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Defending Connected Vehicles Against Malware: Challenges and a Solution Framework

Zhang, Tao, Antunes, Helder, Aggarwal, Siddhartha·2014·IEEE Internet of Things Journal

Abstract

Vehicles face growing security threats as they become increasingly connected with the external world. Hackers, researchers, and car hobbyists have compromised security keys used by the electronic control units (ECUs) on vehicles, modified ECU software, and hacked wireless transmissions from vehicle key fobs and tire monitoring sensors, using low-cost commercially available tools. However, the most damaging security threats to vehicles are only emerging. One such threat is malware, which can infect vehicles in a variety of ways and cause severe consequences. Defending vehicles against malware attacks must address many unique challenges that have not been well addressed in other types of networks. This paper identifies those vehicle-specific challenges, discusses existing solutions and their limitations, and presents a cloud-assisted vehicle malware defense framework that can address these challenges.

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Metadata

Authors
Zhang, T., Antunes, H., & Aggarwal, S.
Venue
IEEE Internet of Things Journal
Published
2014-02
Volume
1
Issue
1
Pages
10-21
ISSN
2327-4662 (ISSN-L)
OpenAlex
W2070268576
Cited by
186
References
0
FWCI
11.22
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Defending Connected Vehicles Against Malware: Challenges and a Solution Framework. https://app.cochat.ai/papers/10.1109/jiot.2014.2302386
The paper
Zhang, T., Antunes, H., & Aggarwal, S. (2014). Defending Connected Vehicles Against Malware: Challenges and a Solution Framework. IEEE Internet of Things Journal. https://doi.org/10.1109/jiot.2014.2302386

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.