Vol. 3 No. 2 (2023): Journal of Millimeterwave Communication, Optimization and Modelling
Articles

Data Security Techniques and Comparison of Differential Privacy Techniques in Bioinformatics

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  • Nilgün İncereis,
  • Hilal Çakır,
  • Bekir Tevfik Akgün
Nilgün İncereis
Bartın University

Published 31.12.2023

Keywords

  • Bioinformatics,
  • data security,
  • data anonymization,
  • data masking,
  • data encryption,
  • role-based access control,
  • differential privacy
    • ...More
    Less

Copyright (c) 2023 Nilgün İncereis; Hilal Çakır, Bekir Tevfik Akgün (Co-Author)

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Abstract

Bioinformatics data is data containing information about biological systems and processes. This data can include genomic data, proteomic data, metabolic data, and similar data. The processing and analysis of bioinformatics data aims to achieve important goals such as conducting scientific research and improving healthcare systems. Data security of bioinformatics data ensures the security of data during processing and analysis as well as protecting individual privacy. In this study, five of the known techniques for data security in bioinformatics have been studied. These techniques include: data anonymization, data masking, data encryption, and role-based access control, and differential privacy. In this study, it is aimed to create functions for the above-mentioned data security techniques by using the dataset obtained from 1000 patients with lung cancer, and to anonymize the dataset by using Laplacian, Gaussian and Exponential mechanisms from differential privacy techniques. Looking at various comparison parameters from the differential privacy techniques, it is concluded that the Laplacian technique strikes the best balance between privacy and utility as it provides the highest privacy guarantee and accuracy, as well as the lowest noise and robustness.

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