Xiulai Li^1,2,3,4, Jieren Cheng^1,3,*, Chengchun Ruan^1,3, Bin Zhang^1,3, Xiangyan Tang^1,3, Mengzhe Sun⁵

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3265-3288, 2023, DOI:10.32604/cmc.2023.045588 - 26 December 2023

Abstract With the rising adoption of blockchain technology due to its decentralized, secure, and transparent features, ensuring its resilience against network threats, especially Distributed Denial of Service (DDoS) attacks, is crucial. This research addresses the vulnerability of blockchain systems to DDoS assaults, which undermine their core decentralized characteristics, posing threats to their security and reliability. We have devised a novel adaptive integration technique for the detection and identification of varied DDoS attacks. To ensure the robustness and validity of our approach, a dataset amalgamating multiple DDoS attacks was derived from the CIC-DDoS2019 dataset. Using this, our… More >

Abdul-Wahid A. Saif¹, Mohammad Ataur-Rahman¹, Sami Elferik¹, Muhammad F. Mysorewala¹, Mujahed Al-Dhaifallah^1,*, Fouad Yacef²

Intelligent Automation & Soft Computing, Vol.27, No.3, pp. 817-834, 2021, DOI:10.32604/iasc.2021.015932 - 01 March 2021

Abstract In this paper, the formation control problem of a group of unmanned air vehicle (UAV) quadrotors is solved using the Takagi–Sugeno (T–S) multi-model approach to linearize the nonlinear model of UAVs. The nonlinear model sof the quadrotor is linearized first around a set of operating points using Taylor series to get a set of local models. Our approach’s novelty is in considering the difference between the nonlinear model and the linearized ones as disturbance. Then, these linear models are interpolated using the fuzzy T–S approach to approximate the entire nonlinear model. Comparison of the nonlinear… More >

Lihua Zhu¹, Zhiqiang Wu¹, Lei Wang², Yu Wang^{1, *}

CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 405-418, 2020, DOI:10.32604/cmc.2020.010124 - 23 July 2020

Abstract The wind as a natural phenomenon would cause the derivation of the pesticide drops during the operation of agricultural unmanned aerial vehicles (UAV). In particular, the changeable wind makes it difficult for the precision agriculture. For accurate spraying of pesticide, it is necessary to estimate the real-time wind parameters to provide the correction reference for the UAV path. Most estimation algorithms are model based, and as such, serious errors can arise when the models fail to properly fit the physical wind motions. To address this problem, a robust estimation model is proposed in this paper. More >