...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Applied Mathematical Modelling >Modeling the spread of malware with the influence of heterogeneous immunization
【24h】

Modeling the spread of malware with the influence of heterogeneous immunization

机译：利用异构免疫的影响对恶意软件的传播进行建模

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

The immunities of computers against malware are actually heterogeneous depending upon the level of secure protection, which is largely determined by the security awareness of users. To understand the effects this can have on the propagation of malicious software, we herein develop a new compartmental model that takes into account heterogeneous immunization of the computer. In terms of protection levels, the traditional susceptible compartment is newly separated into two sub-compartments, weakly-protected and strongly-protected. Besides, our model includes two assumptions: a computer immediately possesses infectivity once it is infected by malware, and weakly-protected susceptible computers have a higher infection rate than strongly-protected susceptible computers. Appropriate Lyapunov functions are introduced to fully analyze the qualitative properties of this model. Specifically, it is proved that the malware-free equilibrium is globally asymptotically stable if the threshold is below unit, whereas the malware equilibrium is globally asymptotically stable if the threshold is above unit. Furthermore, the sensitivity of each parameter on the model's threshold is also analyzed. Through numerical simulations, a collection of effective measures for controlling malware spread is proposed, such as keeping as many systems strongly-protected as possible. These findings suggest that the security awareness of users should be taken both in the interpretation of malware parameters, as well as in the prediction of the evolution of future malware outbreaks.
机译：计算机针对恶意软件的免疫力实际上是不同的，具体取决于安全防护的级别，安全防护的级别很大程度上取决于用户的安全意识。为了了解其对恶意软件传播的影响，我们在此开发了一种新的隔离模型，该模型考虑了计算机的异构免疫。在保护级别方面，传统的易受伤害隔离区新近分为弱保护和强保护两个子隔离区。此外，我们的模型包括两个假设：一台计算机一旦被恶意软件感染，便立即具有传染性；而受保护程度较弱的易受感染计算机的感染率要高于受保护程度较高的易受感染计算机。引入了适当的Lyapunov函数以全面分析该模型的定性性质。具体地，证明了如果阈值低于单位，则无恶意软件的平衡在全局上是渐近稳定的，而如果阈值高于单位，则恶意软件的平衡在全局上是渐近稳定的。此外，还分析了每个参数对模型阈值的敏感性。通过数值模拟，提出了一系列有效的措施来控制恶意软件的传播，例如保持尽可能多的系统受到严格保护。这些发现表明，在解释恶意软件参数以及预测未来恶意软件爆发的演变过程中都应考虑到用户的安全意识。

著录项

  • 来源
    《Applied Mathematical Modelling》 |2016年第4期|3141-3152|共12页
  • 作者

    Wanping Liu; Chao Liu; Xiaoyang Liu; Shaoguo Cui; Xianying Huang;

  • 作者单位

    College of Computer Science and Engineering, Chongqing University of Technology, Chongqing 400054, China;

    College of Computer Science and Engineering, Chongqing University of Technology, Chongqing 400054, China;

    College of Computer Science and Engineering, Chongqing University of Technology, Chongqing 400054, China;

    College of Computer Science and Engineering, Chongqing University of Technology, Chongqing 400054, China;

    College of Computer Science and Engineering, Chongqing University of Technology, Chongqing 400054, China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Mathematical model; User security awareness; Malware propagation; Protection level; Global stability;

    机译：数学模型;用户安全意识;恶意软件传播;防护等级;全球稳定;

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号