基于机器学习的网络攻击下车辆队列零碰撞概率实现

2019 4th International Conference on System Reliability and Safety (ICSRS) Pub Date : 2019-11-01 DOI:10.1109/ICSRS48664.2019.8987644

M. Mongelli, Marco Muselli, Enrico Ferrari

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引用次数: 6

摘要

考虑到系统的可靠性，从人工智能模型中提取知识可能比其预测能力更重要。通过可理解分析发现的规则的详细阐述，可以深入了解车辆队列中的数据包伪造问题。

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Achieving Zero Collision Probability in Vehicle Platooning under Cyber Attacks via Machine Learning

In view of system reliability, extraction of knowledge from models of artificial intelligence may be more important than their forecasting ability. The elaboration of rules found by intelligible analytics gives here insight into the problem of packet falsification in vehicle platooning.

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来源期刊

2019 4th International Conference on System Reliability and Safety (ICSRS)

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