Article Per Year (5 Year)
p-Index From 2021 - 2026
0.408
P-Index
This Author published in this journals
All Journal JOIV : International Journal on Informatics Visualization
N. Hasoon, Jamal
Unknown Affiliation
Computer Science & IT

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Lightweight Image Encryption Based on A Hybrid Approach Jabbar Altaay, Alaa A.; N. Hasoon, Jamal; Kassim Albahadily, Hassan
JOIV : International Journal on Informatics Visualization Vol 8, No 2 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.2.2757

Abstract

A secure image could be achieved by encryption, a technique for securing images over different media transmission lines with privacy and keeping them safe for the receiver. This paper proposes an image encryption approach to achieve excellent security by combining a lightweight encryption algorithm with the chaotic Peter De Jong map. The Lilliput algorithm, lightweight encryption, uses the Peter De-Jones map to produce keys. The suggested approach achieved a suitable level of complexity that matched the historical demands for transmission images. Two methods were used to conduct the tests on a standard image collection: an encrypted image and a generated key. Standard metrics find the similarity between the input and output images to achieve an accurate proposal performance. The encrypted image's entropy was assessed and discovered that it matched the original image values exactly. The results were satisfactory regarding obtaining a precise correlation rate between the original and encrypted photos. The decryption and reconstruction of the image were completed quickly and steadily, with a high success rate and excellent outcomes. The proposed approach was evaluated on a dataset of well-known test photos with unique features, including varying degrees of lightness and shade to create the perfect test.
Dynamic Key Generation Using GWO for IoT System A. Hameedi, Balsam; A. Hatem, Muntaha; N. Hasoon, Jamal
JOIV : International Journal on Informatics Visualization Vol 8, No 2 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.2.2761

Abstract

One well-known technological advancement that significantly impacts many things is the Internet of Things (IoT). These include connectivity, work, healthcare, and the economy. IoT can improve life in many situations, including classrooms and smart cities, through work automation, increased output, and decreased worry. However, cyberattacks and other risks significantly impact intelligent Internet of Things applications. Key generation is essential in information security and the various applications that use a distributed system, networks, or Internet of Things (IoT) systems. Several algorithms have been developed to protect IoT applications from malicious attacks; since IoT devices usually have small memory resources and limited computing and power resources, traditional key generation methods are inappropriate because they require high computational power and memory usage. This paper proposes a method of Dynamic Key Generation Method (DKGM) to overcome the difficulty using a specific chaotic map called the Zaslavskii Map and a swarm intelligent algorithm for optimization called Grey Wolf Optimizer (GWO). DKGM's ability to generate several groups-seed numbers using the Zaslavskii map depends on various initial parameters. GWO selects strong generated numbers depending on the randomness test as a fitness function. Three wolfs GWα, GWβ, and GWΩ, are used to simulate the behavior of a pack of grey wolves when attacking prey. The speed and position of each wolf are updated depending on the best three wolves. Finally, use the sets GWα in the round, GWβ in the subkey, and GWΩ in shifting operations of the Chacha20 hash function. The dynamic procedure was used to improve the high-security analysis of the DKGM approach over earlier methods. Simulations show that the suggested method is preferable for IoT applications.
Co-Authors A. Hameedi, Balsam A. Hatem, Muntaha Jabbar Altaay, Alaa A. Kassim Albahadily, Hassan