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Data Relation Analysis Focusing on Plural Data Transition for Detecting Attacks on Vehicular Network

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Advances in Networked-based Information Systems (NBiS - 2019 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1036))

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Abstract

On the Controller Area Network (CAN), there are three types of messages, namely periodic messages, event based periodic messages, and non-periodic messages. On the attack detection, there are many high accuracy methods for the periodic messages. For the event based periodic messages and the non-periodic messages, detection methods utilizing the relation of plural data in some messages are effective. In such methods, the relations between plural data are investigated from some messages that were collected beforehand. And, obtained relation information is used as attributes of statistic detection. In this paper, a new attack detection method utilizing the number of occurrences of specific values and changes of values in messages is proposed. And the derivation algorithm that derives relation information efficiently is also proposed. By using the derivation algorithm, we found 582 relations for the detection method.

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Correspondence to Jun Yajima .

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Yajima, J., Hasebe, T., Okubo, T. (2020). Data Relation Analysis Focusing on Plural Data Transition for Detecting Attacks on Vehicular Network. In: Barolli, L., Nishino, H., Enokido, T., Takizawa, M. (eds) Advances in Networked-based Information Systems. NBiS - 2019 2019. Advances in Intelligent Systems and Computing, vol 1036. Springer, Cham. https://doi.org/10.1007/978-3-030-29029-0_25

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