DC FieldValueLanguage
dc.contributor.authorNtalianis, Klimis-
dc.contributor.authorMastorakis, Nikolaos-
dc.contributor.authorSkraparlis, Athanasios-
dc.date.accessioned2024-07-12T08:54:53Z-
dc.date.available2024-07-12T08:54:53Z-
dc.date.issued2022-07-01-
dc.identifierscopus-85134215045-
dc.identifier.issn2169-3536-
dc.identifier.other85134215045-
dc.identifier.urihttps://uniwacris.uniwa.gr/handle/3000/2734-
dc.description.abstractCritical infrastructures are assets of invaluable importance, essential for the whole world. Since they serve core functions of our societies, they often become targets of terrorists. Many critical infrastructures are vulnerable, due to their short distance from public roads and in the past years, several vehicle-bomb incidents have been recorded. This paper focuses on the case of truck-bombs, which can either be created from scratch, or terrorists can easily hijack truck cargos carrying dangerous goods and turn them into bombs. The latter are typically called ADR truck cargos, according to the respective agreement of the 30th of September 1957, concerning the international carriage of dangerous goods by road. The proposed scheme performs threat assessment of neighboring critical infrastructures, aiming at preventing explosions of truck-bombs. To do so, each crucial point of a critical infrastructure is initially associated with a level of importance. Next, three scenarios are analyzed: (a) single-attack single-infrastructure, (b) multiple-attack single-infrastructure, and (c) multiple-attack multiple-infrastructure. To reduce computational complexity, the third scenario is simplified to one of the two other scenarios, by introducing a novel fusion technique for the non-overlapping segments of the Voronoi tessellation. By this way, an area of threat assessment is estimated for each critical infrastructure. Then, the threat level is assessed in real time by an innovative algorithm, which: (a) estimates the impact of multiple consecutive explosions, (b) uses five adapted threat levels and (c) introduces multiple criteria and minimum classification conditions based on the number of crucial points and their levels of importance. Extensive real world experimental results and comparisons to other works, exhibit the pros and cons of the proposed scheme. In particular, compared to related work, the proposed scheme improves: (a) computational time by 74.5%, (b) threat notification time by 86.9% and (c) estimated surveillance cost by 98.6%.en_US
dc.language.isoenen_US
dc.relation.ispartofIEEE Accessen_US
dc.subjectADRen_US
dc.subjectCritical infrastructureen_US
dc.subjectMultiple explosionsen_US
dc.subjectReal timeen_US
dc.subjectTerrorism attacksen_US
dc.subjectThreat assessmenten_US
dc.subjectTruck-bomben_US
dc.subjectVoronoi tessellationen_US
dc.titleReal Time Threat Assessment of Truck Cargos Carrying Dangerous Goods for Preventing Terrorism Attacks on Neighboring Critical Infrastructuresen_US
dc.typeArticleen_US
dc.identifier.doi10.1109/ACCESS.2022.3189674en_US
dc.identifier.scopus2-s2.0-85134215045-
dcterms.accessRights1en_US
dc.relation.deptDepartment of Business Administrationen_US
dc.relation.facultySchool of Administrative, Economics and Social Sciencesen_US
dc.relation.volume10en_US
dc.collaborationUniversity of West Attica (UNIWA)en_US
dc.journalsOpen Accessen_US
dc.publicationPeer Revieweden_US
dc.countryGreeceen_US
local.metadatastatusverifieden_US
item.openairetypeArticle-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.languageiso639-1en-
crisitem.author.deptDepartment of Business Administration-
crisitem.author.facultySchool of Administrative, Economics and Social Sciences-
crisitem.author.parentorgSchool of Administrative, Economics and Social Sciences-
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