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Morton Filter-Based Security Mechanism for Healthcare System in Cloud Computing.

Sugandh Bhatia1, Jyoteesh Malhotra2

  • 1Department of Computer Science, Faculty of Engineering and Technology, Guru Nanak Dev University, Amritsar 143005, India.

Healthcare (Basel, Switzerland)
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Summary

This study introduces a novel cloud security mechanism for electronic health records, enhancing data protection using Morton filters and watermarking techniques. The new approach significantly improves security and data throughput in cloud-based healthcare systems.

Keywords:
COVID-19E-health recordsMorton filtercloud computingdigital artifacts

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Area of Science:

  • Computer Science
  • Information Security
  • Healthcare Informatics

Background:

  • Electronic health records (EHRs) contain sensitive patient data, making their security and privacy in cloud-based systems a critical challenge.
  • Existing security measures often utilize probabilistic data structures like cuckoo and bloom filters but overlook throughput considerations.
  • Previous approaches have limitations in effectively securing sensitive EHR data against unauthorized access and breaches.

Purpose of the Study:

  • To develop and evaluate a novel cloud security mechanism for enhancing the protection of electronic health records.
  • To address the shortcomings of existing security methods in cloud-based healthcare systems, particularly concerning data throughput.
  • To improve the overall security and privacy of patient data stored in cloud environments.

Main Methods:

  • Implementation of a new security mechanism incorporating fragile watermarking, least significant bit replacement watermarking, class reliability factor, and Morton filters.
  • Utilizing Morton filters, an approximate set membership data structure (ASMDS), known for improved performance over traditional filters.
  • Conducting simulation experiments on Hadoop version 0.20.3 under Red Hat Enterprise Linux 6 to evaluate the mechanism's effectiveness.

Main Results:

  • The proposed security mechanism demonstrated significant improvements in security and data handling capabilities.
  • Morton filters showed enhanced throughputs for insertions (0.9× to 15.5×), deletions (1.3× to 1.6×), and lookups (1.3× to 2.5×) compared to cuckoo filters.
  • Experimental results confirmed the mechanism's effectiveness for secure data storage in cloud-based healthcare systems with a load factor of 0.9.

Conclusions:

  • The novel cloud security mechanism provides an effective solution for securing sensitive electronic health records in cloud environments.
  • The integration of Morton filters significantly boosts data operation throughputs, addressing a key limitation of prior methods.
  • The research validates the proposed approach as a robust method for enhancing data security and privacy in healthcare cloud systems.