A Scalable Privacy Preserving System for Open Data

2016 ◽  
Author(s):  
Chao-Chun Yeh ◽  
Pang-Chieh Wang ◽  
Yu-Hsuan Pan ◽  
Ming-Chih Kao ◽  
Shih-Kun Huang
Keyword(s):  
Open Data ◽  
Privacy Preserving

An entropy-based analytic model for the privacy-preserving in open data

2016 ◽  
Author(s):  
Soo-Hyung Kim ◽  
Changwook Jung ◽  
Yoon-Joon Lee
Keyword(s):  
Open Data ◽  
Privacy Preserving ◽  
Analytic Model

Personalized privacy in open data sharing scenarios

2017 ◽  
Vol 41 (3) ◽  
pp. 298-310 ◽  
Author(s):  
David Sánchez ◽  
Alexandre Viejo
Keyword(s):  
Data Sharing ◽  
Privacy Protection ◽  
Open Data ◽  
Personal Data ◽  
Privacy Preserving ◽  
New Paradigm ◽  
Content Type ◽  
Privacy Threats ◽  
Individual Privacy ◽  
Whole Life Cycle

Purpose The purpose of this paper is to propose a privacy-preserving paradigm for open data sharing based on the following foundations: subjects have unique privacy requirements; personal data are usually published incrementally in different sources; and privacy has a time-dependent element. Design/methodology/approach This study first discusses the privacy threats related to open data sharing. Next, these threats are tackled by proposing a new privacy-preserving paradigm. The main challenges related to the enforcement of the paradigm are discussed, and some suitable solutions are identified. Findings Classic privacy-preserving mechanisms are ineffective against observers constantly monitoring and aggregating pieces of personal data released through the internet. Moreover, these methods do not consider individual privacy needs. Research limitations/implications This study characterizes the challenges to the tackled by a new paradigm and identifies some promising works, but further research proposing specific technical solutions is suggested. Practical implications This work provides a natural solution to dynamic and heterogeneous open data sharing scenarios that require user-controlled personalized privacy protection. Social implications There is an increasing social understanding of the privacy threats that the uncontrolled collection and exploitation of personal data may produce. The new paradigm allows subjects to be aware of the risks inherent to their data and to control their release. Originality/value Contrary to classic data protection mechanisms, the new proposal centers privacy protection on the individuals, and considers the privacy risks through the whole life cycle of the data release.

Public data and value creation in Italy.The findings from the Open Data 200 study

2018 ◽  
pp. 65-83
Author(s):  
Francesca De Chiara
Keyword(s):  
Value Creation ◽  
Open Data ◽  
Public Data

Promote Good Governance in Public Financial: The Practice of Local Budget (APBD) Transparency Through Open Data Jakarta in Jakarta Provincial Government

2019 ◽  
Vol 15 (1) ◽  
Author(s):  
Dodi Faedlulloh ◽  
Fetty Wiyani
Keyword(s):  
Public Finance ◽  
Good Governance ◽  
Open Data ◽  
Public Trust ◽  
Provincial Government ◽  
Financial Governance ◽  
One Stop ◽  
Data Portal ◽  
Data Transparency ◽  
Local Budget

This paper aimed to explain public financial governance based on good governance implementation in Jakarta Provincial Government. This paper specifically discussed towards transparancy implementation of local budget (APBD) through open data portal that publishes budget data to public. In general, financial transparency through open data has met Transparency 2.0 standards, namely the existence of encompassing, one-stop, one-click budget accountability and accessibility. But there are indeed some shortcomings that are still a concern in order to continue to maintain commitment to the principle of transparency, namely by updating data through consistent data visualization.Transparency of public finance needs to continue to be developed and improved through various innovations to maintain public trust in the government.Keywords: Public Finance, Open Data, Transparency

Privacy Preserving Public Auditing in Secured Cloud Storage

2012 ◽  
Vol 3 (3) ◽  
pp. 60-61
Author(s):  
V.Sajeev V.Sajeev ◽  
◽  
R.Gowthamani R.Gowthamani
Keyword(s):  
Cloud Storage ◽  
Privacy Preserving ◽  
Public Auditing

Adaptive Random Decision Tree: A New Approach for Data Mining with Privacy Preserving

2015 ◽  
Vol 03 (07) ◽  
pp. 6378-6384
Author(s):  
Hemlata B. Deorukhakar, Prof. Pradnya Kasture
Keyword(s):  
Data Mining ◽  
Decision Tree ◽  
Privacy Preserving ◽  
New Approach

Privacy-Preserving Fingerprint Authentication Resistant to Hill-Climbing Attacks

2018 ◽  
Vol E101.A (1) ◽  
pp. 138-148 ◽  
Author(s):  
Haruna HIGO ◽  
Toshiyuki ISSHIKI ◽  
Kengo MORI ◽  
Satoshi OBANA
Keyword(s):  
Privacy Preserving ◽  
Hill Climbing

A Survey of Auditing Techniques for Privacy Preserving and Ensure Data Correctness in the Cloud

2017 ◽  
Vol 7 (1) ◽  
pp. 181-185 ◽  
Author(s):  
S Durga Bhavani ◽  
◽  
Gudlanarva Sudhakar ◽  
Mohammad Almechal ◽  
◽  
...  
Keyword(s):  
Privacy Preserving
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