Shortest Path Network Interdiction With Goal Threshold

Wei, Xiangyu; Zhu, Cheng; Xiao, Kaiming; Yin, Qinye; Zha, Yabing

doi:10.1109/access.2018.2838570

Cited by 13 publications

(8 citation statements)

References 28 publications

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“…Various optimization techniques are used in modeling network interdiction problems. Among these, one may cite the shortest path problem (e.g., Israeli and Wood [23], Wei et al [24], Yaghlane et al [4], etc. ), the stochastic shortest path problem (e.g., Zhang et al [16]), the min-cut problem (e.g., Yaghlane et al [4]), Benders decomposition (e.g., Wei et al [24]), bilevel knapsack (e.g., Caprara et al [25]), to name a few.…”

Section: Literature Reviewmentioning

confidence: 99%

Attack Strategies on Networks With a Budget Constraint

et al. 2021

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In this paper, we develop solutions to the problem of identifying the k most vital cut-sets of a network under limited attacking resources in a network interdiction context. We treat three different versions of the problem, each having a different objective: namely, the highest probability of a successful attack, the least cost attack, and the least expected cost attack combining both success probability and attacking cost. We introduce a budget constraint to reflect the resource limitation of the attacker. We consider both the case of disjoint and non-disjoint cut-sets to target. We develop a simulation-optimization approach accounting for various techniques including the shortest path problem and the min-cut problem. The solution method is found to be very efficient even for large-scale networks. We implement the suggested algorithms for illustration purposes.

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Section: Literature Reviewmentioning

confidence: 99%

Attack Strategies on Networks With a Budget Constraint

et al. 2021

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“…In interdiction network literature, various models are investigated. Wei et al [13] propose algorithms to optimize the consumption of attacker's resources on the shortest path interdiction model by limiting the network capacities. They approach the problem using various tools including Benders decomposition, Lagrange duality, set-covering, and Lagrange approximation algorithms.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimal k Cut-Sets in Attack/Defense Strategies on Networks

et al. 2020

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The paper investigates the most critical k cut-sets to target in the context of attacks on networks. The targeted network fails if the attack successfully disables a full cut-set. The attack process is dynamic and targets one link at a time. We assume perfect information, so that the attacker picks the next link to target after identifying the outcome of the attack on the previous one. The attack may continue to reach up to k cut-sets. The problem is to identify which cut-sets to target (referred to as the k-critical cut-sets of the network) that maximize the probability of a successful attack. We distinguish both cases of disjoint and non-disjoint cut-sets. We develop an algorithm for each case with illustrations. We explore the large scale of networks and offer guidelines on the corresponding defensive strategies. INDEX TERMS cut-set, defense, interdiction networks, multiple-attacks, path-set.

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“…Shortest-path network interdiction problems can be extended for various application scenarios [23]. Wei et al [24] introduced a threshold on the capacity of a network and proposed algorithms based on decomposition and duality formulation to optimize the interdictor's resource consumption. However, the algorithms cannot scale up to large networks and are sensitive to network parameters.…”

Section: Related Workmentioning

confidence: 99%

A Decomposition Approach for Stochastic Shortest-Path Network Interdiction with Goal Threshold

Wei

Jiao

et al. 2019

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Shortest-path network interdiction, where a defender strategically allocates interdiction resource on the arcs or nodes in a network and an attacker traverses the capacitated network along a shortest s-t path from a source to a terminus, is an important research problem with potential real-world impact. In this paper, based on game-theoretic methodologies, we consider a novel stochastic extension of the shortest-path network interdiction problem with goal threshold, abbreviated as SSPIT. The attacker attempts to minimize the length of the shortest path, while the defender attempts to force it to exceed a specific threshold with the least resource consumption. In our model, threshold constraint is introduced as a trade-off between utility maximization and resource consumption, and stochastic cases with some known probability p of successful interdiction are considered. Existing algorithms do not perform well when dealing with threshold and stochastic constraints. To address the NP-hard problem, SSPIT-D, a decomposition approach based on Benders decomposition, was adopted. To optimize the master problem and subproblem iteration, an efficient dual subgraph interdiction algorithm SSPIT-S and a local research based better-response algorithm SSPIT-DL were designed, adding to the SSPIT-D. Numerical experiments on networks of different sizes and attributes were used to illustrate and validate the decomposition approach. The results showed that the dual subgraph and better-response procedure can significantly improve the efficiency and scalability of the decomposition algorithm. In addition, the improved enhancement algorithms are less sensitive and robust to parameters. Furthermore, the application in a real-world road network demonstrates the scalability of our decomposition approach.

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Shortest Path Network Interdiction With Goal Threshold

Cited by 13 publications

References 28 publications

Attack Strategies on Networks With a Budget Constraint

Attack Strategies on Networks With a Budget Constraint

Optimal k Cut-Sets in Attack/Defense Strategies on Networks

A Decomposition Approach for Stochastic Shortest-Path Network Interdiction with Goal Threshold

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