IDEAS home Printed from https://ideas.repec.org/a/gam/jftint/v14y2022i2p55-d748291.html
   My bibliography  Save this article

Securing IoT Devices against Differential-Linear (DL) Attack Used on Serpent Algorithm

Author

Listed:
  • Khumbelo Muthavhine

    (Department of Electrical and Mining Engineering, University of South Africa, Roodepoort, Johannesburg 1709, South Africa)

  • Mbuyu Sumbwanyambe

    (Department of Electrical and Mining Engineering, University of South Africa, Roodepoort, Johannesburg 1709, South Africa)

Abstract

Cryptographic algorithms installed on Internet of Things (IoT) devices suffer many attacks. Some of these attacks include the differential linear attack (DL). The DL attack depends on the computation of the probability of differential-linear characteristics, which yields a Differential-Linear Connectivity Table ( DLCT ). The DLCT is a probability table that provides an attacker many possibilities of guessing the cryptographic keys of any algorithm such as Serpent. In essence, the attacker firstly constructs a DLCT by using building blocks such as Substitution Boxes (S-Boxes) found in many algorithms’ architectures. In depth, this study focuses on securing IoT devices against DL attacks used on Serpent algorithms by using three magic numbers mapped on a newly developed mathematical function called Blocker, which will be added on Serpent’s infrastructure before being installed in IoT devices. The new S-Boxes with 32-bit output were generated to replace the original Serpent’s S-Boxes with 4-bit output. The new S-Boxes were also inserted in Serpent’s architecture. This novel approach of using magic numbers and the Blocker Function worked successfully in this study. The results demonstrated an algorithm for which its S-Box is composed of a 4-bit-output that is more vulnerable to being attacked than an algorithm in which its S-Box comprises 32-bit outputs. The novel approach of using a Blocker, developed by three magic numbers and 32-bits output S-Boxes, successfully blocked the construction of DLCT and DL attacks. This approach managed to secure the Serpent algorithm installed on IoT devices against DL attacks.

Suggested Citation

  • Khumbelo Muthavhine & Mbuyu Sumbwanyambe, 2022. "Securing IoT Devices against Differential-Linear (DL) Attack Used on Serpent Algorithm," Future Internet, MDPI, vol. 14(2), pages 1-32, February.
  • Handle: RePEc:gam:jftint:v:14:y:2022:i:2:p:55-:d:748291
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1999-5903/14/2/55/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1999-5903/14/2/55/
    Download Restriction: no
    ---><---

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jftint:v:14:y:2022:i:2:p:55-:d:748291. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.