利用最短路径发现犯罪群体
Using shortest path to discover criminal community
摘要：
使用现有的社区发现算法提取社区会产生难以分析的密集子网络。提取一个较小的样本，体现了嫌疑人名单的关系，是调查开始的一个重要部分。在本文中，我们提出了我们的最短路径网络搜索算法（SPNSA），开始与“算法饲料”，一个小的子集，特别感兴趣的节点，并建立一个调查子网络的功效。算法馈送可以包括已知的罪犯或嫌疑人，或有影响力的人。这使得我们的方法不同于现有的社区发现算法。我们将SPNSA应用于Enron电子邮件通信数据集，从与Enron崩溃有关的洗钱罪的人开始作为算法馈送。该算法产生稀疏和小的子网络，可以切实可行地确定一系列的人和关系，以进一步调查。相比之下，我们发现，使用社区发现算法或k-邻域方法确定感兴趣的子网络产生更大的规模和复杂性的子网络。当安然公司的18名高级管理人员被用作算法馈送时，所产生的子网络识别出4名被定罪的罪犯，他们不是管理人员，因此不是算法馈送的一部分。我们还通过从算法馈送中删除一个被定罪的罪犯并重新运行算法来直接测试SPNSA;在9种情况中，有5种情况下遗漏的罪犯发生在由此产生的子网络中。
英文摘要：
Extracting communities using existing community detection algorithms yields dense sub-networks that are difficult to analyse. Extracting a smaller sample that embodies the relationships of a list of suspects is an important part of the beginning of an investigation. In this paper, we present the efficacy of our shortest paths network search algorithm (SPNSA) that begins with an "algorithm feed", a small subset of nodes of particular interest, and builds an investigative sub-network. The algorithm feed may consist of known criminals or suspects, or persons of influence. This sets our approach apart from existing community detection algorithms. We apply the SPNSA on the Enron Dataset of e-mail communications starting with those convicted of money laundering in relation to the collapse of Enron as the algorithm feed. The algorithm produces sparse and small sub-networks that could feasibly identify a list of persons and relationships to be further investigated. In contrast, we show that identifying sub-networks of interest using either community detection algorithms or a k-Neighbourhood approach produces sub-networks of much larger size and complexity. When the 18 top managers of Enron were used as the algorithm feed, the resulting sub-network identified 4 convicted criminals that were not managers and so not part of the algorithm feed. We also directly tested the SPNSA by removing one of the convicted criminals from the algorithm feed and re-running the algorithm; in 5 out of 9 cases the left out criminal occurred in the resulting sub-network.
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