Computational Intelligence Driven Secure Unmanned Aerial Vehicle Image Classification in Smart City Environment

查看全文 作　　者：Firas [1]Abedi;Hayder [2]M.A.Ghanimi;Abeer [3]D.Algarni;Naglaa [3]F.Soliman;Walid El-[4,5]Shafai;Ali Hashim [6]Abbas;Zahraa [7]H.Kareem;Hussein Muhi [8]Hariz;Ahmed [9]Alkhayyat 机构地区：[1]Department of Mathematics,College of Education,Al-Zahraa University forWomen,Karbala,Iraq;[2]Biomedical Engineering Department,College of Engineering,University ofWarith Al-Anbiyaa,Karbala,Iraq;[3]Department of Information Technology,College of Computer and Information Sciences,Princess Nourah bint Abdulrahman University,P.O.Box 84428,Riyadh,11671,Saudi Arabia;[4]Security Engineering Lab,Computer Science Department,Prince Sultan University,Riyadh,11586,Saudi Arabia;[5]Department of Electronics and Electrical Communications Engineering,Faculty of Electronic Engineering,Menoufia University,Menouf,32952,Egypt;[6]College of Information Technology,Imam Jaafar Al-Sadiq University,Al-Muthanna,66002,Iraq;[7]Department of Medical Instrumentation Techniques Engineering,Al-Mustaqbal University College,Hillah,51001,Iraq;[8]Computer Engineering Department,Mazaya University College,Dhi Qar,Iraq;[9]College of Technical Engineering,The Islamic University,Najaf,Iraq 出　　处：《Computer Systems Science & Engineering》索引2023年第47卷第12期,共18页 基　　金：Deputyship for Research&Inno-vation,Ministry of Education in Saudi Arabia for funding this research work through the Project Number RI-44-0446. 摘　　要：Computational intelligence(CI)is a group of nature-simulated computationalmodels and processes for addressing difficult real-life problems.The CI is useful in the UAV domain as it produces efficient,precise,and rapid solutions.Besides,unmanned aerial vehicles(UAV)developed a hot research topic in the smart city environment.Despite the benefits of UAVs,security remains a major challenging issue.In addition,deep learning(DL)enabled image classification is useful for several applications such as land cover classification,smart buildings,etc.This paper proposes novel meta-heuristics with a deep learning-driven secure UAV image classification(MDLS-UAVIC)model in a smart city environment.Themajor purpose of the MDLS-UAVIC algorithm is to securely encrypt the images and classify them into distinct class labels.The proposedMDLS-UAVIC model follows a two-stage process:encryption and image classification.The encryption technique for image encryption effectively encrypts the UAV images.Next,the image classification process involves anXception-based deep convolutional neural network for the feature extraction process.Finally,shuffled shepherd optimization(SSO)with a recurrent neural network(RNN)model is applied for UAV image classification,showing the novelty of the work.The experimental validation of the MDLS-UAVIC approach is tested utilizing a benchmark dataset,and the outcomes are examined in various measures.It achieved a high accuracy of 98%. 关 键 词：Computational intelligence unmanned aerial vehicles deep learning metaheuristics smart city image encryption image classification