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Securing DICOM images based on adaptive pixel thresholding approach

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conference contribution
posted on 2020-04-20, 13:04 authored by Qamar Natsheh, Ana SalageanAna Salagean, Eran Edirisinghe
This paper presents a novel efficient two-region Selective encryption approach that exploits medical images statistical properties to adaptively segment Digital Imaging and Communications in Medicine (DICOM) images into regions using thresholding technique in the spatial domain. This approach uses adaptive pixel thresholding, in which thresholds for same DICOM modality, anatomy part and pixel intensities' range were extracted off-line. Then, the extracted thresholds were objectively and subjectively evaluated to select the most accurate threshold for the correspondent pixel intensities' range. In the on-line stage, DICOM images were segmented into a Region Of Interest (ROI) and a Region Of Background (ROB) based on their pixels intensities using the adopted thresholds. After that, ROI was encrypted using Advanced Encryption Standard (AES), while ROB was encrypted using XXTEA. The main goal of the proposed approach is to reduce the encryption processing time overhead in comparison with the Naïve approach; where all image pixels are encrypted using AES. The proposed approach aims to achieve a trade-off between processing time and a high level of security. The encryption time of the proposed approach can save up to 60% of the Naïve encryption time for DICOM images with small-medium ROI.

History

School

  • Science

Department

  • Computer Science

Published in

2018 IEEE 31st International Symposium on Computer-Based Medical Systems (CBMS)

Pages

280 - 285

Source

31st IEEE International Symposium on Computer-Based Medical Systems (CBMS)

Publisher

IEEE

Version

  • AM (Accepted Manuscript)

Rights holder

© IEEE

Publisher statement

© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Publication date

2018-07-23

Copyright date

2018

ISBN

9781538660607

eISSN

2372-9198

Language

  • en

Location

Karlstad, Sweden

Event dates

18th June 2018 - 21st June 2018

Depositor

Dr Ana Salagean. Deposit date: 11 April 2020

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