Cryptographic and Intrusion Detection System for automotive CAN bus: Survey and contributions

被引：0

作者：

Gmiden, Mabrouka ^{[1
]}

Gmiden, Mohamed Hedi ^{[1
]}

Trabelsi, Hafedh ^{[1
]}

机构：

[1] Sch Sfax, Natl Engineers, Comp & Embedded Syst Lab CES, Sfax, Tunisia

来源：

2019 16TH INTERNATIONAL MULTI-CONFERENCE ON SYSTEMS, SIGNALS & DEVICES (SSD) | 2019年

关键词：

In-vehicle Network; CAN bus security; IDS; Cryptography;

D O I：

10.1109/ssd.2019.8893165

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Controller Area Network (CAN) is today the most used protocol in automotive networks. However, CAN bus cannot guarantee the safety of vehicles against cybernetic attacks. Moreover, external connectivity is the most important trends of modern cars. However, hackers can exploit automotive network vulnerabilities to make attacks. Therefore, to protect in-vehicle systems from external attacks, numerous researches proposed security mechanisms based on cryptography and intrusion detection system (IDS). In this paper, we give a survey on the various security approaches which are designed to solve CAN bus security. Along with that, we introduce our contributions o deal with this problem.

引用

页码：158 / 163

页数：6

共 50 条

[31] Windowed Hamming Distance-Based Intrusion Detection for the CAN Bus
Fang, Siwei
Zhang, Guiqi
Li, Yufeng
Li, Jiangtao
APPLIED SCIENCES-BASEL, 2024, 14 (07):
[32] An Effective In-Vehicle CAN Bus Intrusion Detection System Using CNN Deep Learning Approach
Hossain, Md Delwar
Inoue, Hiroyuki
Ochiai, Hideya
Fall, Doudou
Kadobayashi, Youki
2020 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM), 2020,
[33] Intrusion Detection System for In-Vehicle CAN-FD Bus ID Based on GAN Model
Wang, Xu
Xu, Yihu
Xu, Yinan
Wang, Ziyi
Wu, Yujing
IEEE ACCESS, 2024, 12 : 82402 - 82412
[34] Multiple Observation HMM-Based CAN Bus Intrusion Detection System for In-Vehicle Network
Dong, Chen
Wu, Hao
Li, Qingyuan
IEEE ACCESS, 2023, 11 : 35639 - 35648
[35] Intrusion Detection System CAN-Bus In-Vehicle Networks Based on the Statistical Characteristics of Attacks
Khan, Junaid
Lim, Dae-Woon
Kim, Young-Sik
SENSORS, 2023, 23 (07)
[36] A survey of deep learning-based intrusion detection in automotive applications
Lampe, Brooke
Meng, Weizhi
EXPERT SYSTEMS WITH APPLICATIONS, 2023, 221
[37] can-sleuth: Investigating and Evaluating Automotive Intrusion Detection Datasets
Kidmose, Brooke
Meng, Weizhi
PROCEEDINGS OF THE 2024 EUROPEAN INTERDISCIPLINARY CYBERSECURITY CONFERENCE, EICC 2024, 2024, : 19 - 28
[38] Exploring Highly Quantised Neural Networks for Intrusion Detection in Automotive CAN
Khandelwal, Shashwat
Shreejith, Shanker
2023 33RD INTERNATIONAL CONFERENCE ON FIELD-PROGRAMMABLE LOGIC AND APPLICATIONS, FPL, 2023, : 235 - 241
[39] Embedded Vision based Automotive Interior Intrusion Detection System
Cai, Haibin
Lee, Donghee
Hwang, Joonkoo
Fang, Yinfeng
Li, Song
Liu, Honghai
2017 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC), 2017, : 2909 - 2914
[40] Research of Automotive Controller Area Network Bus Detection System
Cui Hongwei
NANOTECHNOLOGY AND PRECISION ENGINEERING, PTS 1 AND 2, 2013, 662 : 736 - 739

← 1 2 3 4 5 →