DocumentCode
86084
Title
Source Identification Using Signal Characteristics in Controller Area Networks
Author
Murvay, Pal-Stefan ; Groza, B.
Author_Institution
Fac. of Automatics & Comput., Politeh. Univ. of Timisoara, Timisoara, Romania
Volume
21
Issue
4
fYear
2014
fDate
Apr-14
Firstpage
395
Lastpage
399
Abstract
The CAN (Controller Area Network) bus, i.e., the de facto standard for connecting ECUs inside cars, is increasingly becoming exposed to some of the most sophisticated security threats. Due to its broadcast nature and ID oriented communication, each node is sightless in regards to the source of the received messages and assuring source identification is an uneasy challenge. While recent research has focused on devising security in CAN networks by the use of cryptography at the protocol layer, such solutions are not always an alternative due to increased communication and computational overheads, not to mention backward compatibility issues. In this work we set steps for a distinct approach, namely, we try to take authentication up to unique physical characteristics of the frames that are placed by each node on the bus. For this we analyze the frames by taking measurements of the voltage, filtering the signal and examining mean square errors and convolutions in order to uniquely identify each potential sender. Our experimental results show that distinguishing between certain nodes is clearly possible and by clever choices of transceivers and frame IDs each message can be precisely linked to its sender.
Keywords
controller area networks; convolution; cryptography; filtering theory; mean square error methods; transceivers; CAN networks; ID oriented communication; communication overhead; computational overhead; controller area networks; convolution; cryptography; mean square errors; protocol layer; security threats; signal filtering; source identification; transceivers; Authentication; Convolution; Cryptography; Physical layer; Transceivers; Vectors; CAN bus; physical fingerprinting; source identification;
fLanguage
English
Journal_Title
Signal Processing Letters, IEEE
Publisher
ieee
ISSN
1070-9908
Type
jour
DOI
10.1109/LSP.2014.2304139
Filename
6730667
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