Attack detection on multi-architecture Internet of Vehicles honeypots and response mechanism research

Intelligent connected vehicles (ICVs) refer to a new vehicle type that utilizes advanced information and communication technology to enable information exchange among vehicles, between vehicles and roads, and between vehicles and the internet. Malicious actors may exploit vulnerabilities in ICVs to gain malicious control, steal data, or launch denial-of-service attacks, resulting in significant economic losses and personal harm. Therefore, it is crucial to research attack detection and response mechanisms for ICVs and build effective network defense systems to ensure the safe operation of these vehicles. However, different manufacturers may adopt different architectures, posing significant challenges to network security defense for these vehicles. To address this issue, this paper proposes an attack detection and response mechanism based on Docker container technology for Multi-Architecture Vehicle Honeypots (MAV-honeypots). The aim is to simulate ICVs under various architectures using honeypot technology, attracting and inducing attackers to carry out attacks, thus achieving identification, analysis, and response to attackers.

Authors

Institutions

Publication Details

Published
2024-12-22
DOI
https://doi.org/10.1145/3712335.3712375
Primary Topic
Network Security and Intrusion Detection
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Attack detection on multi-architecture Internet of Vehicles honeypots and response mechanism research

Shihao Xue, Yuqiao Ning, Quanrui Huo, Shiyu Mu
Network Security and Intrusion Detection
article

Attack detection on multi-architecture Internet of Vehicles honeypots and response mechanism research

Shihao Xue, Yuqiao Ning, Quanrui Huo, Shiyu Mu
article en

Abstract

Intelligent connected vehicles (ICVs) refer to a new vehicle type that utilizes advanced information and communication technology to enable information exchange among vehicles, between vehicles and roads, and between vehicles and the internet. Malicious actors may exploit vulnerabilities in ICVs to gain malicious control, steal data, or launch denial-of-service attacks, resulting in significant economic losses and personal harm. Therefore, it is crucial to research attack detection and response mechanisms for ICVs and build effective network defense systems to ensure the safe operation of these vehicles. However, different manufacturers may adopt different architectures, posing significant challenges to network security defense for these vehicles. To address this issue, this paper proposes an attack detection and response mechanism based on Docker container technology for Multi-Architecture Vehicle Honeypots (MAV-honeypots). The aim is to simulate ICVs under various architectures using honeypot technology, attracting and inducing attackers to carry out attacks, thus achieving identification, analysis, and response to attackers.

China Automotive Technology and Research Center (CN)
Openalex Percentile: Top 68%
Network Security and Intrusion Detection
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.

Attack detection on multi-architecture Internet of Vehicles honeypots and response mechanism research — Shihao Xue, Yuqiao Ning, et al. · (2024) | TGRS Research Map | TGRS