Kavli Affiliate: Feng Wang
| First 5 Authors: Feng Wang, Yaron Koral, Kenichi Futamura, ,
| Summary:
The cybersecurity of connected cars, integral to the broader Internet of
Things (IoT) landscape, has become of paramount concern. Cyber-attacks,
including hijacking and spoofing, pose significant threats to these
technological advancements, potentially leading to unauthorized control over
vehicular networks or creating deceptive identities. Given the difficulty of
deploying comprehensive defensive logic across all vehicles, this paper
presents a novel approach for identifying potential attacks through Radio
Access Network (RAN) event monitoring. The major contribution of this paper is
a location anomaly detection module that identifies aberrant devices that
appear in multiple locations simultaneously – a potential indicator of a
hijacking attack. We demonstrate how RAN-event based location anomaly detection
is effective in combating malicious activity targeting connected cars. Using
RAN data generated by tens of millions of connected cars, we developed a fast
and efficient method for identifying potential malicious or rogue devices. The
implications of this research are far-reaching. By increasing the security of
connected cars, we can enhance the safety of users, provide robust defenses for
the automotive industry, and improve overall cybersecurity practices for IoT
devices.
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