Matches in SemOpenAlex for { <https://semopenalex.org/work/W2404932809> ?p ?o ?g. }
Showing items 1 to 97 of
97
with 100 items per page.
- W2404932809 endingPage "131" @default.
- W2404932809 startingPage "118" @default.
- W2404932809 abstract "Today's organizations are inherently open and connected, sharing knowledge and ideas in order to remain innovative. As a result, these organizations are also more vulnerable to information theft through different forms of security breaches caused by hackers and competitors. One way of understanding the vulnerability of an information system is to build and analyze the attack graph of that system. The attack graph of an information system contains all the paths that can be used to penetrate the system in order to breach critical assets. Although existing literature provides an abundance of attack graph generation algorithms, more methods are required to help analyze the attack graphs. In this paper, we study how best to deploy security countermeasures to protect an organization by analyzing the vulnerability of the organization through the use of its attack graph. In particular, we present an approach to find an optimal affordable subset of arcs, called an interdiction plan, on an attack graph that should be protected from attack to minimize the loss due to security breaches. We formulate this problem as a bi-level mixed-integer linear program and develop an exact algorithm to solve it. Experiments show that the algorithm is able to solve relatively large problems. Two heuristic methods, one with and the other without a heuristic to solve the master problem and both limiting the master problem branch-and-bound tree to only one node solve the large problems remarkably well. Experiments also reveal that the quality of an interdiction plan is relatively insensitive with respect to the error in the estimate of the attacker's budget, and that the breach loss drops sharply at the beginning, then levels off before finally dropping sharply again with increases in the security budget." @default.
- W2404932809 created "2016-06-24" @default.
- W2404932809 creator A5010985393 @default.
- W2404932809 creator A5023209828 @default.
- W2404932809 creator A5028876733 @default.
- W2404932809 date "2016-11-01" @default.
- W2404932809 modified "2023-10-16" @default.
- W2404932809 title "Interdicting attack graphs to protect organizations from cyber attacks: A bi-level defender–attacker model" @default.
- W2404932809 cites W1964498684 @default.
- W2404932809 cites W1990414757 @default.
- W2404932809 cites W1992713805 @default.
- W2404932809 cites W2032107708 @default.
- W2404932809 cites W2044121814 @default.
- W2404932809 cites W2044152003 @default.
- W2404932809 cites W2044221435 @default.
- W2404932809 cites W2045609581 @default.
- W2404932809 cites W2054127354 @default.
- W2404932809 cites W2065527711 @default.
- W2404932809 cites W2073269881 @default.
- W2404932809 cites W2083270195 @default.
- W2404932809 cites W2083658929 @default.
- W2404932809 cites W2091673436 @default.
- W2404932809 cites W2093517413 @default.
- W2404932809 cites W2098716819 @default.
- W2404932809 cites W2100033648 @default.
- W2404932809 cites W2131285604 @default.
- W2404932809 cites W2133494553 @default.
- W2404932809 cites W2133795641 @default.
- W2404932809 cites W2138336119 @default.
- W2404932809 cites W2141492178 @default.
- W2404932809 cites W2150802402 @default.
- W2404932809 cites W2156607688 @default.
- W2404932809 cites W2162253153 @default.
- W2404932809 cites W2169487153 @default.
- W2404932809 cites W2184215007 @default.
- W2404932809 cites W2207375515 @default.
- W2404932809 cites W2273063274 @default.
- W2404932809 cites W2342204193 @default.
- W2404932809 cites W4231612634 @default.
- W2404932809 doi "https://doi.org/10.1016/j.cor.2016.05.005" @default.
- W2404932809 hasPublicationYear "2016" @default.
- W2404932809 type Work @default.
- W2404932809 sameAs 2404932809 @default.
- W2404932809 citedByCount "49" @default.
- W2404932809 countsByYear W24049328092017 @default.
- W2404932809 countsByYear W24049328092018 @default.
- W2404932809 countsByYear W24049328092019 @default.
- W2404932809 countsByYear W24049328092020 @default.
- W2404932809 countsByYear W24049328092021 @default.
- W2404932809 countsByYear W24049328092022 @default.
- W2404932809 countsByYear W24049328092023 @default.
- W2404932809 crossrefType "journal-article" @default.
- W2404932809 hasAuthorship W2404932809A5010985393 @default.
- W2404932809 hasAuthorship W2404932809A5023209828 @default.
- W2404932809 hasAuthorship W2404932809A5028876733 @default.
- W2404932809 hasConcept C124119293 @default.
- W2404932809 hasConcept C127413603 @default.
- W2404932809 hasConcept C132525143 @default.
- W2404932809 hasConcept C146978453 @default.
- W2404932809 hasConcept C154945302 @default.
- W2404932809 hasConcept C173801870 @default.
- W2404932809 hasConcept C38652104 @default.
- W2404932809 hasConcept C41008148 @default.
- W2404932809 hasConcept C80444323 @default.
- W2404932809 hasConcept C86844869 @default.
- W2404932809 hasConcept C95713431 @default.
- W2404932809 hasConceptScore W2404932809C124119293 @default.
- W2404932809 hasConceptScore W2404932809C127413603 @default.
- W2404932809 hasConceptScore W2404932809C132525143 @default.
- W2404932809 hasConceptScore W2404932809C146978453 @default.
- W2404932809 hasConceptScore W2404932809C154945302 @default.
- W2404932809 hasConceptScore W2404932809C173801870 @default.
- W2404932809 hasConceptScore W2404932809C38652104 @default.
- W2404932809 hasConceptScore W2404932809C41008148 @default.
- W2404932809 hasConceptScore W2404932809C80444323 @default.
- W2404932809 hasConceptScore W2404932809C86844869 @default.
- W2404932809 hasConceptScore W2404932809C95713431 @default.
- W2404932809 hasLocation W24049328091 @default.
- W2404932809 hasOpenAccess W2404932809 @default.
- W2404932809 hasPrimaryLocation W24049328091 @default.
- W2404932809 hasRelatedWork W2002568488 @default.
- W2404932809 hasRelatedWork W2020865170 @default.
- W2404932809 hasRelatedWork W2362011720 @default.
- W2404932809 hasRelatedWork W2725637128 @default.
- W2404932809 hasRelatedWork W2766405666 @default.
- W2404932809 hasRelatedWork W2897593657 @default.
- W2404932809 hasRelatedWork W2966654968 @default.
- W2404932809 hasRelatedWork W4248923063 @default.
- W2404932809 hasRelatedWork W4293696969 @default.
- W2404932809 hasRelatedWork W4386004672 @default.
- W2404932809 hasVolume "75" @default.
- W2404932809 isParatext "false" @default.
- W2404932809 isRetracted "false" @default.
- W2404932809 magId "2404932809" @default.
- W2404932809 workType "article" @default.