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Detecting unmanaged and unauthorized devices on the network with long short-term memory network

机译:在具有长短期内存网络的网络上检测不受管和未经授权的设备

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Unmanaged and unauthorized devices present in a corporate network pose potential security risk. Gaining insights into these devices starts with their identification. However, there have been few studies that recognize these devices among tens to hundreds of thousands of devices typically present on a large corporate network. On the other hand, names of the unmanaged and unauthorized devices are telling, as they do not necessarily conform to the existing known and unknown naming conventions followed by the majority of machines managed by a corporation. This work examines the lexical content of networked device names to flag devices with unusual names that are worth noting. We show how a long short-term memory (LSTM) network learns from the device names to flag the anomalously named devices. We demonstrate how the method offers a practical solution to detect unmanaged and unauthorized devices in real-world corporate networks.
机译:公司网络中存在的不受管和未经授权的设备会带来潜在的安全风险。深入了解这些设备始于其识别。但是,很少有研究能够识别大型企业网络中通常存在的数以万计的设备中的这些设备。另一方面,非托管设备和未授权设备的名称在告诉,因为它们不一定符合现有的已知命名和未知命名约定,后跟公司管理的大多数计算机。这项工作检查了网络设备名称的词法内容,以标记带有值得注意的不寻常名称的设备。我们展示了一个长期的短期记忆(LSTM)网络如何从设备名称中学习来标记异常命名的设备。我们将演示该方法如何提供一种实用的解决方案,以检测实际公司网络中的非托管和未授权设备。

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