Security experimental framework of trajectory planning for autonomous vehicles

In the contemporary landscape, autonomous vehicles (AVs) have emerged as a prominent technological advancement globally. Despite their widespread adoption, significant hurdles remain, with security standing out as a critical concern. The potential for attacks within AV networks, exemplified by the T...

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Bibliographic Details
Published inInternational journal of intelligent networks Vol. 5; pp. 315 - 324
Main Authors Al-sheyab, Sujoud, Al-shara, Zakarea, Al-khaleel, Osama
Format Journal Article
LanguageEnglish
Published Elsevier B.V 2024
KeAi Communications Co., Ltd
Subjects
Autonomous vehicle
OSM
Routing
Simulation
SUMO
Trajectory attack
OSM
Routing
SUMO
Trajectory attack
Simulation
Autonomous vehicle
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Summary:In the contemporary landscape, autonomous vehicles (AVs) have emerged as a prominent technological advancement globally. Despite their widespread adoption, significant hurdles remain, with security standing out as a critical concern. The potential for attacks within AV networks, exemplified by the Trajectory Privacy Attack on Autonomous Driving (T-PAAD), underscores the urgency for robust security measures. Unfortunately, existing simulations for preemptively assessing the T-PAAD attack's impact are scarce. This paper introduces the Security Experimental Framework for Autonomous Vehicles (SEFAV), designed to address this gap by providing a versatile platform for simulating security scenarios in AV environments. SEFAV is cross-platform and compatible with different operating systems such as Windows and Linux, enhancing accessibility for researchers and practitioners. Our primary focus lies in showcasing the T-PAAD attack within our framework, highlighting its efficacy in evaluating and fortifying AV security.
ISSN:2666-6030
2666-6030
DOI:10.1016/j.ijin.2024.08.003