Calculating availability and performability measures of repairable computer systems using randomization
TL;DR: The randomization method is used to calculate various measures over a finite observation period related to availability modeling of repairable computer systems, and is extended to calculate performability distributions.
Abstract: Repairable computer systems are considered, the availability behavior of which can be modeled as a homogeneous Markov process. The randomization method is used to calculate various measures over a finite observation period related to availability modeling of these systems. These measures include the distribution of the number of events of a certain type, the distribution of the length of time in a set of states, and the probability of a near-coincident fault. The method is then extended to calculate performability distributions. The method relies on coloring subintervals of the finite observation period based on the particular application, and then calculating the measure of interest using these colored intervals.
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TL;DR: It is found that many techniques from dependiveness evaluation can be applied in the security domain, but that significant challenges remain, largely due to fundamental differences between the accidental nature of the faults commonly assumed in dependability evaluation, and the intentional, human nature of cyber attacks.
Abstract: The development of techniques for quantitative, model-based evaluation of computer system dependability has a long and rich history. A wide array of model-based evaluation techniques is now available, ranging from combinatorial methods, which are useful for quick, rough-cut analyses, to state-based methods, such as Markov reward models, and detailed, discrete-event simulation. The use of quantitative techniques for security evaluation is much less common, and has typically taken the form of formal analysis of small parts of an overall design, or experimental red team-based approaches. Alone, neither of these approaches is fully satisfactory, and we argue that there is much to be gained through the development of a sound model-based methodology for quantifying the security one can expect from a particular design. In this work, we survey existing model-based techniques for evaluating system dependability, and summarize how they are now being extended to evaluate system security. We find that many techniques from dependability evaluation can be applied in the security domain, but that significant challenges remain, largely due to fundamental differences between the accidental nature of the faults commonly assumed in dependability evaluation, and the intentional, human nature of cyber attacks.
537 citations
Cites background from "Calculating availability and perfor..."
...They capture knowledge and expertise in a reusable form; once the attack tree for a certain security feature has been built, it can be included as part of a larger attack tree for a system that uses the security feature....
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01 Jan 1996
TL;DR: In this paper, the authors present a table of table of tables of this paper : Table of Table 1.3.1.1-3.2.0.1]
Abstract: Table of
339 citations
01 Jan 1993
TL;DR: In this paper, the use of stochastic reward nets (SRNs) for the automatic generation of large Markov reward models has been proposed, which allow the specification of practical performance, reliability and per-formability models.
Abstract: Markov and Markov reward models are widely used for the performance and reliability analysis of computer and communication systems. Models of real systems often contain thousands or even millions of states. We propose the use of Stochastic Reward Nets (SRNs) for the automatic generation of these large Markov reward models. SRNs do allow the concise specification of practical performance, reliability and per-formability models.
265 citations
TL;DR: This paper identifies the batch Markovian arrival process (BMAP) as an analytically tractable model of choice for aggregated traffic modeling of IP networks and identifies the expectation-maximization (EM) algorithm for efficient and numerical stable parameter estimation of the BMAP.
251 citations
Cites methods from "Calculating availability and perfor..."
...We show how the randomization technique [9], [14], [17] and a stable calculation of Poisson jump probabilities [8] can effectively be utilized for the computation of the time-dependent conditional expectation of a continuoustime Markov chain (CTMC) required by the E-step of the EM algorithm....
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01 Jan 1991
TL;DR: A unified approach to the specification of measures of performance, dependability, and performability is presented by using a model class well suited for representation of all three aspects of system behavior, and defining a variable class which allows for the Specification of a wide range of measuresof system behavior.
Abstract: Methods for evaluating system performance, dependability, and performability are becoming increasingly more important, particularly in the case of critical applications. Central to the evaluation process is the definition of specific measures of system behavior that are of interest to a user. This paper presents a unified approach to the specification of measures of performance, dependability, and performability. The unification is achieved by 1) using a model class well suited for representation of all three aspects of system behavior, and 2) defining a variable class which allows for the specification of a wide range of measures of system behavior. The resulting approach permits the specification of many non-traditional as well as traditional measures of system performance, dependability, and performability in a unified manner. Example instantiations of variables within this class are given and their relationships to variables used in traditional performance and dependability evaluations are illustrated.
184 citations
Cites background from "Calculating availability and perfor..."
...[29] (rate-based instant-of-time, interval-of-time, and time-averaged interval-of-time variable, cyclic and acyclic system), and de Souza e Silva and Gail [30] (rate and impulse based interval-of-time variable, cyclic and acyclic system)....
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...Notable here is the work of Trivedi et al. [31] (rate-based instant-of-time and interval-oftime variable, cyclic and acyclic system), Smith et al. [29] (rate-based instant-of-time, interval-of-time, and time-averaged interval-of-time variable, cyclic and acyclic system), and de Souza e Silva and Gail [30] (rate and impulse based interval-of-time variable, cyclic and acyclic system)....
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16,450 citations
01 Jan 1950
TL;DR: A First Course in Probability (8th ed.) by S. Ross is a lively text that covers the basic ideas of probability theory including those needed in statistics.
Abstract: Office hours: MWF, immediately after class or early afternoon (time TBA). We will cover the mathematical foundations of probability theory. The basic terminology and concepts of probability theory include: random experiments, sample or outcome spaces (discrete and continuous case), events and their algebra, probability measures, conditional probability A First Course in Probability (8th ed.) by S. Ross. This is a lively text that covers the basic ideas of probability theory including those needed in statistics. Theoretical concepts are introduced via interesting concrete examples. In 394 I will begin my lectures with the basics of probability theory in Chapter 2. However, your first assignment is to review Chapter 1, which treats elementary counting methods. They are used in applications in Chapter 2. I expect to cover Chapters 2-5 plus portions of 6 and 7. You are encouraged to read ahead. In lectures I will not be able to cover every topic and example in Ross, and conversely, I may cover some topics/examples in lectures that are not treated in Ross. You will be responsible for all material in my lectures, assigned reading, and homework, including supplementary handouts if any.
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