The threat status and criminal collaborations of potential terrorists are hidden but give rise to observable behaviours and communications. Terrorists, when acting in concert, need to communicate to organise their plots. The authorities utilise such observable behaviour and communication data to inform their investigations and policing. We present a dynamic latent network model that integrates real-time communications data with prior knowledge on individuals. This model estimates and predicts the latent strength of criminal collaboration between individuals to assist in the identification of potential cells and the measurement of their threat levels. We demonstrate how, by assuming certain plausible conditional independences across the measurements associated with this population, the network model can be combined with models of individual suspects to provide fast transparent algorithms to predict group attacks. The methods are illustrated using a simulated example involving the threat posed by a cell suspected of plotting an attack.

中文翻译：

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基于动态贝叶斯稳定演化的犯罪合作网络建模

潜在恐怖分子的威胁状态和犯罪合作是隐藏的，但会引起可观察的行为和通信。恐怖分子在协同行动时，需要通过沟通来组织他们的阴谋。当局利用这种可观察到的行为和通信数据为他们的调查和警务提供信息。我们提出了一个动态的潜在网络模型，该模型将实时通信数据与个人先验知识相结合。该模型估计和预测个人之间犯罪合作的潜在强度，以帮助识别潜在细胞并测量其威胁级别。我们展示了如何通过假设与该总体相关的测量具有某些似是而非的条件独立性，网络模型可以与个别嫌疑人的模型相结合，提供快速透明的算法来预测群体攻击。这些方法使用一个模拟示例来说明，该示例涉及一个被怀疑策划攻击的单元所构成的威胁。