高级搜索

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

零日病毒传播模型及稳定性分析

孟庆微 仇铭阳 王刚 马润年

孟庆微, 仇铭阳, 王刚, 马润年. 零日病毒传播模型及稳定性分析[J]. 电子与信息学报, 2021, 43(7): 1849-1855. doi: 10.11999/JEIT200519
引用本文: 孟庆微, 仇铭阳, 王刚, 马润年. 零日病毒传播模型及稳定性分析[J]. 电子与信息学报, 2021, 43(7): 1849-1855. doi: 10.11999/JEIT200519
Qingwei MENG, Mingyang QIU, Gang WANG, Runnian MA. Zero-day Virus Transmission Model and Stability Analysis[J]. Journal of Electronics & Information Technology, 2021, 43(7): 1849-1855. doi: 10.11999/JEIT200519
Citation: Qingwei MENG, Mingyang QIU, Gang WANG, Runnian MA. Zero-day Virus Transmission Model and Stability Analysis[J]. Journal of Electronics & Information Technology, 2021, 43(7): 1849-1855. doi: 10.11999/JEIT200519

零日病毒传播模型及稳定性分析

doi: 10.11999/JEIT200519
基金项目: 国家自然科学基金(61573017)
详细信息
    作者简介:

    孟庆微:男,1980年生,博士后,副教授,研究方向为网络空间安全、通信信号处理

    仇铭阳:男,1997年生,硕士生,研究方向为网络空间安全

    王刚:男,1977年生,博士,副教授,研究方向为信息网络系统建设与规划

    马润年:男,1963年生,博士后,教授,研究方向为生物计算、神经网络

    通讯作者:

    王刚 wglxl@nudt.edu.cn

  • 中图分类号: TP393; TP309.5

Zero-day Virus Transmission Model and Stability Analysis

Funds: The National Nature Science Foundation of China (61573017)
  • 摘要: 针对零日病毒特点和传播规律,该文研究了零日病毒传播模型及稳定性。首先,分析了零日病毒传播机理,在易感-感染-移除-易感(SIRS)病毒传播模型基础上,重新定义了感染状态节点,引入执行状态节点和毁损状态节点,建立了零日病毒传播的易感-初始感染-零日-毁损-移除(SIZDR)病毒传播动力学模型;其次,运用劳斯稳定性判据,分析了系统平衡点的局部稳定性,基本再生数${R_0}$及其对病毒传播规模的影响。最后,仿真验证了模型局部稳定性,分析了节点感染率、节点度和节点毁损率等因素对零日病毒传播的影响。理论分析与仿真结果表明,该模型能客观反映零日病毒传播规律,零日病毒扩散规模与节点度、节点感染率正相关,与节点毁损率负相关,对已知病毒的针对性防控可有效提升对零日病毒的防御效果。
  • 图  1  SIZDR病毒传播模型

    图  2  不同$\beta $对应的系统状态

    图  3  不同$K$对应的系统状态

    图  4  不同$\sigma $对应的系统状态

  • [1] ZETTER K. Countdown to Zero Day[M]. ZETTER K. Countdown to Zero Day: Stuxnet and the Launch of the World’s First Digital Weapon. Broadway Books, 2015.
    [2] Cnbeta. 卡巴斯基透露有黑客同时利用Windows 10和Chrome零日漏洞发动攻击[EB/OL]. http://cnnvd.org.cn/web/xxk/yjxwById.tag?id=11,170, 2019.
    [3] Cnbeta. 网络安全研究人员发现新漏洞: 或成另一个WannaCry[EB/OL]. http://cnnvd.org.cn/web/xxk/yjxwById.tag?id=8,486, 2017.
    [4] SUN Xiaoyan, DAI Jun, LIU Peng, et al. Using Bayesian networks for probabilistic identification of zero-day attack paths[J]. IEEE Transactions on Information Forensics and Security, 2018, 13(10): 2506–2521. doi: 10.1109/TIFS.2018.2821095
    [5] SUN Xiaoyan, DAI Jun, LIU Peng, et al. Using Bayesian Networks to Fuse Intrusion Evidences and Detect Zero-day Attack Paths[M]. WANG Lingyu, JAJODIA S, and SINGHAL A. Network Security Metrics. Cham: Springer, 2017.
    [6] DIRO A A and CHILAMKURTI N. Distributed attack detection scheme using deep learning approach for internet of things[J]. Future Generation Computer Systems, 2018, 82: 761–768. doi: 10.1016/j.future.2017.08.043
    [7] KIM J Y, BU S J, and CHO S B. Zero-day malware detection using transferred generative adversarial networks based on deep Autoencoders[J]. Information Sciences, 2018, 460/461: 83–102. doi: 10.1016/j.ins.2018.04.092
    [8] 张瑜, 潘小明, LIU Qingzhong, 等. APT攻击与防御[J]. 清华大学学报: 自然科学版, 2017, 57(11): 1127–1133. doi: 10.16511/j.cnki.qhdxxb.2017.21.024

    ZHANG Yu, PAN Xiaoming, LIU Qingzhong, et al. APT attacks and defenses[J]. Journal of Tsinghua University:Science &Technology, 2017, 57(11): 1127–1133. doi: 10.16511/j.cnki.qhdxxb.2017.21.024
    [9] ZHANG Mengyuan, WANG Lingyu, JAJODIA S, et al. Network diversity: A security metric for evaluating the resilience of networks against zero-day attacks[J]. IEEE Transactions on Information Forensics and Security, 2016, 11(5): 1071–1086. doi: 10.1109/TIFS.2016.2516916
    [10] VALDEZ J S, GUEVARA P, AUDELO J, et al. Numerical approaching of SIR epidemic model for propagation of computer worms[J]. IEEE Latin America Transactions, 2015, 13(10): 3452–3460. doi: 10.1109/TLA.2015.7387254
    [11] 顾海俊, 蒋国平, 夏玲玲. 基于状态概率转移的SIRS病毒传播模型及其临界值分析[J]. 计算机科学, 2016, 43(S1): 64–67.

    GU Haijun, JIANG Guoping, and XIA Lingling. SIRS epidemic model and its Threshold based on state transition probability[J]. Computer Science, 2016, 43(S1): 64–67.
    [12] 王刚, 陆世伟, 胡鑫, 等. 潜伏机制下网络病毒传播SEIQRS模型及稳定性分析[J]. 哈尔滨工业大学学报, 2019, 51(5): 131–137. doi: 10.11918/j.issn.0367-6234.201805136

    WANG Gang, LU Shiwei, HU Xin, et al. Network virus spreading SEIQRS model and its stability under escape mechanism[J]. Journal of Harbin Institute of Technology, 2019, 51(5): 131–137. doi: 10.11918/j.issn.0367-6234.201805136
    [13] 王刚, 陆世伟, 胡鑫, 等. “去二存一”混合机制下的病毒扩散模型及稳定性分析[J]. 电子与信息学报, 2019, 41(3): 709–716. doi: 10.11999/JEIT180381

    WANG Gang, LU Shiwei, HU Xin, et al. Virus propagation model and stability under the hybrid mechanism of “Two-go and One-live”[J]. Journal of Electronics &Information Technology, 2019, 41(3): 709–716. doi: 10.11999/JEIT180381
    [14] WANG Xu, NI Wei, ZHENG Kangfeng, et al. Virus propagation modeling and convergence analysis in large-scale networks[J]. IEEE Transactions on Information Forensics and Security, 2016, 11(10): 2241–2254. doi: 10.1109/TIFS.2016.2581305
    [15] WANG Lei, YAO Changhua, YANG Yuqi, et al. Research on a dynamic virus propagation model to improve smart campus security[J]. IEEE Access, 2018, 6: 20663–20672. doi: 10.1109/ACCESS.2018.2817508
    [16] 秦李, 黄曙光, 陈骁. 病毒传播下的因特网级联故障模型构建与仿真[J]. 计算机应用研究, 2016, 33(4): 1228–1231, 1235. doi: 10.3969/j.issn.1001-3695.2016.04.059

    QIN Li, HUANG Shuguang, and CHEN Xiao. Model and simulation for cascading failure on internet based on virus propagation[J]. Application Research of Computers, 2016, 33(4): 1228–1231, 1235. doi: 10.3969/j.issn.1001-3695.2016.04.059
    [17] 巩永旺, 宋玉蓉, 蒋国平. 移动环境下网络病毒传播模型及其稳定性研究[J]. 物理学报, 2012, 61(11): 110205. doi: 10.7498/aps.61.110205

    GONG Yongwang, SONG Yurong, and JIANG Guoping. Epidemic spreading model and stability of the networks in mobile environment[J]. Acta Physica Sinica, 2012, 61(11): 110205. doi: 10.7498/aps.61.110205
  • 加载中
图(4)
计量
  • 文章访问数:  962
  • HTML全文浏览量:  630
  • PDF下载量:  61
  • 被引次数: 0
出版历程
  • 收稿日期:  2020-06-23
  • 修回日期:  2020-11-26
  • 网络出版日期:  2020-12-01
  • 刊出日期:  2021-07-10

目录

    /

    返回文章
    返回