Parallel Algorithm for the Chameleon Clustering Algorithm using Dynamic Modeling

Dashora, Rajnish; Bajaj, Harsh P.; Dube, Akshat; A, Geetha Mary.

doi:10.5120/13760-1600

Cited by 4 publications

(1 citation statement)

References 8 publications

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“…The origination of Big data on daily basis is increasing due to posts on social media like twitter and facebook, and digital pictures and videos on YouTube, mobile computing, file hosting and transactional records. There are four types of attributes in Big datasets [19].…”

Section: A Big Datasetmentioning

confidence: 99%

Clustering based Privacy Preserving of Big Data using Fuzzification and Anonymization Operation

Khan¹,

Iqbal²,

Faizullah³

et al. 2019

IJACSA

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Big Data is used by data miner for analysis purpose which may contain sensitive information. During the procedures it raises certain privacy challenges for researchers. The existing privacy preserving methods use different algorithms that results into limitation of data reconstruction while securing the sensitive data. This paper presents a clustering based privacy preservation probabilistic model of big data to secure sensitive information..model to attain minimum perturbation and maximum privacy. In our model, sensitive information is secured after identifying the sensitive data from data clusters to modify or generalize it.The resulting dataset is analysed to calculate the accuracy level of our model in terms of hidden data, lossed data as result of reconstruction. Extensive experiements are carried out in order to demonstrate the results of our proposed model. Clustering based Privacy preservation of individual data in big data with minimum perturbation and successful reconstruction highlights the significance of our model in addition to the use of standard performance evaluation measures.

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Section: A Big Datasetmentioning

confidence: 99%