Security Challenges and Mitigation Strategies for CAN-Based Protocols: A Comprehensive Survey

The Controller Area Network (CAN) protocol is the backbone of many critical communication systems in automotive, industrial, and embedded applications. Despite its widespread adoption, CAN-based protocols, such as J1939, CANopen, NMEA 2000, and others, face inherent security vulnerabilities due to their lack of robust authentication and encryption mechanisms. This research examines the security challenges associated with CAN and its derivative protocols, focusing on potential exploits such as message spoofing, eavesdropping, denial-of-service (DoS) attacks, and unauthorized data access. Unlike previous studies, this work comprehensively reviews defense strategies, techniques, and countermeasures across multiple CAN-based protocols, aiming to identify all possible security solutions in a unified analysis. In addition, it evaluates current industry solutions, including encryption overlays, intrusion detection systems (IDS), and protocol enhancements, while considering trade-offs between security and performance metrics, such as network traffic load, latency, and scalability. By analyzing existing approaches, this research identifies gaps in current implementations and explores innovative strategies to enhance security while maintaining network efficiency. The findings contribute to developing more resilient communication frameworks in CAN networks.

Authors

Institutions

Publication Details

Published
2025-03-19
DOI
https://doi.org/10.1109/infoteh64129.2025.10959305
Citations
1
Primary Topic
Vehicular Ad Hoc Networks (VANETs)
Type
article
Field-Weighted Citation Impact
0.73
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Security Challenges and Mitigation Strategies for CAN-Based Protocols: A Comprehensive Survey

Srdjan Popic, Bojan Ramic, Sasa Bojanic
1 citations
Vehicular Ad Hoc Networks (VANETs)
0.73
article

Security Challenges and Mitigation Strategies for CAN-Based Protocols: A Comprehensive Survey

Srdjan Popic, Bojan Ramic, Sasa Bojanic
article en
1 citations

Abstract

The Controller Area Network (CAN) protocol is the backbone of many critical communication systems in automotive, industrial, and embedded applications. Despite its widespread adoption, CAN-based protocols, such as J1939, CANopen, NMEA 2000, and others, face inherent security vulnerabilities due to their lack of robust authentication and encryption mechanisms. This research examines the security challenges associated with CAN and its derivative protocols, focusing on potential exploits such as message spoofing, eavesdropping, denial-of-service (DoS) attacks, and unauthorized data access. Unlike previous studies, this work comprehensively reviews defense strategies, techniques, and countermeasures across multiple CAN-based protocols, aiming to identify all possible security solutions in a unified analysis. In addition, it evaluates current industry solutions, including encryption overlays, intrusion detection systems (IDS), and protocol enhancements, while considering trade-offs between security and performance metrics, such as network traffic load, latency, and scalability. By analyzing existing approaches, this research identifies gaps in current implementations and explores innovative strategies to enhance security while maintaining network efficiency. The findings contribute to developing more resilient communication frameworks in CAN networks.

RT-RK Institute for Computer Based Systems (Serbia) (RS)
Climate action
Openalex Percentile: Top 30%
Vehicular Ad Hoc Networks (VANETs)
0.73
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.