Privacy Preserving Data Generation for Database Application Performance Testing

2004 ◽  
pp. 142-151 ◽  
Author(s):  
Yongge Wang ◽  
Xintao Wu ◽  
Yuliang Zheng
Keyword(s):  
Performance Testing ◽  
Privacy Preserving ◽  
Data Generation ◽  
Application Performance ◽  
Database Application

scholarly journals Veiklos auditas: veiklos tikrinimo ir vertinimo instrumentas

2011 ◽  
Vol 57 ◽  
pp. 26-38 ◽  
Author(s):  
Jonas Mackevičius ◽  
Dalia Daujotaitė
Keyword(s):  
Performance Testing ◽  
Decision Making Process ◽  
Audit Tool ◽  
Application Performance ◽  
New Developments ◽  
New Knowledge ◽  
The Status ◽  
Performance Audit ◽  
And Performance ◽  
Different Levels

Veiklos auditas yra viena iš labai svarbių audito sistemos rūšių, tačiau audito literatūroje daugelis jo aspektų išnagrinėti nepakankamai. Veiklos audito praktinio taikymo patirtis Lietuvoje taip pat maža. Straipsnyje nagrinėjama veiklos audito reikšmė ir sąvokos apibūdinimas įvairių užsienio ir Lietuvos autorių darbuose. Pasiūlytas veiklos audito apibrėžimas (įvertinus šiuolaikinės ekonomikos dinamiškumą ir sudėtingumą), atitinkantis šiandieninės globalios rinkos sąlygas. Ištirta veiklos audito vieta audito sistemoje. Išnagrinėtas veiklos audito procesas.Pagrindiniai žodžiai: veiklos auditas, tikrinimas ir vertinimas, audito sistema, veiklos audito procesas.Performance Audit: Tool of Performance Testing and EvaluationJonas Mackevičius, Dalia Daujotaitė SummaryThe phenomenon of the performance audit could be assessed as a response to new developments in economy and the new management and governance models stimulating to seek a further improvement in the governance and enhancement of the accountability and responsibility of different levels of government. The findings and results of the insights formulated within the research lead to the conclusion that performance audit is representative of the modern version of audit and constitutes a challenge to the conventional administration, imposing a requirement for new knowledge and its innovative application. Performance audit may be perceived as a source of a timely, reliable and objective information on the management and performance processes showing the status of management and shaping the decision-making process."> 

scholarly journals Differential Privacy at Risk: Bridging Randomness and Privacy Budget

2021 ◽  
Vol 2021 (1) ◽  
pp. 64-84
Author(s):  
Ashish Dandekar ◽  
Debabrota Basu ◽  
Stéphane Bressan
Keyword(s):  
At Risk ◽  
Differential Privacy ◽  
Cost Model ◽  
Privacy Preserving ◽  
Fine Tuning ◽  
Data Generation ◽  
The Cost ◽  
Privacy Budget ◽  
Composition Theorem ◽  
Privacy Level

AbstractThe calibration of noise for a privacy-preserving mechanism depends on the sensitivity of the query and the prescribed privacy level. A data steward must make the non-trivial choice of a privacy level that balances the requirements of users and the monetary constraints of the business entity.Firstly, we analyse roles of the sources of randomness, namely the explicit randomness induced by the noise distribution and the implicit randomness induced by the data-generation distribution, that are involved in the design of a privacy-preserving mechanism. The finer analysis enables us to provide stronger privacy guarantees with quantifiable risks. Thus, we propose privacy at risk that is a probabilistic calibration of privacy-preserving mechanisms. We provide a composition theorem that leverages privacy at risk. We instantiate the probabilistic calibration for the Laplace mechanism by providing analytical results.Secondly, we propose a cost model that bridges the gap between the privacy level and the compensation budget estimated by a GDPR compliant business entity. The convexity of the proposed cost model leads to a unique fine-tuning of privacy level that minimises the compensation budget. We show its effectiveness by illustrating a realistic scenario that avoids overestimation of the compensation budget by using privacy at risk for the Laplace mechanism. We quantitatively show that composition using the cost optimal privacy at risk provides stronger privacy guarantee than the classical advanced composition. Although the illustration is specific to the chosen cost model, it naturally extends to any convex cost model. We also provide realistic illustrations of how a data steward uses privacy at risk to balance the trade-off between utility and privacy.

Study and Improvement of a Web Application Load Testing Model

2013 ◽  
Vol 321-324 ◽  
pp. 2969-2973
Author(s):  
Hua Ji Zhu ◽  
Hua Rui Wu
Keyword(s):  
Web Application ◽  
Web Applications ◽  
User Behavior ◽  
Load Capacity ◽  
Performance Testing ◽  
Load Testing ◽  
Application Performance ◽  
Testing Model ◽  
User Groups ◽  
The Web

As an important indicator of Web application performance testing - load capacity is a key factor to judge the merits of the Web application performance, load testing model is an important premise to accurately obtain the Web applications load capacity; This article is based on the model of user groups, Through further analysis of the general user behavior , user groups model is been improved properly. The practical application shows that the improved model more realistically simulate real user behavior, and make the data more statistical significance, which can more accurately predict the performance of web applications. Keywords: Web applications, load capacity, performance testing, load testing, model

scholarly journals Privacy-Preserving Record Linkage: An international collaboration between Canada, Australia and Wales

2017 ◽  
Vol 1 (1) ◽  
Author(s):  
Conrad Pow ◽  
Karey Iron ◽  
James Boyd ◽  
Adrian Brown ◽  
Simon Thompson ◽  
...  
Keyword(s):  
International Collaboration ◽  
Record Linkage ◽  
Large Scale ◽  
Phase 1 ◽  
Performance Testing ◽  
Privacy Preserving ◽  
Data Repository ◽  
Hospital Inpatient ◽  
Experimental Conditions ◽  
Match Rate

ABSTRACT ObjectivesLinkage of “big data” can provide the answers to a variety of health questions that benefit the delivery of patient care, impact of policies, system planning and evaluation. In some jurisdictions, legal and operational barriers may prevent data linkage for research and system evaluation. Collaboration between international research institutions in Canada, Australia and Wales was formed at the Farr Institute International Conference in 2015. This partnership will test privacy-preserving record linkage (PPRL) techniques for linkage accuracy on real datasets held in a Canadian data repository. ApproachBloom filter PPRL techniques have been incorporated into a prototype linkage system. Evaluations on probabilistic linkage using Bloom filters method have shown potential for large-scale record linkage, performing both accurately and efficiently under experimental conditions. The prototype will be used to evaluate the Bloom filter PPRL techniques in 3 phases. Phase 1: 3 tests using simulated data relating to 20 million individuals will be matched to a sub-cohort of 1 million individuals. Phase 2: 100,000 people from hospital inpatient records will be matched to 18 million people in a health system registration file. These tests will inform whether the method can achieve high levels of privacy protection without negatively impacting performance and linkage quality. Performance indicators include match rate and processing efficiency based on record volumes. ResultsLinkage quality will be assessed by the number of true matches and non matches identified as links and non-links. This method will be evaluated using synthetic and real-world datasets, where the true match status is known. Initial performance testing linked a file of 3,000 records to 30,000 with a 100% match result. Subsequent test phases as above will continue to be evaluated and these results will be presented. ConclusionCompletion of the phased tests will confirm the ability to link datasets while preserving privacy. This international collaboration will expand the utility of this prototype linkage system and expand the global knowledge bank focusing on PPRL methods in general. It will also inform how to adapt to local requirements by providing a solution to many common legal and administrative challenges.

Privacy-Preserving Data Generation and Sharing Using Identification Sanitizer

2020 ◽  
pp. 185-200
Author(s):  
Shuo Wang ◽  
Lingjuan Lyu ◽  
Tianle Chen ◽  
Shangyu Chen ◽  
Surya Nepal ◽  
...  
Keyword(s):  
Privacy Preserving ◽  
Data Generation

scholarly journals Analisis Hasil Implementasi Pengembangan Aplikasi Mobile Pendekatan Hybrid Pada Aplikasi Family Tracking

2019 ◽  
Vol 3 (1) ◽  
pp. 17-22
Author(s):  
Miftachul Huda ◽  
Indah Lestari ◽  
Anggy Trisnadoli
Keyword(s):  
Mobile Application ◽  
Source Code ◽  
Hybrid Approach ◽  
Performance Testing ◽  
Average Difference ◽  
Application Performance ◽  
Gps Technology ◽  
Activity Schedule ◽  
And Function ◽  
Framework Development

Family Tracking is a mobile application that utilizes GPS technology to find out the location of each family member. There are several features such as the activity schedule, group chat, and the supervision area added by parents to the child's activity schedule. This application was developed with hybrid approach using Ionic 3 Framework development tools with support of Firebase backend. With the hybrid approach can produce multi-platform applications using the same source code. In this research the application was developed for the Android and iOS platforms. Based on functionality testing in accordance with ISO 9126-2 standards, that all features and functions contained in the application run well on both platforms. Then based on the application performance testing on each device that has the same benchmark value, the application can run stablen iOS devices but has the highest memory usage compared to Android devices with an average difference of 33.81mb. And then applications on iOS devices have lower CPU usage than Android devices, with differences in usage averaging 18.79%. Then based on the results of interviews to get user feedback, the results show that the application can running well and function as expected on Android and iOS devices.

scholarly journals Accelerating Genomic Data Generation and Facilitating Genomic Data Access Using Decentralization, Privacy-Preserving Technologies and Equitable Compensation

2018 ◽  
Vol 1 ◽  
pp. 1-23 ◽  
Author(s):  
Dennis Grishin ◽  
Kamal Obbad ◽  
Preston Estep ◽  
Kevin Quinn ◽  
Sarah Wait Zaranek ◽  
...  
Keyword(s):  
Genomic Data ◽  
Data Access ◽  
Privacy Preserving ◽  
Data Generation
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