IDEAS home Printed from https://ideas.repec.org/a/sae/intdis/v18y2022i9p15501329221119398.html
   My bibliography  Save this article

Differential cryptanalysis of full-round ANU-II ultra-lightweight block cipher

Author

Listed:
  • Ting Fan
  • Lingchen Li
  • Yongzhuang Wei
  • Enes Pasalic

Abstract

Lightweight ciphers are often used as the underlying encryption algorithm in resource-constrained devices. Their cryptographic security is a mandatory goal for ensuring the security of data transmission. Differential cryptanalysis is one of the most fundamental methods applicable primarily to block ciphers, and the resistance against this type of cryptanalysis is a necessary design criterion. ANU-II is an ultra-lightweight block cipher proposed in 2017, whose design offers many advantages such as the use of fewer hardware resources (logic gates), low power consumption and fast encryption for Internet of Things devices. The designers of ANU-II claimed its resistance against differential cryptanalysis and postulated that the design is safe enough for Internet of Things devices. However, as addressed in this article, the security claims made by designers appear not to be well grounded. Using mixed-integer linear programming–like techniques, we identify one-round differential characteristic that holds with probability 1, which is then efficiently employed in mounting the key recovery attack on full-round ANU-II with only 2 2 chosen plaintexts and 2 62.4 full-round encryptions. The result shows that the designers’ security evaluation of ANU-II against differential cryptanalysis is incorrect and the design rationale is flawed. To remedy this weakness, we provide an improved variant of ANU-II, which has much better resistance to differential cryptanalysis without affecting the hardware and/or software implementation cost.

Suggested Citation

  • Ting Fan & Lingchen Li & Yongzhuang Wei & Enes Pasalic, 2022. "Differential cryptanalysis of full-round ANU-II ultra-lightweight block cipher," International Journal of Distributed Sensor Networks, , vol. 18(9), pages 15501329221, September.
  • Handle: RePEc:sae:intdis:v:18:y:2022:i:9:p:15501329221119398
    DOI: 10.1177/15501329221119398
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/15501329221119398
    Download Restriction: no

    File URL: https://libkey.io/10.1177/15501329221119398?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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:sae:intdis:v:18:y:2022:i:9:p:15501329221119398. 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: SAGE Publications (email available below). General contact details of provider: .

    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.