{"title":"MetaCAN:一种基于优化自适应混合元启发式的CAN总线安全入侵检测系统","authors":"Kadir Ileri , Abdur Rakib , Soufiene Djahel","doi":"10.1016/j.vehcom.2025.100956","DOIUrl":null,"url":null,"abstract":"<div><div>The Controller Area Network (CAN) bus is a message-based protocol widely used in modern vehicles to facilitate communication between various Electronic Control Units (ECUs). However, its simplistic design lacks fundamental security measures, making it highly susceptible to cyberattacks. These vulnerabilities pose significant risks to vehicle safety, highlighting the critical need for implementation of effective intrusion detection systems (IDS). Therefore, in this paper, a machine learning based IDS optimized through an adaptive hybrid metaheuristic approach, named MetaCAN, is proposed to secure the CAN bus. MetaCAN leverages the complementary strengths of particle swarm optimization (PSO) for fast convergence and cuckoo search (CS) for robust global search to ensure effective hyperparameter tuning and model optimization. MetaCAN is evaluated using three real-world datasets including Survival Analysis, Car Hacking: Attack & Defense Challenge 2020, and OTIDS. Unlike traditional binary detection systems, MetaCAN offers multi-class attack detection by identifying five distinct attack types including Denial of Service (DoS), fuzzy, masquerade, malfunction, and replay attacks. Moreover, the detection accuracy of the system is enhanced through a feature engineering process that introduces two effective features such as Time Interval and ID Repetition Count. The experimental results show that MetaCAN consistently outperforms existing IDS solutions targeted the same datasets, making it a promising solution for securing the CAN bus in real-world vehicular environments.</div></div>","PeriodicalId":54346,"journal":{"name":"Vehicular Communications","volume":"55 ","pages":"Article 100956"},"PeriodicalIF":5.8000,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"MetaCAN: An optimized adaptive hybrid metaheuristic-based intrusion detection system for CAN bus security\",\"authors\":\"Kadir Ileri , Abdur Rakib , Soufiene Djahel\",\"doi\":\"10.1016/j.vehcom.2025.100956\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The Controller Area Network (CAN) bus is a message-based protocol widely used in modern vehicles to facilitate communication between various Electronic Control Units (ECUs). However, its simplistic design lacks fundamental security measures, making it highly susceptible to cyberattacks. These vulnerabilities pose significant risks to vehicle safety, highlighting the critical need for implementation of effective intrusion detection systems (IDS). Therefore, in this paper, a machine learning based IDS optimized through an adaptive hybrid metaheuristic approach, named MetaCAN, is proposed to secure the CAN bus. MetaCAN leverages the complementary strengths of particle swarm optimization (PSO) for fast convergence and cuckoo search (CS) for robust global search to ensure effective hyperparameter tuning and model optimization. MetaCAN is evaluated using three real-world datasets including Survival Analysis, Car Hacking: Attack & Defense Challenge 2020, and OTIDS. Unlike traditional binary detection systems, MetaCAN offers multi-class attack detection by identifying five distinct attack types including Denial of Service (DoS), fuzzy, masquerade, malfunction, and replay attacks. Moreover, the detection accuracy of the system is enhanced through a feature engineering process that introduces two effective features such as Time Interval and ID Repetition Count. The experimental results show that MetaCAN consistently outperforms existing IDS solutions targeted the same datasets, making it a promising solution for securing the CAN bus in real-world vehicular environments.</div></div>\",\"PeriodicalId\":54346,\"journal\":{\"name\":\"Vehicular Communications\",\"volume\":\"55 \",\"pages\":\"Article 100956\"},\"PeriodicalIF\":5.8000,\"publicationDate\":\"2025-07-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Vehicular Communications\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S221420962500083X\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"TELECOMMUNICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Vehicular Communications","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S221420962500083X","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"TELECOMMUNICATIONS","Score":null,"Total":0}
MetaCAN: An optimized adaptive hybrid metaheuristic-based intrusion detection system for CAN bus security
The Controller Area Network (CAN) bus is a message-based protocol widely used in modern vehicles to facilitate communication between various Electronic Control Units (ECUs). However, its simplistic design lacks fundamental security measures, making it highly susceptible to cyberattacks. These vulnerabilities pose significant risks to vehicle safety, highlighting the critical need for implementation of effective intrusion detection systems (IDS). Therefore, in this paper, a machine learning based IDS optimized through an adaptive hybrid metaheuristic approach, named MetaCAN, is proposed to secure the CAN bus. MetaCAN leverages the complementary strengths of particle swarm optimization (PSO) for fast convergence and cuckoo search (CS) for robust global search to ensure effective hyperparameter tuning and model optimization. MetaCAN is evaluated using three real-world datasets including Survival Analysis, Car Hacking: Attack & Defense Challenge 2020, and OTIDS. Unlike traditional binary detection systems, MetaCAN offers multi-class attack detection by identifying five distinct attack types including Denial of Service (DoS), fuzzy, masquerade, malfunction, and replay attacks. Moreover, the detection accuracy of the system is enhanced through a feature engineering process that introduces two effective features such as Time Interval and ID Repetition Count. The experimental results show that MetaCAN consistently outperforms existing IDS solutions targeted the same datasets, making it a promising solution for securing the CAN bus in real-world vehicular environments.
期刊介绍:
Vehicular communications is a growing area of communications between vehicles and including roadside communication infrastructure. Advances in wireless communications are making possible sharing of information through real time communications between vehicles and infrastructure. This has led to applications to increase safety of vehicles and communication between passengers and the Internet. Standardization efforts on vehicular communication are also underway to make vehicular transportation safer, greener and easier.
The aim of the journal is to publish high quality peer–reviewed papers in the area of vehicular communications. The scope encompasses all types of communications involving vehicles, including vehicle–to–vehicle and vehicle–to–infrastructure. The scope includes (but not limited to) the following topics related to vehicular communications:
Vehicle to vehicle and vehicle to infrastructure communications
Channel modelling, modulating and coding
Congestion Control and scalability issues
Protocol design, testing and verification
Routing in vehicular networks
Security issues and countermeasures
Deployment and field testing
Reducing energy consumption and enhancing safety of vehicles
Wireless in–car networks
Data collection and dissemination methods
Mobility and handover issues
Safety and driver assistance applications
UAV
Underwater communications
Autonomous cooperative driving
Social networks
Internet of vehicles
Standardization of protocols.