Uncovering illicit supply networks and their interfaces to licit counterparts through graph-theoretic algorithms

Anzoom, Rashid; Nagi, Rakesh; Vogiatzis, Chrysafis

doi:10.1080/24725854.2022.2162169

Cited by 4 publications

(2 citation statements)

References 42 publications

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“…Understanding the structure of criminal enterprise activity, particularly linking different sectors of the supply chain in lawful and illegal activity, is critical to developing effective disruption strategies [e.g (Duxbury and Haynie, 2018;Keskin et al, 2022;Anzoom et al, 2023;Hilend et al, 2023)]. Not all actors associated with an illicit supply chain are engaged in illegal behavior, nor are all segments in the chain equality compromised, thus, efforts to identify subgroups with the aim of disrupting criminal interference seek to uncover interactions among actors that directly support or involve illegal activity.…”

Section: Identifying Iuu Communitiesmentioning

confidence: 99%

“…While community detection is an important descriptive exercise that is well suited for exploring criminal enterprise (Morselli et al, 2007;Bichler et al, 2013;Anzoom et al, 2023), not all subgroup community detection algorithms are suitable for exploring specific segments of a supply chain. First, prior research used algorithms premised on the idea that the entire network is under investigation, and that distinct subgroups will have greater within-group connectivity than between-group connectivity based on density.…”

Section: Study Objectivementioning

confidence: 99%

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Detecting communities at high-risk of IUU fishing: networks of shadow encounters in Area 81 of the Western Central Pacific

Bichler,

Petrossian,

Viramontes

et al. 2024

Front. Mar. Sci.

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IntroductionIllegal, unreported, and unregulated (IUU) fishing is a serious environmental crime with severe economic, social, and security implications. Efforts to monitor IUU fishing could be enhanced by using patterns of at-sea transshipment of fish to detect illicit subgroups.MethodsUsing data from Global Fishing Watch, this study investigates repeat transshipment events among vessels observed to operate in the U.N. FAO Area 81 during 2015-2021. Ship-to-ship transfer networks mapping potential encounters among 30 refrigerated cargo vessels (carriers) and 613 fishing vessels exhibit distinct communities that extend beyond this region.ResultsHighly central, carriers associated with open registries (flags of convenience) and exhibiting high operational deficiencies form networks that shadow the activities of national fleets.DiscussionObserved between group linkages among vessels draw attention to these parallel trade currents embedding regional activity into the larger fishing industry, providing a focus for monitoring and conservation efforts.

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Section: Identifying Iuu Communitiesmentioning

confidence: 99%

Section: Study Objectivementioning

confidence: 99%

Detecting communities at high-risk of IUU fishing: networks of shadow encounters in Area 81 of the Western Central Pacific

Bichler,

Petrossian,

Viramontes

et al. 2024

Front. Mar. Sci.

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A survey on optimization studies of group centrality metrics

Camur,

Vogiatzis

2024

Networks

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Centrality metrics have become a popular concept in network science and optimization. Over the years, centrality has been used to assign importance and identify influential elements in various settings, including transportation, infrastructure, biological, and social networks, among others. That said, most of the literature has focused on nodal versions of centrality. Recently, group counterparts of centrality have started attracting scientific and practitioner interest. The identification of sets of nodes that are influential within a network is becoming increasingly more important. This is even more pronounced when these sets of nodes are required to induce a certain motif or structure. In this study, we review group centrality metrics from an operations research and optimization perspective for the first time. This is particularly interesting due to the rapid evolution and development of this area in the operations research community over the last decade. We first present a historical overview of how we have reached this point in the study of group centrality. We then discuss the different structures and motifs that appear prominently in the literature, alongside the techniques and methodologies that are popular. We finally present possible avenues and directions for future work, mainly in three areas: (i) probabilistic metrics to account for randomness along with stochastic optimization techniques; (ii) structures and relaxations that have not been yet studied; and (iii) new emerging applications that can take advantage of group centrality. Our survey offers a concise review of group centrality and its intersection with network analysis and optimization.

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