A Novel Intrusion Detection System for Next Generation In-Vehicle Networks

Zhouyan Deng, Yijie Xun, Jiajia Liu, Shouqing Li, Yilin Zhao

Research output: Contribution to journalConference articlepeer-review

3 Scopus citations

Abstract

As emerging technologies such as mobile communication, vehicle to everything, and artificial intelligence are widely used in intelligent connected vehicles, drivers can gain a convenient and colorful driving experience. While these tech-nologies enrich the driving experience, they also bring a series of vulnerable interfaces to the vehicle. These interfaces can be used by hackers to attack other nodes of in-vehicle network that lack authentication and encryption. For this, researchers design scheme to encrypt and authenticate messages to protect in-vehicle networks, but this scheme would occupy the bandwidth resources of in-vehicle network. Therefore, researchers propose parameter monitoring-based intrusion detection system (IDS), information theory-based IDS, and fingerprint-based IDS, which do not occupy bandwidth. However, most IDSs either cannot locate the source of the attack, cannot detect aperiodic frames, or need to know the non-public mapping between electronic control units (ECUs) and identifiers (IDs) of in-vehicle network. To solve these weaknesses, we propose a novel IDS that establishes voltage fingerprints for each ID. This system can detect period and aperiodic malicious frames and locate the source of attack without knowing the mapping between ECUs and IDs. The experimental results on actual vehicles demonstrate that our scheme is robust against real scenarios.

Original languageEnglish
Pages (from-to)2098-2103
Number of pages6
JournalProceedings - IEEE Global Communications Conference, GLOBECOM
DOIs
StatePublished - 2022
Event2022 IEEE Global Communications Conference, GLOBECOM 2022 - Rio de Janeiro, Brazil
Duration: 4 Dec 20228 Dec 2022

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