Physical-Layer Cyberattack and Interference Resilient Automotive Radars

In this paper, we present a physical-layer attack and interference resilient automotive radar system, and derive analytical upper bounds for the probability of not detecting an attack, and the probability of false attack alarm. We consider a quite general attack model and prove that if the attack si...

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Main Author: Onur Toker
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9274416/
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spelling doaj-da0bacb68e6d4ec5bf49237aa039bf792021-03-30T04:02:52ZengIEEEIEEE Access2169-35362020-01-01821553121554310.1109/ACCESS.2020.30416219274416Physical-Layer Cyberattack and Interference Resilient Automotive RadarsOnur Toker0https://orcid.org/0000-0003-2580-5449Department of Electrical and Computer Engineering, Florida Polytechnic University, Lakeland, FL, USAIn this paper, we present a physical-layer attack and interference resilient automotive radar system, and derive analytical upper bounds for the probability of not detecting an attack, and the probability of false attack alarm. We consider a quite general attack model and prove that if the attack signal level is above a defined relative threshold, both the probability of false attack alarm and the probability of not detecting an attack converge to zero exponentially with the number of samples acquired during a single chirp, and the number of chirps used in a frame. We also derive an analytical formula for this relative threshold, and prove that by selecting shorter frame durations, and using lower noise RF equipment, the threshold can be made as small as possible. Basically, by proper selection of radar parameters arbitrarily small attack signals can be detected almost always with almost no false alarms. We also present a numerical example using real measured data obtained from two 77 GHz automotive radars operated at the same time. Also using real data, we show that the proposed system reduces the negative effects of undetected weak attacks which are below the above mentioned threshold.https://ieeexplore.ieee.org/document/9274416/Automotive radarsattack resiliencecybersecurityinterference resiliencephysical-layer attacks
collection DOAJ
language English
format Article
sources DOAJ
author Onur Toker
spellingShingle Onur Toker
Physical-Layer Cyberattack and Interference Resilient Automotive Radars
IEEE Access
Automotive radars
attack resilience
cybersecurity
interference resilience
physical-layer attacks
author_facet Onur Toker
author_sort Onur Toker
title Physical-Layer Cyberattack and Interference Resilient Automotive Radars
title_short Physical-Layer Cyberattack and Interference Resilient Automotive Radars
title_full Physical-Layer Cyberattack and Interference Resilient Automotive Radars
title_fullStr Physical-Layer Cyberattack and Interference Resilient Automotive Radars
title_full_unstemmed Physical-Layer Cyberattack and Interference Resilient Automotive Radars
title_sort physical-layer cyberattack and interference resilient automotive radars
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2020-01-01
description In this paper, we present a physical-layer attack and interference resilient automotive radar system, and derive analytical upper bounds for the probability of not detecting an attack, and the probability of false attack alarm. We consider a quite general attack model and prove that if the attack signal level is above a defined relative threshold, both the probability of false attack alarm and the probability of not detecting an attack converge to zero exponentially with the number of samples acquired during a single chirp, and the number of chirps used in a frame. We also derive an analytical formula for this relative threshold, and prove that by selecting shorter frame durations, and using lower noise RF equipment, the threshold can be made as small as possible. Basically, by proper selection of radar parameters arbitrarily small attack signals can be detected almost always with almost no false alarms. We also present a numerical example using real measured data obtained from two 77 GHz automotive radars operated at the same time. Also using real data, we show that the proposed system reduces the negative effects of undetected weak attacks which are below the above mentioned threshold.
topic Automotive radars
attack resilience
cybersecurity
interference resilience
physical-layer attacks
url https://ieeexplore.ieee.org/document/9274416/
work_keys_str_mv AT onurtoker physicallayercyberattackandinterferenceresilientautomotiveradars
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