Analysis of Delay-Aware Worm Propagation Model in Wireless IoT Systems With Ratio-Dependent Functional Response

被引:3
作者
Madhusudanan, V. [1 ]
Geetha, R. [2 ]
Murthy, B. S. N. [3 ]
Dao, Nhu-Ngoc [4 ]
Cho, Sungrae [5 ]
机构
[1] SA Engn Coll, Dept Math, Chennai 600077, India
[2] SA Engn Coll, Dept Comp Sci & Engn, Chennai 600077, India
[3] Aditya Coll Engn & Technol, Dept Math, Surampalem 533437, India
[4] Ho Chi Minh City Open Univ, Fac Comp Sci, Ho Chi Minh City 70000, Vietnam
[5] Chung Ang Univ, Sch Comp Sci & Engn, Seoul 06974, South Korea
关键词
Grippers; Internet of Things; Wireless communication; Bifurcation; Delays; Mathematical models; Delay effects; Epidemic model; local stability; wireless internet of things (IoT); worm propagation; COMPUTER VIRUS;
D O I
10.1109/ACCESS.2023.3264978
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This article presents a delayed susceptibility, exposure, infectivity, recovery, and vaccination (SEIRV) model with nonlinear incidence and ratio-dependent functional responses. Model limitations and local stability analyses were examined with strict consideration of delay awareness. In addition, the presence of Hopf bifurcations with delay as a bifurcation parameter was investigated along with feature distributions with appropriate constraints. Numerical simulations are presented to verify the proposed theoretical results. In particular, if the latency exceeds the threshold, worm propagation in the system may become out of control. We demonstrated that the propagation characteristics of worms can easily be predicted and eliminated if the delay values are below a suitable threshold. Finally, we conclude that worm propagation is controllable by shifting the presence of Hopf bifurcations.
引用
收藏
页码:34968 / 34976
页数:9
相关论文
共 25 条
[1]   A delayed computer virus model with nonlinear incidence rate [J].
Chu, Yugui ;
Xia, Wanjun ;
Wang, Zecheng .
SYSTEMS SCIENCE & CONTROL ENGINEERING, 2019, 7 (01) :389-406
[2]   An Epidemic Theoretic Framework for Vulnerability Analysis of Broadcast Protocols in Wireless Sensor Networks [J].
De, Pradip ;
Liu, Yonghe ;
Das, Sajal K. .
IEEE TRANSACTIONS ON MOBILE COMPUTING, 2009, 8 (03) :413-425
[3]   Modeling and Stability Analysis of Worm Propagation in Wireless Sensor Network [J].
Feng, Liping ;
Song, Lipeng ;
Zhao, Qingshan ;
Wang, Hongbin .
MATHEMATICAL PROBLEMS IN ENGINEERING, 2015, 2015
[4]   Hopf bifurcation analysis of a delayed viral infection model in computer networks [J].
Feng, Liping ;
Liao, Xiaofeng ;
Li, Huaqing ;
Han, Qi .
MATHEMATICAL AND COMPUTER MODELLING, 2012, 56 (7-8) :167-179
[5]   Influence of Clamor on the Transmission of Worms in Remote Sensor Network [J].
Geetha, R. ;
Madhusudanan, V. ;
Srinivas, M. N. .
WIRELESS PERSONAL COMMUNICATIONS, 2021, 118 (01) :461-473
[6]   Cloud Integrated IoT Enabled Sensor Network Security: Research Issues and Solutions [J].
Geetha, R. ;
Suntheya, A. K. ;
Srikanth, G. Umarani .
WIRELESS PERSONAL COMMUNICATIONS, 2020, 113 (02) :747-771
[7]   A Light Weight Secure Communication Scheme for Wireless Sensor Networks [J].
Geetha, R. ;
Madhusudhan, V. ;
Padmavathy, T. ;
Lallithasree, A. .
WIRELESS PERSONAL COMMUNICATIONS, 2019, 108 (03) :1957-1976
[8]   Bifurcations in a fractional-order BAM neural network with four different delays [J].
Huang, Chengdai ;
Wang, Juan ;
Chen, Xiaoping ;
Cao, Jinde .
NEURAL NETWORKS, 2021, 141 :344-354
[9]   Novel bifurcation results for a delayed fractional-order quaternion-valued neural network [J].
Huang, Chengdai ;
Nie, Xiaobing ;
Zhao, Xuan ;
Song, Qiankun ;
Tu, Zhengwen ;
Xiao, Min ;
Cao, Jinde .
NEURAL NETWORKS, 2019, 117 :67-93
[10]   Hopf bifurcation of a delayed worm model with two latent periods [J].
Liu, Juan ;
Zhang, Zizhen .
ADVANCES IN DIFFERENCE EQUATIONS, 2019, 2019 (01)