Principled Data Access: Building Public-private Data Partnerships for Better Official Statistics

2021 ◽  
Author(s):  
Claudia Biancotti ◽  
Oscar Borgogno ◽  
Giovanni Furio Veronese
Cryptography ◽  
2021 ◽  
Vol 5 (1) ◽  
pp. 2
Author(s):  
Tushar Kanti Saha ◽  
Takeshi Koshiba

Conjunctive queries play a key role in retrieving data from a database. In a database, a query containing many conditions in its predicate, connected by an “and/&/∧” operator, is called a conjunctive query. Retrieving the outcome of a conjunctive query from thousands of records is a heavy computational task. Private data access to an outsourced database is required to keep the database secure from adversaries; thus, private conjunctive queries (PCQs) are indispensable. Cheon, Kim, and Kim (CKK) proposed a PCQ protocol using search-and-compute circuits in which they used somewhat homomorphic encryption (SwHE) for their protocol security. As their protocol is far from being able to be used practically, we propose a practical batch private conjunctive query (BPCQ) protocol by applying a batch technique for processing conjunctive queries over an outsourced database, in which both database and queries are encoded in binary format. As a main technique in our protocol, we develop a new data-packing method to pack many data into a single polynomial with the batch technique. We further enhance the performances of the binary-encoded BPCQ protocol by replacing the binary encoding with N-ary encoding. Finally, we compare the performance to assess the results obtained by the binary-encoded BPCQ protocol and the N-ary-encoded BPCQ protocol.


Author(s):  
Anja Bechmann ◽  
Peter Bjerregaard Vahlstrup

The aim of this article is to discuss methodological implications and challenges in different kinds of deep and big data studies of Facebook and Instagram through methods involving the use of Application Programming Interface (API) data. This article describes and discusses Digital Footprints (www.digitalfootprints.dk), a data extraction and analytics software that allows researchers to extract user data from Facebook and Instagram data sources; public streams as well as private data with user consent. Based on insights from the software design process and data driven studies the article argues for three main challenges: Data quality, data access and analysis, and legal and ethical considerations.


2019 ◽  
Vol 6 (Supplement_2) ◽  
pp. S606-S606
Author(s):  
Breanna R Campbell ◽  
Koeun Choi ◽  
Megan Gray ◽  
Chelsea Canan ◽  
Anthony Moll ◽  
...  

Abstract Background mHealth (mobile health) is a promising tool to deliver healthcare interventions to underserved populations. Across low- and middle-income countries (LMIC), the prevalence of smartphones has risen to 42%. Effective mHealth deployment in LMIC requires an understanding of how LMIC populations use mobile technology. We characterized the use of mobile devices in rural KwaZulu-Natal, South Africa to tailor mHealth interventions for people living with HIV and at risk for acquiring HIV. Methods We surveyed participants in community settings and offered free HIV counseling and testing. Participants self-reported their gender, age, relationship status, living distance from preferred clinic, receipt of monthly grant, condomless sex frequency, and circumcision status (if male). Outcomes included cell phone and smartphone ownership, private data access, health information seeking, and willingness to receive healthcare messages. We performed multivariable logistic regression to assess the relationship between demographic factors and outcomes. Results Among 788 individuals surveyed, the median age was 28 (IQR 22–40) years, 75% were male, and 86% owned personal cell phones, of which 43% were smartphones. The majority (59%) reported having condomless sex and most (59%) males reported being circumcised. Although only 10% used the phone to seek health information, 93% of cell phone owners were willing to receive healthcare messages. Being young, female, and in a relationship were associated with cell phone ownership. Smartphone owners were more likely to be young and female, less likely to live 10–30 minutes from preferred clinic, and less likely to receive a monthly grant. Those reporting condomless sex or lack of circumcision were significantly less likely to have private data access. Conclusion Most participants were willing to receive healthcare messages via phone, indicating that mHealth interventions may be feasible in rural KwaZulu-Natal. Smartphone-based mHealth interventions specifically geared to prevent or support the care of HIV in young women in KwaZulu-Natal may be feasible. mHealth interventions encouraging condom use and medical male circumcision should consider the use of non-smartphone SMS and be attuned to mobile data limitations. Disclosures All authors: No reported disclosures.


2021 ◽  
Vol 18 (11) ◽  
pp. 92-103
Author(s):  
Wei Liang ◽  
Songyou Xie ◽  
Jiahong Cai ◽  
Chong Wang ◽  
Yujie Hong ◽  
...  

2015 ◽  
Vol 2015 ◽  
pp. 1-17
Author(s):  
Shyamala Devi Munisamy ◽  
Arun Chokkalingam

Cloud computing has pioneered the emerging world by manifesting itself as a service through internet and facilitates third party infrastructure and applications. While customers have no visibility on how their data is stored on service provider’s premises, it offers greater benefits in lowering infrastructure costs and delivering more flexibility and simplicity in managing private data. The opportunity to use cloud services on pay-per-use basis provides comfort for private data owners in managing costs and data. With the pervasive usage of internet, the focus has now shifted towards effective data utilization on the cloud without compromising security concerns. In the pursuit of increasing data utilization on public cloud storage, the key is to make effective data access through several fuzzy searching techniques. In this paper, we have discussed the existing fuzzy searching techniques and focused on reducing the searching time on the cloud storage server for effective data utilization. Our proposedAsymmetric Classifier Multikeyword Fuzzy Searchmethod provides classifier search server that creates universal keyword classifier for the multiple keyword request which greatly reduces the searching time by learning the search path pattern for all the keywords in the fuzzy keyword set. The objective of using BTree fuzzy searchable index is to resolve typos and representation inconsistencies and also to facilitate effective data utilization.


2020 ◽  
Vol 36 (4) ◽  
pp. 943-954
Author(s):  
Isnaeni Noviyanti ◽  
Panca D. Prabawa ◽  
Dwi Puspita Sari ◽  
Ade Koswara ◽  
Titi Kanti Lestari ◽  
...  

Nowadays, the use of so-called big data as a new data source to complement official statistics has become an opportunity for organizations focusing on statistics. The use of big data can lead to a more efficient data collection. However, currently, there has not been any standard business process for big data collection and processing in BPS-Statistics Indonesia. Meanwhile, the adoption of technologies alone cannot determine the success of big data use. It is widely known that big data use can be challenging, since there are issues regarding data access, quality, and methodology, as well as the development of required skillsets. This paper proposes a framework for a business process that is specifically designed to support the use of big data for official statistics at BPS-Statistics Indonesia along with how existing technology will support it. The development of this framework is based on the wider Statistical Business Process Framework and Architecture (SBFA) developed by BPS-Statistics Indonesia to describe and manage its overall statistical business processes. The paper uses the example of the use of Mobile Positioning Data (MPD) as a big data source to delineate Metropolitan Areas in Indonesia as a way to explain the implementation of the framework.


2021 ◽  
pp. 263
Author(s):  
Gabriel Nicholas

Policymakers are faced with a vexing problem: how to increase competition in a tech sector dominated by a few giants. One answer proposed and adopted by regulators in the United States and abroad is to require large platforms to allow consumers to move their data from one platform to another, an approach known as data portability. Facebook, Google, Apple, and other major tech companies have enthusiastically supported data portability through their own technical and political initiatives. Today, data portability has taken hold as one of the go-to solutions to address the tech industry’s competition concerns. This Article argues that despite the regulatory and industry alliance around data portability, today’s public and private data portability efforts are unlikely to meaningfully improve competition. This is because current portability efforts focus solely on mitigating switching costs, ignoring other barriers to entry that may preclude new platforms from entering the market. The technical implementations of data portability encouraged by existing regulation—namely one-off exports and API interoperability—address switching costs but not the barriers of network effects, unique data access, and economies of scale. This Article proposes a new approach to better alleviate these other barriers called collective portability, which would allow groups of users to coordinate to transfer data they share to a new platform, all at once. Although not a panacea, collective portability would provide a meaningful alternative to existing approaches while avoiding both the privacy/competitive utility trade off of one-off exports and the hard-to regulate power dynamics of APIs.


Sensors ◽  
2020 ◽  
Vol 20 (17) ◽  
pp. 4681
Author(s):  
Xiaoshuai Zhang ◽  
Chao Liu ◽  
Kok Keong Chai ◽  
Stefan Poslad

Permissioned blockchains can be applied for sharing data among permitted users to authorise the data access requests in a permissioned blockchain. A consensus network constructed using pre-selected nodes should verify a data requester’s credentials to determine if he or she have the correct permissions to access the queried data. However, current studies do not consider how to protect users’ privacy for data authorisation if the pre-selected nodes become untrusted, e.g., the pre-selected nodes are manipulated by attackers. When a user’s credentials are exposed to pre-selected nodes in the consensus network during authorisation, the untrusted (or even malicious) pre-selected nodes may collect a user’s credentials and other private information without the user’s right to know. Therefore, the private data exposed to the consensus network should be tightly restricted. In this paper, we propose a challenge-response based authorisation scheme for permissioned blockchain networks named Challenge-Response Assisted Access Authorisation (CRA3) to protect users’ credentials during authorisation. In CRA3, the pre-selected nodes in the consensus network do not require users’ credentials to authorise data access requests to prevent privacy leakage when these nodes are compromised or manipulated by attackers. Furthermore, the computational burden on the consensus network for authorisation is reduced because the major computing work of the authorisation is executed by the data requester and provider in CRA3.


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