An exact approach for the r-interdiction median problem with fortification

Roboredo, Marcos Costa; Pessoa, Artur Alves; Aizemberg, Luiz

doi:10.1051/ro/2017060

Cited by 6 publications

(3 citation statements)

References 22 publications

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“…Analysing scientific articles describing the r-Interdiction Median Problem with the Fortification method, one can notice that the theory described in the publication by Church, Scaparra and Middlenton (2004) is taken as the basis for all calculations. Therefore, from all the studied articles (Higle, 2005;Berman, Krass, & Menezes, 2007;Liu, Fan, & Ordonez, 2009;Aksen, Piyade, & Aras, 2010;Jenelius, Westin & Holmgren, 2010;Akbari-Jafarabadi et al, 2017;Li, X., Kizito, & Paula, 2018;Roboredo, Pessoa, & Aizemberg, 2019) one was chosen for further research, which deals with attacks on critical objects. Only some scientific articles consider the possibility of using the method to integrate it into cyber strategy.…”

Section: Insights Into Regional Developmentmentioning

confidence: 99%

Industrial Control Systems (ICS) cyber prediction model

Katina¹,

Plėta²,

Petkevičius³

et al. 2023

IRD

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Acceleration of scientific and technical progress, speeding up of technological changes, IT process globalisation and integration of OT processes invoked new challenges in preparing cyber strategies. Issues with adapting strategy for a particular specificity, region and specific cyber-attacks are not applicable. Therefore, a natural need arises to adjust the process for future cyber-attacks. It should be noted that the vast majority of organisations still need to possess a strategy that has been developed in correlation with future cyber-attacks. A part of organisations, irrespective of the lack of methodology and necessary infrastructure at the initial stage, commenced applying strategic management methods as a more dynamic environment demanded adequate changes in the cyber security within the organisation itself. The organisation started to plan such changes because, at the initial stage of the strategic management theory development, the strategy was understood as a plan drawn up to achieve the set objectives, regardless of the future need. Implementing such strategic procedures is grounded on something other than scientific calculations and is often associated with excessive use of funds. Therefore, the main goal of this article is to determine how much the r-Interdiction Median Problem with Fortification (RIMF) module can be used as a model for deciding methods for protecting critical infrastructure systems.

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Section: Insights Into Regional Developmentmentioning

confidence: 99%

Industrial Control Systems (ICS) cyber prediction model

Katina¹,

Plėta²,

Petkevičius³

et al. 2023

IRD

View full text Add to dashboard Cite

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“…Khanduzi [17] implements two novel approaches to solve the multi-period interdiction problem with fortification. Roboredo [18] proposes a branch-and-cut algorithm for the RIMF problem, which is the best exact algorithm found. Furthermore, Roboredo [19] also put forward a branch-and-cut algorithm for the r-interdiction covering problem with fortification (RICF) problem, which is faster in solving large instances compared with the exact method found in the literature.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Gaming Case of the R-Interdiction Median Problem with Fortification and an MILP-Based Solution Approach

et al. 2020

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This paper studies the cyclic dynamic gaming case of the r-interdiction median problem with fortification (CDGC-RIMF), which is important for strengthening a facility’s reliability and invulnerability under various possible attacks. We formulated the CDGC-RIMF as a bi-objective mixed-integer linear programming (MILP) model with two opposing goals to minimize/maximize the loss from both the designer (leader) and attacker (follower) sides. The first goal was to identify the most cost-effective plan to build and fortify the facility considering minimum loss, whereas the attacker followed the designer to seek the most destructive way of attacking to cause maximum loss. We found that the two sides could not reach a static equilibrium with a single pair of confrontational plans in an ordinary case, but were able to reach a dynamically cyclic equilibrium when the plan involved multiple pairs. The proposed bi-objective model aimed to discover the optimal cyclic plans for both sides to reach a dynamic equilibrium. To solve this problem, we first started from the designer’s side with a design and fortification plan, and then the attacker was able to generate their worst attack plan based on that design. After that, the designer changed their plan again based on the attacker’s plan in order to minimize loss, and the attacker correspondingly modified their plan to achieve maximum loss. This game looped until, finally, a cyclic equilibrium was reached. This equilibrium was deemed to be optimal for both sides because there was always more loss for either side if they left the equilibrium first. This game falls into the subgame of a perfect Nash equilibrium—a kind of complete game. The proposed bi-objective model was directly solved by the CPLEX solver to achieve optimal solutions for small-sized problems and near-optimal feasible solutions for larger-sized problems. Furthermore, for large-scale problems, we developed a heuristic algorithm that implemented dynamic iterative partial optimization alongside MILP (DIPO-MILP), which showed better performance compared with the CPLEX solver when solving large-scale problems.

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“…This problem has received great attention and a number of effective solution algorithms has been developed. Among most effective are the implicit enumeration algorithm [27], an exact approach based on reformulating the problem as the maximal covering problem [28,36], and a branch-and-cut algorithm from [26].…”

Section: Introductionmentioning

confidence: 99%

Locating Facilities Under Deliberate Disruptive Attacks

Ushakov

Vasilyev

2020

Mathematical Optimization Theory and Operations Research

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Facility disruptions or failures may occur due to natural disasters or a deliberate man-made attack. Such an attack is known as interdiction. Recently, facility location problems, addressing intentional strikes against operating facilities and strategies to reduce their impact, have received particular attention. In this paper, we present a new location-interdiction median problem aimed at designing a distribution network which is robust to the worst-case, long-term facility losses. We suppose that there are two players: defender (system designer) and attacker. The defender decides where to locate facilities to minimize the overall cost of supplying the demands of customers. The attacker determines which r facilities to interdict to maximize the cost of serving the customers from the remaining operational facilities. Note that we suppose that the facilities are attacked simultaneously and interdicted facilities become unavailable. We propose bilevel and single-level integer formulations of this problem. For a particular case when the attacker hits a single facility, we develop a fast local search procedure based on implicit enumeration of interdiction strategies. We test our approaches in a series of computational experiments on well-known test problems.

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An exact approach for the r-interdiction median problem with fortification

Cited by 6 publications

References 22 publications

Industrial Control Systems (ICS) cyber prediction model

Industrial Control Systems (ICS) cyber prediction model

Dynamic Gaming Case of the R-Interdiction Median Problem with Fortification and an MILP-Based Solution Approach

Locating Facilities Under Deliberate Disruptive Attacks

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