• Login
    View Item 
    •   Research Bank Home
    • Unitec Institute of Technology
    • Study Areas
    • Computing
    • Computing Journal Articles
    • View Item
    •   Research Bank Home
    • Unitec Institute of Technology
    • Study Areas
    • Computing
    • Computing Journal Articles
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Evaluating encryption algorithms for sensitive data using different storage devices

    Sarrafpour, Bahman; Alkorbi, Mohammed; Jamil, N.; Asif Naeem, M.; Mirza, F.

    Thumbnail
    Share
    View fulltext online
    Sarrafpour, B. (2020).pdf (1.164Mb)
    Date
    2020-05-20
    Citation:
    Sassani, B. A., Alkorbi, M., Jamil, N., Asif Naeem, M., & Mirza, F. (2020). Evaluating Encryption Algorithms for Sensitive Data Using Different Storage Devices. Scientific Programming, Volume 2020 |Article ID 6132312 | 9 pages, 9. doi:10.1155/2020/6132312
    Permanent link to Research Bank record:
    https://hdl.handle.net/10652/4942
    Abstract
    Sensitive data need to be protected from being stolen and read by unauthorized persons regardless of whether the data are stored in hard drives, flash memory, laptops, desktops, and other storage devices. In an enterprise environment where sensitive data is stored on storage devices, such as financial or military data, encryption is used in the storage device to ensure data confidentiality. Nowadays, the SSD-based NAND storage devices are favored over HDD and SSHD to store data because they offer increased performance and reduced access latency to the client. In this paper, the performance of different symmetric encryption algorithms is evaluated on HDD, SSHD, and SSD-based NAND MLC flash memory using two different storage encryption software. Based on the experiments we carried out, Advanced Encryption Standard (AES) algorithm on HDD outperforms Serpent and Twofish algorithms in terms of random read speed and write speed (both sequentially and randomly), whereas Twofish algorithm is slightly faster than AES in sequential reading on SSHD and SSD-based NAND MLC flash memory. By conducting full range of evaluative tests across HDD, SSHD, and SSD, our experimental results can give better idea for the storage consumers to determine which kind of storage device and encryption algorithm is suitable for their purposes. This will give them an opportunity to continuously achieve the best performance of the storage device and secure their sensitive data.
    Keywords:
    encryption algorithms, symmetric encryption algorithms, storage encryption software, Advanced Encryption Standard (AES) algorithm, storage devices
    ANZSRC Field of Research:
    080402 Data Encryption, 080303 Computer System Security
    Copyright Holder:
    Copyright © 2020 Bahman A. Sassani (Sarrafpour) et al

    Copyright Notice:
    This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
    Available Online at:
    https://www.hindawi.com/journals/sp/2020/6132312/
    Rights:
    This digital work is protected by copyright. It may be consulted by you, provided you comply with the provisions of the Act and the following conditions of use. These documents or images may be used for research or private study purposes. Whether they can be used for any other purpose depends upon the Copyright Notice above. You will recognise the author's and publishers rights and give due acknowledgement where appropriate.
    Metadata
    Show detailed record
    This item appears in
    • Computing Journal Articles [51]

    Te Pūkenga

    Research Bank is part of Te Pūkenga - New Zealand Institute of Skills and Technology

    • About Te Pūkenga
    • Privacy Notice

    Copyright ©2022 Te Pūkenga

    Usage

    Downloads, last 12 months
    44
     
     

    Usage Statistics

    For this itemFor the Research Bank

    Share

    About

    About Research BankContact us

    Help for authors  

    How to add research

    Register for updates  

    LoginRegister

    Browse Research Bank  

    EverywhereInstitutionsStudy AreaAuthorDateSubjectTitleType of researchSupervisorCollaboratorThis CollectionStudy AreaAuthorDateSubjectTitleType of researchSupervisorCollaborator

    Te Pūkenga

    Research Bank is part of Te Pūkenga - New Zealand Institute of Skills and Technology

    • About Te Pūkenga
    • Privacy Notice

    Copyright ©2022 Te Pūkenga