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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Indonesian Journal of Electrical Engineering and Computer Science
El Kafi, Jamal
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Computer Science & IT Engineering

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Enhance big data security based on HDFS using the hybrid approach Zine-Dine, Fayçal; Alcabnani, Sara; Azouaoui, Ahmed; El Kafi, Jamal
Indonesian Journal of Electrical Engineering and Computer Science Vol 38, No 2: May 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v38.i2.pp1256-1264

Abstract

Hadoop has emerged as a prominent open-source framework for the storage, management, and processing of extensive big data through its distributed file system, known as Hadoop distributed file system (HDFS). This widespread adoption can be attributed to its capacity to provide reliable, scalable, and cost-effective solutions for managing large datasets across diverse sectors, including finance, healthcare, and social media. Nevertheless, as the significance and scale of big data applications continue to expand, the challenge of ensuring the security and safeguarding of sensitive data within Hadoop has become increasingly critical. In this study, the authors introduce a novel strategy aimed at bolstering data security within the Hadoop storage framework. This approach specifically employs a hybrid encryption technique that leverages the advantages of both advanced encryption standard (AES) and data encryption standard (DES) algorithms, whereby files are encrypted in HDFS and subsequently decrypted during the map task. To assess the efficacy of this method, the authors performed experiments with various file sizes, benchmarking the outcomes against other established security measures.
Dual simulated annealing soft decoder for linear block codes Alaoui, Hicham Tahiri; Azouaoui, Ahmed; El Kafi, Jamal
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 4: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i4.pp2776-2787

Abstract

This paper proposes a new approach to soft decoding for linear block codes called dual simulated annealing soft decoder (DSASD) which utilizes the dual code instead of the original code, using the simulated annealing algorithm as presented in a previously developed work. The DSASD algorithm demonstrates superior decoding performance across a wide range of codes, outperforming classical simulated annealing and several other tested decoders. We conduct a comprehensive evaluation of the proposed algorithm's performance, optimizing its parameters to achieve the best possible results. Additionally, we compare its decoding performance and algorithmic complexity with other decoding algorithms in its category. Our results demonstrate a gain in performance of approximately 2.5 dB at a bit error rate (BER) of 6×10⁻⁶ for the LDPC (60,30) code.
Co-Authors Alaoui, Hicham Tahiri Alcabnani, Sara Azouaoui, Ahmed Zine-Dine, Fayçal