Visible to the public Biblio

Filters: Keyword is monte carlo  [Clear All Filters]
2021-05-05
Tang, Sirui, Liu, Zhaoxi, Wang, Lingfeng.  2020.  Power System Reliability Analysis Considering External and Insider Attacks on the SCADA System. 2020 IEEE/PES Transmission and Distribution Conference and Exposition (T D). :1—5.

Cybersecurity of the supervisory control and data acquisition (SCADA) system, which is the key component of the cyber-physical systems (CPS), is facing big challenges and will affect the reliability of the smart grid. System reliability can be influenced by various cyber threats. In this paper, the reliability of the electric power system considering different cybersecurity issues in the SCADA system is analyzed by using Semi-Markov Process (SMP) and mean time-to-compromise (MTTC). External and insider attacks against the SCADA system are investigated with the SMP models and the results are compared. The system reliability is evaluated by reliability indexes including loss of load probability (LOLP) and expected energy not supplied (EENS) through Monte Carlo Simulations (MCS). The lurking threats of the cyberattacks are also analyzed in the study. Case studies were conducted on the IEEE Reliability Test System (RTS-96). The results show that with the increase of the MTTCs of the cyberattacks, the LOLP values decrease. When insider attacks are considered, both the LOLP and EENS values dramatically increase owing to the decreased MTTCs. The results provide insights into the establishment of the electric power system reliability enhancement strategies.

2021-04-27
Xie, J., She, H., Chen, X., Zhang, H., Niu, Y..  2020.  Test Method for Automatic Detection Capability of Civil Aviation Security Equipment Using Bayesian Estimation. 2020 IEEE 2nd International Conference on Civil Aviation Safety and Information Technology (ICCASIT. :831–835.
There are a lot of emerging security equipment required to be tested on detection rate (DR) and false alarm rate (FAR) for prohibited items. This article imports Bayesian approach to accept or reject DR and FAR. The detailed quantitative predictions can be made through the posterior distribution obtained by Markov chain Monte Carlo method. Based on this, HDI + ROPE decision rule is established. For the tests that need to make early decision, HDI + ROPE stopping rule is presented with biased estimate value, and criterial precision rule is presented with unbiased estimate value. Choosing the stopping rule according to the test purpose can achieve the balance of efficiency and accuracy.
2021-03-15
Ibrahim, A. A., Ata, S. Özgür, Durak-Ata, L..  2020.  Performance Analysis of FSO Systems over Imperfect Málaga Atmospheric Turbulence Channels with Pointing Errors. 2020 12th International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP). :1–5.
In this study, we investigate the performance of FSO communication systems under more realistic channel model considering atmospheric turbulence, pointing errors and channel estimation errors together. For this aim, we first derived the composite probability density function (PDF) of imperfect Málaga turbulence channel with pointing errors. Then using this PDF, we obtained bit-error-rate (BER) and ergodic channel capacity (ECC) expressions in closed forms. Additionally, we present the BER and ECC metrics of imperfect Gamma-Gamma and K turbulence channels with pointing errors as special cases of Málaga channel. We further verified our analytic results through Monte-Carlo simulations.
2020-12-28
Makarfi, A. U., Rabie, K. M., Kaiwartya, O., Li, X., Kharel, R..  2020.  Physical Layer Security in Vehicular Networks with Reconfigurable Intelligent Surfaces. 2020 IEEE 91st Vehicular Technology Conference (VTC2020-Spring). :1—6.

This paper studies the physical layer security (PLS) of a vehicular network employing a reconfigurable intelligent surface (RIS). RIS technologies are emerging as an important paradigm for the realisation of smart radio environments, where large numbers of small, low-cost and passive elements, reflect the incident signal with an adjustable phase shift without requiring a dedicated energy source. Inspired by the promising potential of RIS-based transmission, we investigate two vehicular network system models: One with vehicle-to-vehicle communication with the source employing a RIS-based access point, and the other model in the form of a vehicular adhoc network (VANET), with a RIS-based relay deployed on a building. Both models assume the presence of an eavesdropper to investigate the average secrecy capacity of the considered systems. Monte-Carlo simulations are provided throughout to validate the results. The results show that performance of the system in terms of the secrecy capacity is affected by the location of the RIS-relay and the number of RIS cells. The effect of other system parameters such as source power and eavesdropper distances are also studied.

2020-12-15
Cribbs, M., Romero, R., Ha, T..  2020.  Orthogonal STBC Set Building and Physical Layer Security Application. 2020 IEEE 21st International Workshop on Signal Processing Advances in Wireless Communications (SPAWC). :1—5.
Given a selected complex orthogonal space-time block code (STBC), transformation algorithms are provided to build a set, S, of unique orthogonal STBCs with cardinality equal to \textbackslashtextbarS\textbackslashtextbar = 2r+c+k-1·r!·c!, where r, c, and k are the number of rows, columns, and data symbols in the STBC matrix, respectively. A communications link is discussed that encodes data symbols with a chosen STBC from the set known only to the transmitter and intended receiver as a means of providing physical layer security (PLS). Expected bit error rate (BER) and informationtheoretic results for an eavesdropper with a priori knowledge of the communications link parameters with the exception of the chosen STBC are presented. Monte Carlo simulations are provided to confirm the possible BER results expected when decoding the communications link with alternative STBCs from the set. Application of the transformation algorithms provided herein are shown to significantly increase the brute force decoding complexity of an eavesdropper compared to a related work in the literature.
2020-11-20
Yogarathinam, A., Chaudhuri, N. R..  2019.  Wide-Area Damping Control Using Multiple DFIG-Based Wind Farms Under Stochastic Data Packet Dropouts. 2019 IEEE Power Energy Society General Meeting (PESGM). :1—1.
Data dropouts in communication network can have a significant impact on wide-area oscillation damping control of a smart power grid with large-scale deployment of distributed and networked phasor measurement units and wind energy resources. Remote feedback signals sent through communication channels encounter data dropout, which is represented by the Gilbert-Elliott model. An observer-driven reduced copy (ORC) approach is presented, which uses the knowledge of the nominal system dynamics during data dropouts to improve the damping performance where conventional feedback would suffer. An expression for the expectation of the bound on the error norm between the actual and the estimated states relating uncertainties in the cyber system due to data dropout and physical system due to change in operating conditions is also derived. The key contribution comes from the analytical derivation of the impact of coupling between the cyber and the physical layer on ORC performance. Monte Carlo simulation is performed to calculate the dispersion of the error bound. Nonlinear time-domain simulations demonstrate that the ORC produces significantly better performance compared to conventional feedback under higher data drop situations.
Dung, L. T., Tran, H. T. K., Hoa, N. T. T., Choi, S..  2019.  Analysis of Local Secure Connectivity of Legitimate User in Stochastic Wireless Networks. 2019 3rd International Conference on Recent Advances in Signal Processing, Telecommunications Computing (SigTelCom). :155—159.
In this paper, we investigate the local secure connectivity in terms of the probability of existing a secure wireless connection between two legitimate users and the isolated security probability of a legitimate user in stochastic wireless networks. Specifically, the closed-form expressions of the probability that there is a secure wireless communication between two legitimate users are derived first. Then, based on these equations, the corresponding isolated secure probability are given. The characteristics of local secure connectivity are examined in four scenarios combined from two wireless channel conditions (deterministic/Rayleigh fading) and two eavesdropper configurations (non-colluding/colluding). All the derived mathematical equations are validated by the Monte-Carlo simulation. The obtained numerical results in this paper reveal some interesting features of the impact of eavesdropper collusion, wireless channel fading, and density ratio on the secure connection probability and the isolated security probability of legitimate user in stochastic networks.
2020-07-16
Kadampot, Ishaque Ashar, Tahmasbi, Mehrdad, Bloch, Matthieu R.  2019.  Codes for Covert Communication over Additive White Gaussian Noise Channels. 2019 IEEE International Symposium on Information Theory (ISIT). :977—981.

We propose a coding scheme for covert communication over additive white Gaussian noise channels, which extends a previous construction for discrete memoryless channels. We first show how sparse signaling with On-Off keying fails to achieve the covert capacity but that a modification allowing the use of binary phase-shift keying for "on" symbols recovers the loss. We then construct a modified pulse-position modulation scheme that, combined with multilevel coding, can achieve the covert capacity with low-complexity error-control codes. The main contribution of this work is to reconcile the tension between diffuse and sparse signaling suggested by earlier information-theoretic results.

2020-06-02
Kundu, M. K., Shabab, S., Badrudduza, A. S. M..  2019.  Information Theoretic Security over α-µ/α-µ Composite Multipath Fading Channel. 2019 IEEE International Conference on Telecommunications and Photonics (ICTP). :1—4.

Multipath fading as well as shadowing is liable for the leakage of confidential information from the wireless channels. In this paper a solution to this information leakage is proposed, where a source transmits signal through a α-μ/α-μ composite fading channel considering an eavesdropper is present in the system. Secrecy enhancement is investigated with the help of two fading parameters α and μ. To mitigate the impacts of shadowing a α-μ distribution is considered whose mean is another α-μ distribution which helps to moderate the effects multipath fading. The mathematical expressions of some secrecy matrices such as the probability of non-zero secrecy capacity and the secure outage probability are obtained in closed-form to analyze security of the wireless channel in light of the channel parameters. Finally, Monte-Carlo simulations are provided to justify the correctness of the derived expressions.

2020-04-24
Balijabudda, Venkata Sreekanth, Thapar, Dhruv, Santikellur, Pranesh, Chakraborty, Rajat Subhra, Chakrabarti, Indrajit.  2019.  Design of a Chaotic Oscillator based Model Building Attack Resistant Arbiter PUF. 2019 Asian Hardware Oriented Security and Trust Symposium (AsianHOST). :1—6.

Physical Unclonable Functions (PUFs) are vulnerable to various modelling attacks. The chaotic behaviour of oscillating systems can be leveraged to improve their security against these attacks. We have integrated an Arbiter PUF implemented on a FPGA with Chua's oscillator circuit to obtain robust final responses. These responses are tested against conventional Machine Learning and Deep Learning attacks for verifying security of the design. It has been found that such a design is robust with prediction accuracy of nearly 50%. Moreover, the quality of the PUF architecture is evaluated for uniformity and uniqueness metrics and Monte Carlo analysis at varying temperatures is performed for determining reliability.

2020-04-10
Huang, Weiqing, Zhang, Qiaoyu, Wei, Dong, Li, Huiyan.  2019.  A Secure and Power-Efficient Constellations for Physical Layer Security. 2019 IEEE International Conference on Smart Internet of Things (SmartIoT). :479—483.
With the development of wireless networks, the security of wireless systems is becoming more and more important. In this paper, a novel double layers constellations is proposed to protect the polarization modulation information from being acquired by the eavesdropper. Based on the double layers constellations, a constellations' optimization algorithm for achieving high power-efficiency is proposed. Based on this algorithm, 4,8,16-order double-layer constellations are designed. We use Monte Carlo simulation to test the security performance and symbol error rate performance of this constellations. The results show that the double layers constellations can effectively ensure communication security and the SER performance has superiority over the classic symmetrical constellations.
2020-03-09
Sion, Laurens, Van Landuyt, Dimitri, Wuyts, Kim, Joosen, Wouter.  2019.  Privacy Risk Assessment for Data Subject-Aware Threat Modeling. 2019 IEEE Security and Privacy Workshops (SPW). :64–71.
Regulatory efforts such as the General Data Protection Regulation (GDPR) embody a notion of privacy risk that is centered around the fundamental rights of data subjects. This is, however, a fundamentally different notion of privacy risk than the one commonly used in threat modeling which is largely agnostic of involved data subjects. This mismatch hampers the applicability of privacy threat modeling approaches such as LINDDUN in a Data Protection by Design (DPbD) context. In this paper, we present a data subject-aware privacy risk assessment model in specific support of privacy threat modeling activities. This model allows the threat modeler to draw upon a more holistic understanding of privacy risk while assessing the relevance of specific privacy threats to the system under design. Additionally, we propose a number of improvements to privacy threat modeling, such as enriching Data Flow Diagram (DFD) system models with appropriate risk inputs (e.g., information on data types and involved data subjects). Incorporation of these risk inputs in DFDs, in combination with a risk estimation approach using Monte Carlo simulations, leads to a more comprehensive assessment of privacy risk. The proposed risk model has been integrated in threat modeling tool prototype and validated in the context of a realistic eHealth application.
2020-02-10
Gao, Jian, Bai, Huifeng, Wang, Dongshan, Wang, Licheng, Huo, Chao, Hou, Yingying.  2019.  Rapid Security Situation Prediction of Smart Grid Based on Markov Chain. 2019 IEEE 3rd Information Technology, Networking, Electronic and Automation Control Conference (ITNEC). :2386–2389.

Based on Markov chain analysis method, the situation prediction of smart grid security and stability can be judged in this paper. First component state transition probability matrix and component state prediction were defined. A fast derivation method of Markov state transition probability matrix using in system state prediction was proposed. The Matlab program using this method was compiled to analyze and obtain the future state probability distribution of grid system. As a comparison the system state distribution was simulated based on sequential Monte Carlo method, which was in good agreement with the state transition matrix, and the validity of the method was verified. Furthermore, the situation prediction of the six-node example was analyzed, which provided an effective prediction and analysis tool for the security situation.

2019-10-23
Alshawish, Ali, Spielvogel, Korbinian, de Meer, Hermann.  2019.  A Model-Based Time-to-Compromise Estimator to Assess the Security Posture of Vulnerable Networks. 2019 International Conference on Networked Systems (NetSys). :1-3.

Several operational and economic factors impact the patching decisions of critical infrastructures. The constraints imposed by such factors could prevent organizations from fully remedying all of the vulnerabilities that expose their (critical) assets to risk. Therefore, an involved decision maker (e.g. security officer) has to strategically decide on the allocation of possible remediation efforts towards minimizing the inherent security risk. This, however, involves the use of comparative judgments to prioritize risks and remediation actions. Throughout this work, the security risk is quantified using the security metric Time-To-Compromise (TTC). Our main contribution is to provide a generic TTC estimator to comparatively assess the security posture of computer networks taking into account interdependencies between the network components, different adversary skill levels, and characteristics of (known and zero-day) vulnerabilities. The presented estimator relies on a stochastic TTC model and Monte Carlo simulation (MCS) techniques to account for the input data variability and inherent prediction uncertainties.

2019-09-04
Paiker, N., Ding, X., Curtmola, R., Borcea, C..  2018.  Context-Aware File Discovery System for Distributed Mobile-Cloud Apps. 2018 IEEE International Conference on Cloud Computing Technology and Science (CloudCom). :198–203.
Recent research has proposed middleware to enable efficient distributed apps over mobile-cloud platforms. This paper presents a Context-Aware File Discovery Service (CAFDS) that allows distributed mobile-cloud applications to find and access files of interest shared by collaborating users. CAFDS enables programmers to search for files defined by context and content features, such as location, creation time, or the presence of certain object types within an image file. CAFDS provides low-latency through a cloud-based metadata server, which uses a decision tree to locate the nearest files that satisfy the context and content features requested by applications. We implemented CAFDS in Android and Linux. Experimental results show CAFDS achieves substantially lower latency than peer-to-peer solutions that cannot leverage context information.
2019-03-22
Kumar, A., Abdelhadi, A., Clancy, C..  2018.  Novel Anomaly Detection and Classification Schemes for Machine-to-Machine Uplink. 2018 IEEE International Conference on Big Data (Big Data). :1284-1289.

Machine-to-Machine (M2M) networks being connected to the internet at large, inherit all the cyber-vulnerabilities of the standard Information Technology (IT) systems. Since perfect cyber-security and robustness is an idealistic construct, it is worthwhile to design intrusion detection schemes to quickly detect and mitigate the harmful consequences of cyber-attacks. Volumetric anomaly detection have been popularized due to their low-complexity, but they cannot detect low-volume sophisticated attacks and also suffer from high false-alarm rate. To overcome these limitations, feature-based detection schemes have been studied for IT networks. However these schemes cannot be easily adapted to M2M systems due to the fundamental architectural and functional differences between the M2M and IT systems. In this paper, we propose novel feature-based detection schemes for a general M2M uplink to detect Distributed Denial-of-Service (DDoS) attacks, emergency scenarios and terminal device failures. The detection for DDoS attack and emergency scenarios involves building up a database of legitimate M2M connections during a training phase and then flagging the new M2M connections as anomalies during the evaluation phase. To distinguish between DDoS attack and emergency scenarios that yield similar signatures for anomaly detection schemes, we propose a modified Canberra distance metric. It basically measures the similarity or differences in the characteristics of inter-arrival time epochs for any two anomalous streams. We detect device failures by inspecting for the decrease in active M2M connections over a reasonably large time interval. Lastly using Monte-Carlo simulations, we show that the proposed anomaly detection schemes have high detection performance and low-false alarm rate.

2019-02-08
Xie, H., Lv, K., Hu, C..  2018.  An Improved Monte Carlo Graph Search Algorithm for Optimal Attack Path Analysis. 2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE). :307-315.

The problem of optimal attack path analysis is one of the hotspots in network security. Many methods are available to calculate an optimal attack path, such as Q-learning algorithm, heuristic algorithms, etc. But most of them have shortcomings. Some methods can lead to the problem of path loss, and some methods render the result un-comprehensive. This article proposes an improved Monte Carlo Graph Search algorithm (IMCGS) to calculate optimal attack paths in target network. IMCGS can avoid the problem of path loss and get comprehensive results quickly. IMCGS is divided into two steps: selection and backpropagation, which is used to calculate optimal attack paths. A weight vector containing priority, host connection number, CVSS value is proposed for every host in an attack path. This vector is used to calculate the evaluation value, the total CVSS value and the average CVSS value of a path in the target network. Result for a sample test network is presented to demonstrate the capabilities of the proposed algorithm to generate optimal attack paths in one single run. The results obtained by IMCGS show good performance and are compared with Ant Colony Optimization Algorithm (ACO) and k-zero attack graph.

2019-01-21
Cho, S., Chen, G., Chun, H., Coon, J. P., O'Brien, D..  2018.  Impact of multipath reflections on secrecy in VLC systems with randomly located eavesdroppers. 2018 IEEE Wireless Communications and Networking Conference (WCNC). :1–6.
Considering reflected light in physical layer security (PLS) is very important because a small portion of reflected light enables an eavesdropper (ED) to acquire legitimate information. Moreover, it would be a practical strategy for an ED to be located at an outer area of the room, where the reflection light is strong, in order to escape the vigilance of a legitimate user. Therefore, in this paper, we investigate the impact of multipath reflections on PLS in visible light communication in the presence of randomly located eavesdroppers. We apply spatial point processes to characterize randomly distributed EDs. The generalized error in signal-to-noise ratio that occurs when reflections are ignored is defined as a function of the distance between the receiver and the wall. We use this error for quantifying the domain of interest that needs to be considered from the secrecy viewpoint. Furthermore, we investigate how the reflection affects the secrecy outage probability (SOP). It is shown that the effect of the reflection on the SOP can be removed by adjusting the light emitting diode configuration. Monte Carlo simulations and numerical results are given to verify our analysis.
2018-11-14
Repp, P..  2017.  Diagnostics and Assessment of the Industrial Network Security Expert System. 2017 International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM). :1–5.
The paper dwells on the design of a diagnostic system and expert assessment of the significance of threats to the security of industrial networks. The proposed system is based on a new cyber-attacks classification and presupposes the existence of two structural blocks: the industrial network virtual model based on the scan selected nodal points and the generator of cyber-attacks sets. The diagnostic and expert assessment quality is improved by the use of the Markov chains or the Monte Carlo numerical method. The numerical algorithm of generating cyber-attacks sets is based on the LP$\tau$-sequence.
2018-10-26
Pfister, J., Gomes, M. A. C., Vilela, J. P., Harrison, W. K..  2017.  Quantifying equivocation for finite blocklength wiretap codes. 2017 IEEE International Conference on Communications (ICC). :1–6.

This paper presents a new technique for providing the analysis and comparison of wiretap codes in the small blocklength regime over the binary erasure wiretap channel. A major result is the development of Monte Carlo strategies for quantifying a code's equivocation, which mirrors techniques used to analyze forward error correcting codes. For this paper, we limit our analysis to coset-based wiretap codes, and give preferred strategies for calculating and/or estimating the equivocation in order of preference. We also make several comparisons of different code families. Our results indicate that there are security advantages to using algebraic codes for applications that require small to medium blocklengths.

2018-08-23
Mahmood, N. H., Pedersen, K. I., Mogensen, P..  2017.  A centralized inter-cell rank coordination mechanism for 5G systems. 2017 13th International Wireless Communications and Mobile Computing Conference (IWCMC). :1951–1956.
Multiple transmit and receive antennas can be used to increase the number of independent streams between a transmitter-receiver pair, or to improve the interference resilience property with the help of linear minimum mean squared error (MMSE) receivers. An interference aware inter-cell rank coordination framework for the future fifth generation wireless system is proposed in this article. The proposal utilizes results from random matrix theory to estimate the mean signal-to-interference-plus-noise ratio at the MMSE receiver. In addition, a game-theoretic interference pricing measure is introduced as an inter-cell interference management mechanism to balance the spatial multiplexing vs. interference resilience trade-off. Exhaustive Monte Carlo simulations results demonstrating the performance of the proposed algorithm indicate a gain of around 40% over conventional non interference-aware schemes; and within around 6% of the optimum performance obtained using a brute-force exhaustive search algorithm.
2018-06-07
Araújo, D. R. B., Barros, G. H. P. S. de, Bastos-Filho, C. J. A., Martins-Filho, J. F..  2017.  Surrogate models assisted by neural networks to assess the resilience of networks. 2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI). :1–6.

The assessment of networks is frequently accomplished by using time-consuming analysis tools based on simulations. For example, the blocking probability of networks can be estimated by Monte Carlo simulations and the network resilience can be assessed by link or node failure simulations. We propose in this paper to use Artificial Neural Networks (ANN) to predict the robustness of networks based on simple topological metrics to avoid time-consuming failure simulations. We accomplish the training process using supervised learning based on a historical database of networks. We compare the results of our proposal with the outcome provided by targeted and random failures simulations. We show that our approach is faster than failure simulators and the ANN can mimic the same robustness evaluation provide by these simulators. We obtained an average speedup of 300 times.

2017-12-12
Lee, S. H., Wang, L., Khisti, A., Womell, G. W..  2017.  Covert communication with noncausal channel-state information at the transmitter. 2017 IEEE International Symposium on Information Theory (ISIT). :2830–2834.

We consider the problem of covert communication over a state-dependent channel, where the transmitter has non-causal knowledge of the channel states. Here, “covert” means that the probability that a warden on the channel can detect the communication must be small. In contrast with traditional models without noncausal channel-state information at the transmitter, we show that covert communication can be possible with positive rate. We derive closed-form formulas for the maximum achievable covert communication rate (“covert capacity”) in this setting for discrete memoryless channels as well as additive white Gaussian noise channels. We also derive lower bounds on the rate of the secret key that is needed for the transmitter and the receiver to achieve the covert capacity.

2017-04-20
Takalo, H., Ahmadi, A., Mirhassani, M., Ahmadi, M..  2016.  Analog cellular neural network for application in physical unclonable functions. 2016 IEEE International Symposium on Circuits and Systems (ISCAS). :2635–2638.
In this paper an analog cellular neural network is proposed with application in physical unclonable function design. Dynamical behavior of the circuit and its high sensitivity to the process variation can be exploited in a challenge-response security system. The proposed circuit can be used as unclonable core module in the secure systems for applications such as device identification/authentication and secret key generation. The proposed circuit is designed and simulated in 45-nm bulk CMOS technology. Monte Carlo simulation for this circuit, results in unpolarized Gaussian-shaped distribution for Hamming Distance between 4005 100-bit PUF instances.
2017-03-29
Nicol, David M., Kumar, Rakesh.  2016.  Efficient Monte Carlo Evaluation of SDN Resiliency. Proceedings of the 2016 Annual ACM Conference on SIGSIM Principles of Advanced Discrete Simulation. :143–152.

Software defined networking (SDN) is an emerging technology for controlling flows through networks. Used in the context of industrial control systems, an objective is to design configurations that have built-in protection for hardware failures in the sense that the configuration has "baked-in" back-up routes. The objective is to leave the configuration static as long as possible, minimizing the need to have the controller push in new routing and filtering rules We have designed and implemented a tool that enables us to determine the complete connectivity map from an analysis of all switch configurations in the network. We can use this tool to explore the impact of a link failure, in particular to determine whether the failure induces loss of the ability to deliver a flow even after the built-in back-up routes are used. A measure of the original configuration's resilience to link failure is the mean number of link failures required to induce the first such loss of service. The computational cost of each link failure and subsequent analysis is large, so there is much to be gained by reducing the overall cost of obtaining a statistically valid estimate of resiliency. This paper shows that when analysis of a network state can identify all as-yet-unfailed links any one of whose failure would induce loss of a flow, then we can use the technique of importance sampling to estimate the mean number of links required to fail before some flow is lost, and analyze the potential for reducing the variance of the sample statistic. We provide both theoretical and empirical evidence for significant variance reduction.