ABDELLATIF JARJAR

Prof. ABDELLATIF JARJAR


Research Focus & Metrics

Academic Career Length

8Years (2019-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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30 June 2021 in Journal of Multimedia Information System
Verified
Journal Article
Open access
PDF file
AJABDELLATIF JARJAR
ABDELLATIF JARJAR

1 June 2024 in International Journal of Electrical and Computer Engineering (IJECE)
Verified
Journal Article
Open access
PDF file
HBHamid El Bourakkadi
Hamid El Bourakkadi
ACAbdelhakim Chemlal
Abdelhakim Chemlal
HTHassan TABTI
Hassan TABTI
MKMourad Kattass
Mourad Kattass
AJABDELLATIF JARJAR
ABDELLATIF JARJAR
ABAbdelhamid Benazzi
Abdelhamid Benazzi
This article presents an improvement to the traditional Vigenere encryption method, specifically adapted for the encryption of color images. This enhancement relies on the use of two chaotic maps widely employed in the field of cryptography. After vectorizing the original image and calculating the initialization value, which alters the seeding pixel to trigger the encryption process, our approach integrates two new large substitution tables. These tables are linked to confusion and diffusion functions, incorporating multiple reversible pseudo-random affine functions at the pixel level. Finally, a global permutation is applied to the entire resulting vector to increase the temporal complexity of potential attacks on our system. Simulations conducted on a diverse set of images of various sizes and formats demonstrate the resilience of our approach against any unexpected attacks.


1 June 2024 in Indonesian Journal of Electrical Engineering and Computer Science
Verified
Journal Article
Open access
PDF file
HBHamid El Bourakkadi
Hamid El Bourakkadi
ACAbdelhakim Chemlal
Abdelhakim Chemlal
HTHassan TABTI
Hassan TABTI
MKMourad Kattass
Mourad Kattass
AJABDELLATIF JARJAR
ABDELLATIF JARJAR
ABAbdelhamid Benazzi
Abdelhamid Benazzi
This paper presents an improved method for encrypting color images, surpassing the effectiveness of genetic crossover and substitution operations. The technique incorporates dynamic random functions to enhance the integrity of the resulting vector, increasing temporal complexity to thwart potential attacks. The improvement involves integrating genetic crossover and utilizing two extensive pseudorandom replacement tables derived from established chaotic maps in cryptography. Following the controlled vectorization of the original image, our approach initiates with a first genetic crossover inspired by deoxyribonucleic acid (DNA) behavior at the pixel level. This genetic crossover is succeeded by a confusion-diffusion lap, reinforcing the connection between encrypted pixels and their neighboring counterparts. The confusion-diffusion process employs dynamic pseudorandom affine functions at the pixel level. Then a second genetic crossover operator is applied. Simulations conducted on a diverse set of images with varying sizes and formats showcase the robustness of our method against statistical, brute-force, and differential attacks.

17 May 2022 in Medical & Biological Engineering & Computing
Verified
Journal Article
Closed access
PDF file
AJABDELLATIF JARJAR
ABDELLATIF JARJAR

24 May 2023
Verified
Conference Paper
Open access
HRHicham Rrghout
Hicham Rrghout
MKMourad Kattass
Mourad Kattass
YQYounes Qobbi
Younes Qobbi
NBNaima Benazzi
Naima Benazzi
AJABDELLATIF JARJAR
ABDELLATIF JARJAR
ABAbdelhamid Benazzi
Abdelhamid Benazzi
In this work, a new approach to image encryption is proposed. This crypto system is composed of two stages of the Hill cipher. First, a passage in vector of the original image is carried out, followed by a subdivision in blocks of three pixels, then, an invertible (3×3) order matrix is generated from the chaotic maps will be used for implementation an encryption process based on an affine transformation. Finally, another complete order matrix (3×3) not necessarily invertible is used to install a diffusion phase using a new mode enhancement (CBC) whose purpose is to protect our approach against any differential attack. Simulations on a large number of images prove that our algorithm has excellent security performance.