Secure Cloud based Privacy Preserving DataMinning Platform

Abstract

The adoption of cloud environment for various application uses has led to security and privacy concern of user’s data. To protect user data and privacy on such platform is an area of concern. Many cryptography strategy has been presented to provide secure sharing of resource on cloud platform. These methods tries to achieve a secure authentication strategy to realize feature such as self-blindable access tickets, group signatures, anonymous access tickets, minimal disclosure of tickets and revocation but each one varies in realization of these features. Each feature requires different cryptography mechanism for realization. Due to this it induces computation complexity which affects the deployment of these models in practical application. Most of these techniques are designed for a particular application environment and adopt public key cryptography which incurs high cost due to computation complexity. To address these issues this work present an secure and efficient privacy preserving of mining data on public cloud platform by adopting party and key based authentication strategy. The proposed SCPPDM (Secure Cloud Privacy Preserving Data Mining) is deployed on Microsoft azure cloud platform. Experiment is conducted to evaluate computation complexity. The outcome shows the proposed model achieves significant performance interm of computation overhead and cost.

Data mining privacy preserving: Research agenda

“…Besides techniques, seven PPDM methods were identified: Probabilistic Neural Network, Apriori algorithm, K-anonymity, SMC, Oblivious transfer, Noise addition, and Randomization. The additional contribution of this article lies in the discovery and upgrade of Shah and Gulati (2016) classification of methods and techniques by adding data swapping (Gupta & Joshi, 2009;Herman & Custers, 2004;Mendes & Vilela, 2017;Patel & Swati, 2015), semi-honest parties (Lindell & Pinkas, 2000;Rajesh et al, 2016), and also Secure Cloud Computing based PPDM (Kumaraswamy & Venugopal, 2017). The extracted data in the process of data extraction prove that there is no generic solution when it comes to privacy preserving and security in the data mining process.…”

“…All of the methods and techniques can be used to support privacy and security issues that the user can encounter using one of the cloud computing platforms. Kumaraswamy and Venugopal (2017) 4.5 | Future research…”

Big Data Security Architecture using Split and Merge Method

“…This key is common for a given file input, but varies for different file inputs. It must be maintained in a special registry and communicated securely to a legitimate user of the information [1] [2].The XOR operation results in two output sets namely, α and β. These are then saved in different physical locations within the target file system.…”

“…Big data refers to the management and analysis of huge amounts of data that exceeds the capability and efficiency of traditional data in every dimension. Big data collects and analyses large amounts of data from heterogeneous sources to discover unprecedented new knowledge and understanding of scientific and business scenarios [1] [2]. Aiming to gain greater insight into patterns not generally discernible from smaller data sets, big data business intelligence enables visibility into associations and trends that otherwise go unnoticed.…”