Yazar "Ibrahim, Lina Jamal" seçeneğine göre listele

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    LSOARP: A Link Stability and Obstacle-Aware Routing Protocol for UAV Networks
    (Penerbit UTHM, 2025) Alwhelat, Almuntadher Mahmood; Ilyas, Muhammad; Idoko, John Bush; Ibrahim, Lina Jamal; Al-Hakeem, Mazin S.; Salih, Sinan Q.
    As using Unmanned Aerial Vehicles (UAVs) continues to grow across military, environmental, and public safety sectors, we are seeing a fast development of Flying Ad Hoc Networks (FANETs). Despite this progress, creating reliable routing protocols for UAVs remains complex because of their high mobility, constantly changing network topology, frequent link drops, and physical obstacles in the environment. Current protocols often overlook the importance of link stability and obstacleaware navigation, which can lead to decreased performance in realworld applications. we present LSOARP: a Link Stability and ObstacleAware Routing Protocol customized for UAV networks. This new protocol combines Bézier-curve-based trajectory adjustments for better obstacle avoidance with a multi-criteria link evaluation that considers residual link lifetime, energy efficiency, and route availability. We model UAV movement using a realistic prediction mechanism that captures various states such as high, low, idle, and paused. Routing decisions are then made using a weighted cost function to select the most stable and energy-efficient paths, ensuring strong network performance. Simulation experiments conducted under different conditions—including varying node density, speed, pause times, and traffic loads—show that LSOARP considerably outperforms traditional protocols like RLPR and AODV. It offers higher packet delivery ratios, lower end-to-end delays, reduced energy consumption, and less control overhead. These promising results demonstrate that LSOARP is both scalable and reliable in complex UAV environments, making it a strong candidate for real-time FANET applications.
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    Öğe
    Securing critical information: An image cryptography digital based on multi level cryptographic
    (Altınbaş Üniversitesi / Lisansüstü Eğitim Enstitüsü, 2022) Ibrahim, Lina Jamal; Uçan, Osman Nuri
    The importance of image encryption has considerably increased specially after the spectacular growth of internet of things (IoT) and due to the simplicity of capturing and transferring digital images. Although there are several encryption approaches, chaotic with image cryptography is considered the most appropriate approach for image applications due to its sensitivity to starting conditions and control parameter value. This research aims at generating an encrypted image free of statistical information to make cryptanalysis infeasible. Therefore, a new method was introduced in this thesis called Multi-layer Chaotic Maps (MLCM) based on confusion and diffusion. Basically, the confusion method uses the Sensitive Logistic Map (SLM), Hénon Map, and the additive white Gaussian noise to generate random numbers to be used in the pixel permutation method. However, the diffusion method uses Extended Bernoulli Map (EBM), Tinkerbell, Burgers, and Ricker maps to generate the random matrix. The correlation between adjacent pixels was minimized to have a very small value (x10-3). Besides, the keyspace was extended to be very large (2^450) considering the key sensitivity to hinder brute force attack. Finally, a histogram was idealized to be perfectly equal in all occurrences and the resulted information entropy was equal to the ideal value (8), which means that the resulted encrypted image is free of statistical properties in terms of the value of the histogram and the value of information entropy. Based on the findings, the high randomness of the generated random sequences of the proposed confusion and diffusion methods is capable of producing a robust image encryption framework against all types of cryptanalysis attacks.