Libyan Journal of Informatics https://uot.edu.ly/journals/index.php/LJI <p style="direction: ltr;"><strong>The Libyan Journal of Informatics</strong></p> <p style="direction: ltr;">Is a refereed, biannual, open-accessed scientific journal published by the faculty of information technology at university of Tripoli. The journal publishes original research and studies in the field of Information Science and Technology, and provides rich and diverse content that meets the needs of researchers, academics, and those interested in the field of informatics.</p> <p style="direction: ltr;">The Libyan Journal of Informatics aims to be a rich source of digital knowledge and aims to contribute to the development of the field of Information and Communication Technology by publishing distinguished scientific research and studies. Also, it provides free online access to its content.</p> Faculty of information technology at university of Tripoli, Libya en-US Libyan Journal of Informatics Image Encryption Based on Chaotic Logistic Map https://uot.edu.ly/journals/index.php/LJI/article/view/1675 <p>One of the most efficient methods for ensuring privacy in the digital <br>world is image encryption. We should facilitate and secure the transfer of private <br>images from one location to another when sent over a public network, such as <br>when sending them to be stored on a cloud drive. This paper proposed an algorithm to encrypt and decrypt the images. The approach uses a chaotic logistic <br>map to generate a keystream and then applies an XOR operation for the encryption and decryption of images. The findings indicate that the proposed technique <br>is an effective method for image encryption and decryption. We evaluate the metrics for encryption performance analysis: information entropy, histogram analysis, correlation coefficients between plain and cipher images, energy, contrast, <br>and homogeneity, and the analysis of the key's sensitivity. The results indicate <br>that the proposed technique demonstrates efficacy.</p> Mahmoud Hasan Adel Eluheshi Copyright (c) 2025 Libyan Journal of Informatics 2025-06-30 2025-06-30 2 01 1 16 Evaluating Redundancy and Failure Detection. https://uot.edu.ly/journals/index.php/LJI/article/view/1894 <p>The exponential growth of the Internet and its integration into daily life underscore the critical importance of resilient networks. Service outages can cause significant financial losses and damage reputation. First-hop redundancy protocols (FHRPs) are commonly used to enhance virtual gateway resilience and reduce downtime, but they can suffer from slow failure detection, leading to packet loss. Bidirectional routing detection (BFD) provides a rapid mechanism for link failure detection and connectivity monitoring.</p> <p>This paper explores the intricate landscape of network reliability, investigates the benefits of combining BFD with three prominent FHRPs (HSRP, VRRP, and GLBP) to improve network performance, increase availability, and reduce downtime. The evaluation is based on metrics of convergence time, packet loss, CPU utilization, and bandwidth consumption. Results from PNETLAB simulations indicate that using BFD greatly speeds up the detection of failures and reduces packet loss for all three protocols. GLBP achieved the fastest convergence, while VRRP exhibited the lowest CPU utilization. The findings indicate that the integration of Bidirectional Forwarding Detection (BFD) with First Hop Redundancy Protocol (FHRP) gateways significantly enhance network convergence times, thereby improving overall network reliability and stability.</p> Mai Elbaabaa Ahmed Ben Hassan Mahmud Mansour Najia Ben Saud Copyright (c) 2025 Libyan Journal of Informatics 2025-06-30 2025-06-30 2 01 17 42 Improving Security for the Libyan E-Government Portal https://uot.edu.ly/journals/index.php/LJI/article/view/1692 <p>The expansion of digital services in Libya has created an urgent need to secure access to sensitive government portals. This study proposes an enhanced multi-factor authentication system within the Libyan e-Government Portal Project by leveraging the government’s policy of linking Subscriber Identification Module (SIM) cards to the National Identity Number (NID) database for all Libyan citizens' mobile phone users. This linkage adds another authentication layer as an identity verification factor, leveraging the solution to the multi-factor authentication (MFA) level, ensuring that only users with verified identities can register mobile numbers to receive one-time passwords (OTPs).<br>Furthermore, this research highlights the successful implementation of NID-SIM linkage by the Central Bank of Libya (CBL) within their Foreign Currency Management System (FCMS) authentication process, providing a practical demonstration of the effectiveness of this linkage. A comparative analysis of authentication methods shows that using OTP via SMS authentication with NID-SIM linkage is a secure approach, thereby ensuring the integrity of sensitive government services. The proposed system addresses the common challenges facing traditional two-factor authentication systems, thereby enhancing</p> Hamdi Ahmed Jaber Copyright (c) 2025 Libyan Journal of Informatics 2025-06-30 2025-06-30 2 01 43 63 A Malware Detection and Classification using Artificial Neural Networks https://uot.edu.ly/journals/index.php/LJI/article/view/1723 <p>The rapid evolution of malware, particularly polymorphic and metamorphic variants, has rendered traditional detection methods, such as signature-based and behavioural detection, increasingly ineffective. This paper's objective is a comprehensive review of Artificial Neural Networks (ANNs) for malware detection and classification via a comprehensive review of the most widely used ANNs. The study focuses on supervised models, unsupervised models, and hybrid architectures across diverse environments. The study results indicate that the supervised models achieve exceptional accuracy (&gt;95%); the unsupervised models offer interpretability and adaptability to evolving threats but face challenges in generalising to unseen data. Conversely, hybrid models combine spatial and temporal feature extraction, achieving 99.4% accuracy, albeit with higher computational costs. This study emphasises the importance of the need for robust frameworks against obfuscation, efficient architectures for resource-constrained environments, and enhanced generalisation across malware families.</p> Mohammed Abosaeeda Mahmud Mansour Copyright (c) 2025 Libyan Journal of Informatics 2025-06-30 2025-06-30 2 01 64 90