An increasing amount of processes are becoming automated for increased efficiency and safety. Common examples are in automotive, industrial control systems or healthcare. Automation usually relies on a network of sensors to provide key data to control systems. One potential risk to these automated processes comes from fraudulent data injected in the network by malicious actors. In this article we propose a new mechanism of data tampering detection that does not depend on secret cryptographic keys - that can be lost or stolen - or accurate modelling of the network as is the case with existing machine learning based techniques. We define and analyse the mathematical structure of the proposed technique called ABBA and propose an algorithm for implementation.
翻译:为了提高效率和安全性,越来越多的程序正在自动化,常见的例子有汽车、工业控制系统或保健;自动化通常依靠传感器网络为控制系统提供关键数据;这些自动化程序的一个潜在风险来自恶意行为者向网络注入的欺诈性数据;在本条中,我们提议建立一个新的数据篡改探测机制,该机制不依赖于可能丢失或被盗的秘密加密钥匙,也不依赖于网络的精确建模,如现有机器学习技术那样。我们界定和分析了拟议的称为ABBA的技术的数学结构,并提出了实施算法。