论文标题

使用流行病学模型对自传播恶意软件进行建模

Modeling Self-Propagating Malware with Epidemiological Models

论文作者

Chernikova, Alesia, Gozzi, Nicolò, Boboila, Simona, Perra, Nicola, Eliassi-Rad, Tina, Oprea, Alina

论文摘要

自我传播恶意软件(SPM)最近造成了巨大的财务损失和巨大的社会影响,WannaCry和Colonial Pipeline等知名活动能够在互联网上迅速传播并导致服务中断。迄今为止,SPM的传播行为仍未得到充分理解,从而导致捍卫这些网络威胁的困难。为了解决这一差距,在本文中,我们对新提出的用于SPM传播的流行病学模型进行了全面分析,易感感染感染的休眠反射(SIIDR)。我们对SIIDR模型的稳定性进行了理论分析,并通过将其表示为连续时间的普通微分方程系统来得出其基本繁殖数。我们获得了在各种条件下生成的15个Wanancry攻击痕迹,得出模型的过渡速率,并表明Siidr最适合真实数据。我们发现,在建模SPM传播时,SIIDR模型的表现优于流行病学(例如SI,SIS和SIS)的更确定的隔室模型。

Self-propagating malware (SPM) has recently resulted in large financial losses and high social impact, with well-known campaigns such as WannaCry and Colonial Pipeline being able to propagate rapidly on the Internet and cause service disruptions. To date, the propagation behavior of SPM is still not well understood, resulting in the difficulty of defending against these cyber threats. To address this gap, in this paper we perform a comprehensive analysis of a newly proposed epidemiological model for SPM propagation, Susceptible-Infected-Infected Dormant-Recovered (SIIDR). We perform a theoretical analysis of the stability of the SIIDR model and derive its basic reproduction number by representing it as a system of Ordinary Differential Equations with continuous time. We obtain access to 15 WananCry attack traces generated under various conditions, derive the model's transition rates, and show that SIIDR fits best the real data. We find that the SIIDR model outperforms more established compartmental models from epidemiology, such as SI, SIS, and SIR, at modeling SPM propagation.

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