从外部看内部:利用网络流量分析检测假冒设备

Trey Reece;Supreeth Sathyanarayana;William H. Robinson;Raheem A. Beyah
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引用次数: 0

摘要

为了对抗日益增长的假冒组件威胁,本文描述了一种基于组件发送和处理ICMP、UDP和TCP网络数据包的方式对组件进行指纹识别的技术。然后通过人工神经网络对这些网络指纹进行处理,以便对各个处理器进行分类和分类。这些测试发现ICMP和UDP数据包为识别网络中的假冒组件提供了一种有效、廉价、快速的工具。
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On The Outside Looking In: Towards Detecting Counterfeit Devices Using Network Traffic Analysis
In order to combat the growing threat of counterfeit components, this paper describes a technique to fingerprint and identify components based upon the way in which they send and process ICMP, UDP, and TCP network packets. These network fingerprints are then processed by an artificial neural network in order to categorize and classify individual processors. These tests found that ICMP and UDP packets provided an an effective, inexpensive, and fast tool for identifying counterfeit components in a network.
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