Field Testing and Detection of Camera Interference for Autonomous Driving

• URL: http://arxiv.org/abs/2408.04524v1
• Date: Thu, 8 Aug 2024 15:24:19 GMT
• Title: Field Testing and Detection of Camera Interference for Autonomous Driving
• Authors: Ki Beom Park, Huy Kang Kim,
• Abstract summary: This study explores the detection of camera interference attacks (CIA) within an automotive ethernet-driven environment using a novel GRU-based IDS. Our IDS effectively analyzes packet length sequences to differentiate between normal and anomalous data transmissions.
• Score: 3.3148826359547514
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: In recent advancements in connected and autonomous vehicles (CAVs), automotive ethernet has emerged as a critical technology for in-vehicle networks (IVNs), superseding traditional protocols like the CAN due to its superior bandwidth and data transmission capabilities. This study explores the detection of camera interference attacks (CIA) within an automotive ethernet-driven environment using a novel GRU-based IDS. Leveraging a sliding-window data preprocessing technique, our IDS effectively analyzes packet length sequences to differentiate between normal and anomalous data transmissions. Experimental evaluations conducted on a commercial car equipped with H.264 encoding and fragmentation unit-A (FU-A) demonstrated high detection accuracy, achieving an AUC of 0.9982 and a true positive rate of 0.99 with a window size of 255.

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