DAGA: Detecting Attacks to In-Vehicle Networks via N-Gram Analysis
Author:
Affiliation:
1. Department of Engineering “Enzo Ferrari”, University of Modena, Reggio Emilia, Modena, Italy
2. Department of Physics, Informatics, Mathematics, University of Modena, Reggio Emilia, Modena, Italy
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Computer Networks and Communications,Aerospace Engineering,Automotive Engineering
Link
http://xplorestaging.ieee.org/ielx7/25/9950228/09829329.pdf?arnumber=9829329
Reference60 articles.
1. n-Gram Statistics for Natural Language Understanding and Text Processing
2. A Lightweight Intrusion Detection System for CAN Protocol Using Neighborhood Similarity
3. LibreCAN
4. READ: Reverse Engineering of Automotive Data Frames
5. Modeling inter-signal arrival times for accurate detection of CAN bus signal injection attacks
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