Computer Science ›› 2024, Vol. 51 ›› Issue (6A): 230800032-7.doi: 10.11896/jsjkx.230800032

• Information Security • Previous Articles     Next Articles

Scheme for Maximizing Secure Communication Capacity in UAV-assisted Edge Computing Networks

XUE Jianbin, DOU Jun, WANG Tao, MA Yuling   

  1. School of Computer and Communication,Lanzhou University of Technology,Lanzhou 730050,China
  • Published:2024-06-06
  • About author:XUE Jianbin,born in 1973,Ph.D,professor.His main research interests include future mobile communication,communication network and system security,wireless network edge intelligence computing,IOT and ubiquitous heterogeneous networks.
    DOU Jun,born in 1999,postgraduate.Her main research interest is secure communication for drones.
  • Supported by:
    Gansu Science and Technology Program(23YFGA0062)and Innovation Fund of Gansu Province(2022A-215).

Abstract: Aiming at the problem that user information is easy to be leaked in UAV-assisted mobile edge computing system,based on non-orthogonal multiple access(NOMA) technology,a secure communication scheme for UAV-assisted mobile edge computing system is proposed.While ensuring the minimum secure computation requirement for each ground user,the average secure computation capability of the system is maximized by jointly optimizing the channel coefficients,the transmit power,the computation frequency of the central processing unit,the local computation and the UAV trajectory.Due to the uncertainty of the eavesdropper location,the coupling of multiple variables and the non-convexity of the problem,successive convex approximation and block coordinate descent method are used to solve the problem.Simulation results show that compared with the benchmark scheme,the proposed scheme outperforms the benchmark scheme in terms of system secure computation performance.

Key words: Mobile edge computing, Non-orthogonal multiple access, UAV, Physical layer security, Communications Security

CLC Number: 

  • TN929.5
[1]HUANG H L,SAVKIN A.A Method for Optimized Deploy-ment of Unmanned Aerial Vehicles for Maximum Coverage and MinimumInterferencein Cellular Networks[J].IEEE Transactions on Industrial Informatics,2019,15(5):2638-2647.
[2]DU Y Y,KUN W,ZHANG K Z.Joint Resources and Workflow Scheduling in UAV-Enabled Wirelessly-Powered MEC for IoT Systems[J].IEEE Transactions on Vehicular Technology,2019,68(10):10187-10200.
[3]HUANG F,CHEN J,WANG H C,et al.UAV-Assisted SWIPTin Internet of Things With Power Splitting:Trajectory Design and Power Allocation[J].IEEE Access,2019,7:68260-68270.
[4]ZHAN C,HU H,SUI X F,et al.Completion Time and Energy Optimization in the UAV-Enabled Mobile-Edge Computing System[J].IEEE Internet of Journal,2020,7(8):7808-7822.
[5]ZHOU F H,WU Y P,HU R,et al.Computation Rate Maximization in UAV-Enabled Wireless-Powered Mobile-Edge Computing Systems[J].IEEE Journal on Selected Areas in Communications,2018,36(9):1927-1941.
[6]HU Q Y,CAI Y L,YU G D,et al.Joint Offloading and Trajectory Design for UAV-Enabled Mobile Edge Computing Systems[J].IEEE Internet of Things Journal,2019,6(2):1879-1892.
[7]ZHANG T K,XU Y,JONATHAN L,et al.Joint Computationand Communication Design for UAV-Assisted Mobile Edge Computing in IoT[J].IEEE Transactions on Industrial Informatics,2020,16(8):5505-5516.
[8]YU Z,GONG Y M,GONG S M,et al.Joint Task Offloading and Resource Allocation in UAV-Enabled Mobile Edge Computing[J].IEEE Internet of Things Journal,2020,7(4):3147-3159.
[9]CUI F Y,CAI Y L,QIN Z J,et al.Multiple Access for Mobile-UAV Enabled Networks:Joint Trajectory Design and Resource Allocation[J].IEEE Transactions on Communications,2019,67(7):4980-4994.
[10]NA Z Y,LIU Y,SHI J C,et al.UAV-Supported Clustered NOMA for 6G-Enabled Internet of Things:Trajectory Planning and Resource Allocation[J].IEEE Internet of Things Journal,2021,8(20):15041-15048.
[11]LI S L,LI B G,ZHAO W.Joint Optimization of Caching and Computation in Multi-Server NOMA-MEC System via Reinforcement Learning[J].IEEE Access,2020,8:112762-112771.
[12]WU Y,NI K J,ZHANG C,et al.NOMA-Assisted Multi-Access Mobile Edge Computing:A Joint Optimization of Computation Offloading and Time Allocation[J].IEEE Transactions on Vehicular Technology,2018,67(12):12244-12258.
[13]ZHANG X C,ZHANG J,XIONG J,et al.Energy-EfficientMulti-UAV-Enabled Multiaccess Edge Computing Incorporating NOMA[J].IEEE Internet of Things Journal,2020,7(6):5613-5627.
[14]CHEN X Y,YANG Z T,ZHAO N,et al.Secure Transmission via Power Allocation in NOMA-UAV Networks With Circular Trajectory[J].IEEE Transactions on Vehicular Technology,2020,69(9):10033-10045.
[15]XU Y,ZHANG T K,YANG D C,et al.Joint Resource and Trajectory Optimization for Security in UAV-Assisted MEC Systems[J].IEEE Transactions on Communications,2021,69(1):573-588.
[16]SUN X L,YANG W W,CAI Y M.Secure Communication inNOMA-Assisted Millimeter-Wave SWIPT UAV Networks[J].IEEE Internet of Things Journal,2020,7(3):1884-1897.
[17]HU G J,CAI Y M,CAI Y L,et al.Joint Optimization of Position and Jamming Power for UAV-Aided Proactive Eavesdropping Over Multiple Suspicious Communication Links[J].IEEE Wireless Communications Letters,2020,9(12):2093-2097.
[18]HUANG H L,SAVKIN A,WEI N W.Navigation of a UAV Team for Collaborative Eavesdropping on Multiple Ground Transmitters[J].IEEE Transactions on vehicular Technology,2021,70(10):10450-10460.
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