Yazar "Salih, Sinan Q." seçeneğine göre listele

Listeleniyor 1 - 2 / 2
  • Küçük Resim
    Öğe
    Grey wolf optimizer and discrete chaotic map for substitution boxes design and optimization
    (Institute of Electrical and Electronics Engineers Inc., 2023) Lawah, Ali Ibrahim; Ibrahim, Abdullahi Abdu; Salih, Sinan Q.; Alhadawi, Hussam S.; JosephNg, Poh Soon
    A metaheuristic approach based on the nature-inspired and well-known Grey Wolf Optimization algorithm (GWO) was employed in this study to design an approach for retrieving strong designs of 8×8 substitution boxes (S-boxes). The GWO was developed as a novel metaheuristic based on inspiration from grey wolves and how they hunt. The ability of the GWO to quickly explore the search space for the near/optimal feature subsets that maximize any given fitness function (in consideration of its distinctive hierarchical structure) aids in the construction of strong S-boxes that can satisfy the required criteria. However, when tackling optimization problems, GWO may experience the problem of premature convergence. Therefore, a variant of GWO called Crossover Grey Wolf Optimizer (XGWO) has been proposed in this study. The performance of the proposed novel approach was evaluated using numerous cryptographic performance metrics, including bijective property, bit independence, strict avalanche, linear probability, and I/O XOR distribution and the result was contrasted with a couple of existing S-box creation techniques. Overall, the results of the experiment showed that the suggested S-box design had adequate cryptographic features. Author
  • [ X ]
    Öğe
    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.