Efficient Cryptographic-Based Technique for Privacy Preservation in Industries Practising Big Data

Industries such as healthcare and energy practicing big data analytic as it have driven the industry productivity. However, this occasion leads to data security and privacy concerns of the data captured and analyze since it contains many confidentiality sensitive and privacy-sensitive data. Security breaches of electronic medical data can risk patient privacy and violate the Health Insurance Portability and Accountability Act (HIPPA). The information collected by smart meters such as residential occupancy and social activities, can be extracted without a priori knowledge of household activities. The leakage of detailed information about household activities, rise to serious privacy concerns. Therefore a privacy preservation technique is required to ensure the user's privacy is preserved. Current work focus on cryptographic-based privacy preserving technique as this technique has the highest accuracy in data mining while at the same time preserve the privacy of data. However, this technique lacking in term of efficiency with regards to large data set. This paper attempts to address this issue by studying various cryptographic-based privacy preserving techniques in big data environment. Small/medium-size and large-size dataset from two identified industries, which are energy and healthcare are used as input for the algorithm of the proposed technique to be implemented using MATLAB. The efficiency of the proposed technique will be validated by comparing it with an existing cryptographic privacy-preserving techniques based on efficiency parameters which are computational cost and communication cost. The aim of this study is to propose an efficient cryptographic-based technique for privacy preservation for big data environment. It is expected that the finding of the research can help the identified industries in processing the vast amount of data efficiently and at the same time to preserve data privacy.