M.; Zurbarán, Mayra; Santander, Alcides

doi:10.1109/ccst.2013.6922079

Cited by 12 publications

(7 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The Pinwheel method was designed for applications that constantly keep track and update the users' location to a service provider (Wightman, Zurbaran, & Santander, 2014; Wightman et al., 2013; Zurbarán, Ávila, Wightman, & Fernández, 2014; Zurbarán, González, Wightman Rojas, & Labrador, 2014) and is a modified randomization method. In the Pinwheel method, the obfuscated point is a random point or either the farthest or the middle point among N random points in a pinwheel shape with center the original point P and radius r (Figure 1e).…”

Section: Existing Methods and Related Workmentioning

confidence: 99%

A comparison of obfuscation methods used for privacy protection: Exploring the challenges of polygon data in agricultural research

Nowbakht

O’Sullivan

Cawkwell

et al. 2022

Transactions in GIS

View full text Add to dashboard Cite

A major challenge of sharing spatially explicit agricultural and agri‐environmental data is to identify the trade‐off between field parcel confidentiality and spatial pattern preservation. In this work, 27 point‐based obfuscation and evaluation methods were applied on agricultural data, collected by the Irish Nutrient Management Planning Online (NMP Online) platform, which is a high‐density polygon dataset developed to inform precision agriculture through nutrient management based on soil fertility and agronomic targets. Broad categorizations of methods—including N*Rand, Donut, Density, Pinwheel, AHilb, and k‐anonymity—were developed, combined, and modified to achieve the best trade‐off between security and accuracy. To improve geoprivacy and spatial pattern preservation of existing Donut and Density methods, qualitative approaches, including Donut‐k and Density‐k methods, were introduced which identify the optimal values of radii based on a combination of the Donut method and k‐anonymity satisfaction, and subsequently optimal k‐anonymity determination. Modified AHilb and Donut‐AHilb methods were also developed to generate smaller and arbitrary obfuscation areas to improve location security. The Donut‐AHilb method was found to be the best at spatial pattern preservation and satisfying larger k‐anonymity, but the risk of false identification and non‐unique obfuscation was high when considering the polygon nature of agricultural data such as field parcels. Further, we introduce the term “non‐unique obfuscated points,” which is important when obfuscating static objects as two or more points might have the same obfuscated location, which has relevance to the wider GIScience community.

show abstract

Section: Existing Methods and Related Workmentioning

confidence: 99%

A comparison of obfuscation methods used for privacy protection: Exploring the challenges of polygon data in agricultural research

Nowbakht

O’Sullivan

Cawkwell

et al. 2022

Transactions in GIS

View full text Add to dashboard Cite

show abstract

“…Where φ is a parameter that will define the degrees wide of the pinwheel like distribution of the resulting points. A small value of φ will result more and thinner wings, a high value will result in less wider wings; therefore this determines the periodicity of the distribution of the output obfuscated location as shown in with high asymmetry of noise proved to be more efficient against filtering attacks, this is possible by adjusting values of φ according to [4]; therefore offering more geoprivacy with the same maximum radius of noise than a normal distribution. In order to decrease the probability that an obfuscated location falls too far from its original location, an extra step was taken for the pinwheel implementation in this paper.…”

Section: B Pinwheelmentioning

confidence: 99%

“…These algorithms disturb the original location but still provide distorted geographical coordinates as an obfuscated result as seen in Table 1. In particular, algorithms to include in this evaluation are: Donut Masking from [3], Pinwheel from [4], NRand-K from [5], VoKA: Voronoi K-Aggregation from [6], and a mechanism that induces noise by clustering based on VoKA from [7]; the framework will contain different analysis and metrics that will be computed with the datasets in their original form and obfuscated with the different mechanisms. The evaluations will aid in identifying what kind of perturbations are more suitable to preserve geographic properties and in general the framework will be replicable for any kind of LPPM based on noise or masking.…”

Section: Introductionmentioning

confidence: 99%

An Evaluation Framework for Assessing the Impact of Location Privacy on Geospatial Analysis

et al. 2020

View full text Add to dashboard Cite

The need for addressing geoprivacy in location based services has increased the offer of mechanisms that protect location information, however, these algorithms are not always developed to ensure the usability of the data and therefore, their adoption is not wide. In this work, a framework is presented to evaluate the effects of geoprivacy mechanisms on the quality of geodata to provide insights into how the data is affected for geospatial analysis. For this purpose, a toolkit of indices was developed to evaluate different characteristics of the data before and after a geoprivacy mechanism is implemented, providing a criterion to select one of them. The indices measure the changes in the presence of clusters through the quantification of hotspots in hotspot analysis and the difference observed in heatmaps of the concentration of the geodata. Variations in global indices like the Nearest Neighbor Index (NNI) and the orientation of the standard deviational ellipse are also measured. For demonstration, the data of crime arrests in New York was used for the month of January in 2017 and 2018. Five mechanisms were tested with different settings, resulting with the NRand-K algorithm producing fewer alterations to the reference data, preserving its initial characteristics better than the other mechanisms.

show abstract

“…We make our custom PostGIS functions available as open-source software [29]. The pinwheel technique was originally designed because other point obfuscation methods could be reversed by methods designed to filter uniform noise; the randomness of the pinwheel has been shown to maintain high variability, making it less susceptible to privacy attack [25]. Our geographically constrained pinwheel algorithm leverages the same concept as the original pinwheel algorithm and improves its research utility by adding constraint checking that controls how the new obfuscated point is selected.…”

Section: Overviewmentioning

confidence: 99%

Geospatial Imprecision With Constraints for Precision Public Health: Algorithm Development and Validation

Harris,

Delcher

2024

Online J Public Health Inform

View full text Add to dashboard Cite

Background Location and environmental social determinants of health are increasingly important factors in both an individual’s health and the monitoring of community-level public health issues. Objective We aimed to measure the extent to which location obfuscation techniques, designed to protect an individual’s privacy, can unintentionally shift geographical coordinates into neighborhoods with significantly different socioeconomic demographics, which limits the precision of findings for public health stakeholders. Methods Point obfuscation techniques intentionally blur geographic coordinates to conceal the original location. The pinwheel obfuscation method is an existing technique in which a point is moved along a pinwheel-like path given a randomly chosen angle and a maximum radius; we evaluate the impact of this technique using 2 data sets by comparing the demographics of the original point and the resulting shifted point by cross-referencing data from the United States Census Bureau. Results Using poverty measures showed that points from regions of low poverty may be shifted to regions of high poverty; similarly, points in regions with high poverty may be shifted into regions of low poverty. We varied the maximum allowable obfuscation radius; the mean difference in poverty rate before and after obfuscation ranged from 6.5% to 11.7%. Additionally, obfuscation inadvertently caused false hot spots for deaths by suicide in Cook County, Illinois. Conclusions Privacy concerns require patient locations to be imprecise to protect against risk of identification; precision public health requires accuracy. We propose a modified obfuscation technique that is constrained to generate a new point within a specified census-designated region to preserve both privacy and analytical accuracy by avoiding demographic shifts.

show abstract

High variability geographical obfuscation for location privacy

Cited by 12 publications

References 12 publications

A comparison of obfuscation methods used for privacy protection: Exploring the challenges of polygon data in agricultural research

A comparison of obfuscation methods used for privacy protection: Exploring the challenges of polygon data in agricultural research

An Evaluation Framework for Assessing the Impact of Location Privacy on Geospatial Analysis

Geospatial Imprecision With Constraints for Precision Public Health: Algorithm Development and Validation

Contact Info

Product

Resources

About