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Introduction of first passage time (FPT) analysis for software reliability and network security

机译:引入首次通过时间(FPT)分析以提高软件可靠性和网络安全性

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The study of the First Passage Time (FPT) problem (also known as first passage problem, FPP) started more than a century ago, but its diverse applications in science and engineering mostly emerged in the last two to three decades. Assuming that X(t) is a one-dimensional stochastic process, the First Passage Time is defined as the time (T) when X(t) first crosses a threshold. Engineering reliability is obviously a suitable application domain, and indeed applications such as optimal dam design in hydrology and analysis of structural failure in civil and mechanical engineering are typical examples. Although we envision that the FPT problem has great potential in network and software reliability, it should be more useful for network security and survivability because the approaches developed for the FPT problem are mostly analytical. The assumption for this inference is that in reliability analysis, experimental or historical data are often more readily available, which makes statistical approaches such as survival analysis more convenient and likely more realistic. In contrast, data is generally more difficult to obtain in security and survivability analyses, and analytical approaches can be leveraged to play more important roles. Furthermore, security and survivability often have to deal with malicious actions that may be driven by sophisticated cognition and behavioral processes, which are highly variable over time and very difficult to detect with short term data. If the behavior of an intruder can be characterized with some stochastic process such as Brownian motion, then the FPT approach may be applied to find the closed-form solution of the probability density function (PDF) of the first passage time, which can be the time when the system breaks down or when the hacker is successful in compromising a network. In addition, the solutions to FPT depend on boundary and initial conditions of the corresponding partial differential equations, and they also describe the evolution of PDF over time. This may suggest that it is possible to model the behavior changes of an intruder over time and circumstances. Another advantage of FPT analysis is that it may help solve some non-Markov stochastic process problems in reliability analysis and survival analysis. In this article, we first briefly introduce the FPT problem with Brownian motion as an example, and then suggest its potential applications in software reliability and network security.
机译:对首次通过时间(FPT)问题(也称为第一次通过问题,FPP)的研究始于一个多世纪前,但是它在科学和工程学中的各种应用大多出现在最近的两到三十年中。假设X(t)是一维随机过程,则“第一通过时间”定义为X(t)首次超过阈值时的时间(T)。工程可靠性显然是一个合适的应用领域,确实,例如水文学中的最佳大坝设计以及土木和机械工程中的结构破坏分析等应用就是典型的例子。尽管我们认为FPT问题在网络和软件可靠性方面具有很大的潜力,但是它对于网络安全性和可生存性应该更有用,因为针对FPT问题开发的方法大多是分析性的。该推断的假设是,在可靠性分析中,通常更容易获得实验数据或历史数据,这使诸如生存分析之类的统计方法更加方便,并且可能更加现实。相反,在安全性和生存性分析中,通常很难获得数据,可以利用分析方法发挥更重要的作用。此外,安全性和生存能力通常必须处理由复杂的认知和行为过程驱动的恶意行为,这些行为随时间变化很大,很难用短期数据检测到。如果入侵者的行为可以通过某种随机过程(例如布朗运动)来表征,则可以使用FPT方法来找到第一次通过时间的概率密度函数(PDF)的封闭形式解,该解可以是系统崩溃或黑客成功破坏网络的时间。此外,FPT的解决方案取决于相应偏微分方程的边界条件和初始条件,并且它们还描述了PDF随着时间的变化。这可能表明可以对入侵者随时间和环境的行为变化进行建模。 FPT分析的另一个优点是,它可以帮助解决可靠性分析和生存分析中的某些非马尔可夫随机过程问题。在本文中,我们首先以布朗运动为例简要介绍FPT问题,然后提出其在软件可靠性和网络安全性方面的潜在应用。

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