Differential privacy: its technological prescriptive using big data

Jain, Priyank; Gyanchandani, Manasi; Khare, Nilay

doi:10.1186/s40537-018-0124-9

Cited by 47 publications

(23 citation statements)

References 33 publications

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“…Through this study, authors focus on analysis of agriculture data and find optimal parameters to maximize crop production using data mining techniques and multiple linear programming. Jain et al (2018) throws light on the privacy of data aspect in this article. Since Big data has become a part and parcel of everyday life, privacy has become a topic requiring emphasis.…”

Section: Literature Reviewmentioning

confidence: 96%

An Empirical Study of Big Data Analytics in Rural Arena

2019

IJSSES

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Innovations in ICT sector facilitate qualitative life style for citizens in the globe. Countries that facilitate usage of new techniques in ICT, i.e. Big data analytics, find it easier to fulfil the needs of their citizens. Big data is characterized by its volume, variety, and speed. Analytics involves its processing in a cost effective way in order to draw conclusion for their useful application. Big data also involves the field of machine learning, artificial intelligence leading to accuracy in data presentation useful for public policy making. Hence using data analytics in public policy-making is a proper way to march towards all round development of any country. The data-driven insights can help the government to take important strategic decisions with regard to socioeconomic development of country. Developed nations like the UK and the USA are already far ahead on the path of digitization with the support of Big Data analytics. India is a huge country and it is currently on the path of massive digitization being realised through Digital India Mission. Internet connection per household is on the rise every year. This transforms into a massive data set that has the potential to improvise the public services delivery system into an effective service mechanism for Indian citizens. In fact, when compared to developed nations, this capacity is being underutilized in India. This is particularly true for administrative system in rural areas. The present paper focuses on the need of the adaptation for Big data analytics in Indian rural administration and its contribution towards development of the country on a faster pace. Results of the research focused on the need for increasing awareness and serious capacity building of the government personnel working for rural development with regard to Big data analytics and its utility for development of the country. Multiple public policies are framed and implemented for rural development yet, the results are not as effective as they should be. Big data has a major role to play in this context as it can assist in improving both policymaking and implementation, which aims at all round development of the country.

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Section: Literature Reviewmentioning

confidence: 96%

An Empirical Study of Big Data Analytics in Rural Arena

2019

IJSSES

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“…The data gathered from different environments is outsourced into the public database. The sharing of data in this way meets the security constraints since outsourcing sensitive data with personal information is not advisable in recent days due to the increased vulnerabilities and threats [14], [15]. Let D and D represent two neighboring datasets that are not similar since they differ by one dataset entry.…”

Section: Preliminary Knowledgementioning

confidence: 99%

On Differential Privacy-Based Framework for Enhancing User Data Privacy in Mobile Edge Computing Environment

et al. 2021

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The potential growth in data mining has an important aspect on security due to the consideration of the data as an asset. The provisioning of protection in a public infrastructure fails to ensure privacy disclosure of an individual's information. Differential Privacy (DP) is a promising solution for assuring privacy protection by injecting noise using the Laplace mechanism or Exponential mechanism. The access of data by analysts is performed via edge devices. A common problem identified from previous research work is the leakage of privacy at the edge layer and data accessed by unauthorized people. To address the problem, this paper proposes DP-FCNN, that implements Differential Privacy using a Fuzzy Convolution Neural Network (FCNN) with Laplace Mechanism for injecting noise. The processes handled here are data processing and query processing. The dataset is uploaded by the data owner to the data provider, who is responsible for injecting noise and then encrypting with Piccolo encryption before uploading it into the cloud. Based on the uploaded dataset, the data owner constructs a hash index from the extracted key attributes by using the BLAKE2s algorithm for performing hashing. The hash index is fed into the edge server to form a Merkle hash tree due to the data leakage at the edge is eliminated. On the other hand, requests/queries by the data analyst are authenticated by the data provider. The hash tree in the edge server then searches for the corresponding data, extracting it from the cloud and delivers it to the data analyst in an encrypted format. Every authenticated data analyst is provided with a decryption key for retrieving the query result. This is implemented using Java and the results show better efficiency in terms of scalability, processing time and accuracy.

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“…In this work, we focused on Laplace mechanism since the dataset we employed for evaluation is mainly numerical. The scale of the noise in the Laplace mechanism is dependent on the sensitivity function, divided by [20].…”

Section: A Laplace Mechanismmentioning

confidence: 99%

Management Plane for Differential Privacy Preservation Through Smart Contracts

Khan

Lahmadi

Kräussl

et al. 2020

2020 IEEE/ACS 17th International Conference on Computer Systems and Applications (AICCSA)

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Blockchain has emerged as a novel solution addressing a plethora of industrial issues in domains spanning from financial to educational. However, several challenges restrict the widespread adoption of the technology and data privacy, with throughput and scalability issues, ranks amongst the foremost. In this paper, we introduce a novel privacy management plane which integrates differential privacy to query existing relational databases through the blockchain as well as spearheads the use of blockchain for local differential privacy. The distinguishing feature in the latter is that the privacy management plane gives the data owners the right to perturb their data with the desired privacy budget, while in the former it gives the right to the data curator to change the privacy budget dynamically while answering queries through the blockchain. The paper also includes experimental evaluation of the developed privacy management plane and integrates management operations in it through another smart contract. The paper addresses the issue of GDPR and it's implications in the context of blockchain data, while highlighting the compliance of the proposed implementation.

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Differential privacy: its technological prescriptive using big data

Cited by 47 publications

References 33 publications

An Empirical Study of Big Data Analytics in Rural Arena

An Empirical Study of Big Data Analytics in Rural Arena

On Differential Privacy-Based Framework for Enhancing User Data Privacy in Mobile Edge Computing Environment

Management Plane for Differential Privacy Preservation Through Smart Contracts

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