基于移动众包网络动态激励机制的恶意代码传播模型
Malware Propagation Model Based on Dynamic Incentive Mechanism of Mobile Crowdsourcing Network
王琪 1任建国 1王磊2
作者信息
- 1. 江苏师范大学 计算机科学与技术学院,江苏 徐州 221116
- 2. 淮河水利委员会沂沭泗水利管理局 水文局,江苏 徐州 221018
- 折叠
摘要
基于移动众包网络(MCN)的固有特性,引入动态激励促进网络移动用户(MU)的活跃性,研究了恶意代码在MCN中传播的动态行为,提出一个新的恶意代码传播模型SIR-M,M节点表示处理节点任务的众包节点.首先,考虑到刚被感染节点的能动性,受感染节点可通过MCN的众包机制寻求MU对此节点进行隔离和免疫强化.其次,通过稳定性分析和数值仿真验证模型有效性,与SIR模型进行比较以分析众包机制对系统的影响.结果表明,移动众包网络的众包机制显著减缓了恶意代码的传播速度,降低了恶意代码在网络中大规模泛滥的风险.
Abstract
Based on the inherent characteristics of mobile crowdsourcing networks(MCN),dynamic incentives are introduced to promote the activity analysis of mobile users(MU)in the network.The dynamic behavior of malicious code propagation in MCN is studied,and a new mali-cious code propagation model SIR-M is proposed,where M nodes represent crowdsourcing nodes that handle node tasks.Firstly,considering the initiative of the newly infected node,the infected node can seek MU isolation and immune enhancement for this node through the crowd-sourcing mechanism of MCN.Then,the effectiveness of the model was verified through stability analysis and numerical simulation,and com-pared with the SIR model to analyze the impact of crowdsourcing mechanism on the system.The results indicate that the crowdsourcing mecha-nism of mobile crowdsourcing networks significantly slows down the propagation speed of malicious code and reduces the risk of large-scale proliferation of malicious code in the network.
关键词
传播模型/动态激励/移动众包网络/稳定性分析/恶意代码Key words
propagation model/dynamic incentives/MCN/stability analysis/malware引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
万方数据