Security Analysis of Intelligent Transportation Systems Based on Simulation Data
Title | Security Analysis of Intelligent Transportation Systems Based on Simulation Data |
Publication Type | Conference Paper |
Year of Publication | 2018 |
Authors | Ming, Liang, Zhao, Gang, Huang, Minhuan, Kuang, Xiaohui, Li, Hu, Zhang, Ming |
Conference Name | 2018 1st International Conference on Data Intelligence and Security (ICDIS) |
Keywords | Analytical models, Buildings, composability, compositionality, Information security, Information systems, Intelligent Data and Security, Intelligent Data Security, intelligent transportation systems, ITS, ITS system, layered network security model, malicious node threat, Metrics, Networked Control Systems Security, pubcrawl, resilience, Resiliency, road safety, road traffic, roadside infrastructure units, Scalability, security, security analysis, security model, security of data, threat model, Traffic Control, traffic engineering computing, Transportation, transportation efficiency, transportation security, vehicle ad hoc networks, Veins |
Abstract | Modern vehicles in Intelligent Transportation Systems (ITS) can communicate with each other as well as roadside infrastructure units (RSUs) in order to increase transportation efficiency and road safety. For example, there are techniques to alert drivers in advance about traffic incidents and to help them avoid congestion. Threats to these systems, on the other hand, can limit the benefits of these technologies. Securing ITS itself is an important concern in ITS design and implementation. In this paper, we provide a security model of ITS which extends the classic layered network security model with transportation security and information security, and gives a reference for designing ITS architectures. Based on this security model, we also present a classification of ITS threats for defense. Finally a proof-of-concept example with malicious nodes in an ITS system is also given to demonstrate the impact of attacks. We analyzed the threat of malicious nodes and their effects to commuters, like increasing toll fees, travel distances, and travel times etc. Experimental results from simulations based on Veins shows the threats will bring about 43.40% more total toll fees, 39.45% longer travel distances, and 63.10% more travel times. |
DOI | 10.1109/ICDIS.2018.00037 |
Citation Key | ming_security_2018 |
- threat model
- resilience
- road safety
- road traffic
- roadside infrastructure units
- security
- Security analysis
- security model
- security of data
- pubcrawl
- traffic control
- traffic engineering computing
- Transportation
- transportation efficiency
- transportation security
- vehicle ad hoc networks
- Veins
- Information systems
- Intelligent Data Security
- Compositionality
- Resiliency
- Scalability
- Analytical models
- Buildings
- composability
- information security
- Intelligent Data and Security
- Intelligent Transportation Systems
- ITS
- ITS system
- layered network security model
- malicious node threat
- Metrics
- Networked Control Systems Security