Forthcoming Articles

International Journal of Embedded Systems

International Journal of Embedded Systems (IJES)

Forthcoming articles have been peer-reviewed and accepted for publication but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.

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International Journal of Embedded Systems (2 papers in press)

Regular Issues

  • MILP-based difference probabilities of PRESENT and Keccak   Order a copy of this article
    by Guoyong Han, Hongluan Zhao, Yang Gao, Wanxuan Yan, Yixuan Wu, Jinxin Wu 
    Abstract: Mixed integer linear programming (MILP) model is one of the best tools to search differential trails for bit-oriented block ciphers. Based on this method, it is easy to evaluate block ciphers against differential attack. This paper focuses on the research to search for better distinguishers of block cipher PRESENT-80 and Keccak-f[400]. The 14/15/16-round differential distinguisher of PRESENT-80 with the probability of no less than 271/275/279 are obtained. A 17-round differential path (the start with two active S-boxes) with no less than 276 is shown. For Keccak-f[400], the 3/4/5-round differential characteristics with the probabilities of 2156/2284/2385 are presented. Better differential cryptanalysis results can be obtained based on the above superior distinguishers. This paper provides a reference to find better and more accurate differential paths to attack block ciphers, and presents a detailed calculation process of them. The limitation of this paper lies in the fact that the current distinguishers have not been used for specific cryptanalysis.
    Keywords: mixed integer linear programming; MILP; differential probabilities; PRESENT-80; Keccak-f[400].
    DOI: 10.1504/IJES.2025.10074128
     
  • Porting sequential haze removal using dark channel prior to hybrid OpenMP and CUDA   Order a copy of this article
    by Ling-Huey Li, Tien-Hsiung Weng, Mengyen Hsieh, Hung-Lung Tsai, Arcangelo Castiglione 
    Abstract: Image dehazing has been used in many applications such as underwater imaging, autonomous, aerial, and drone vehicles, as well as surveillance and security. While it is common today to use combinations of CPUs and GPUs in heterogeneous computing environments, we present in this work the development of a parallel hybrid approach using CUDA and OpenMP to enhance the efficiency of the Dark Channel Prior algorithm for haze removal. Implementation techniques and result discussions regarding program improvements may be used to support parallel developers. Preliminary studies, results, and experiments on hybrid CUDA and OpenMP have shown promising outcomes.
    Keywords: image dehaze; haze removal; dark channel prior algorithm; OpenMP; CUDA.
    DOI: 10.1504/IJES.2025.10074135
     

 

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