1 Introduction
Intelligent Connected Vehicle (ICV) is a new generation of vehicle which is equipped with advanced in-vehicle sensors, controllers, actuators and other devices, and integrates modern communication and network technology to realize intelligent information exchange and sharing between vehicles and X (people, cars, roads, backgrounds, etc.) [1]. The Chinese government said it is paying great attention to the development of intelligent connected vehicles and considers the sector a vital way to ease the burden on transportation, energy consumption and environmental pollution [2]. By 2020, the market scale of the country’s intelligent connected vehicles sector is expected to exceed 100 billion yuan [3]. However, these rapid changes to enhance the intelligent and connected functions of vehicles are having a serious effect on their security. Specifically, the Internet penetrates into the modern vehicles [4]. Increased connectivity often results in a heightened risk of a cybersecurity attack [5–7], such as Denial-of-Service (DoS) attack, man-in-the-middle attack and Structured Query Language (SQL) injection. In 2015, preeminent hackers Charlie Miller and Chris Valasek dominated headlines with their landmark hack of a Jeep Cherokee [8]. In 2016, team of hackers take remote control of Tesla Model S from 12 miles away [9]. In 2017, Keen Lab discovered new security vulnerabilities on Tesla motors and realized full attack chain to implement arbitrary CAN BUS and ECUs remote controls on Tesla motors with latest firmware [10]. In 2018, researchers hacked BMW cars and discovered 14 vulnerabilities [11].
Cars are getting more and more connected, which means more electronics plus access to the internet. Which, in turn, means more opportunities to hack cars remotely. For the security, generally speaking, the measures of protection against malicious attacks are little known to automotive manufacturers and suppliers. Modern cars need to be developed with security in mind, and that is something that has to be done by security professionals, whereas the Original Equipment Manufacturers (OEMs) lack the ability to comprehensively evaluate the security levels of their cars. Automotive information security can be guaranteed in many ways, such as security standards, regulations and test evaluation methods or public announcement system. As one of the most direct and effective means, the test evaluation method could provide a security process framework and guidance to help OEMs identify and assess security threats and design security into cyber-physical vehicle systems throughout the entire development lifecycle process. However, due to the lack of relevant standards, there are relatively few test evaluation methods for automotive information security in the industry, while most of these methods focus on testing the safety of cars [12, 13].
In this paper, a novel Intelligent Connected Vehicle Attack and Defense (ICV-ISAD) test evaluation method is proposed to address the test evaluation issue of automotive security. The article is structured as follows: in the following Sect. 2 it studies the problem and object statement under investigation from the two aspects of ICV’s classic system architecture and the main attack surfaces it faces. In Sect. 3 we introduce the test methodology of ICV-ISAD test method from three stages. In Sect. 4 there are some experimental results and analyses for ICV-ISAD test method. After the overall outlook for above, the last section concludes this article with a summary.
2 Problem and Object Statement Under Investigation
While automobile manufacturers have improved the intelligent and connected functions of their automobiles a lot during the past decades, adequate protection measures for vehicle security are not available yet [14]. Moreover, vehicle security related incidents can also affect the safety of automotive systems [15]. All of this interplay between intelligent and security clearly motivates automotive security as a research topic with increasing relevance and importance. Also, it motivates us to explore a test method to evaluate automotive security.
![../images/485150_1_En_15_Chapter/485150_1_En_15_Fig1_HTML.png](../images/485150_1_En_15_Chapter/485150_1_En_15_Fig1_HTML.png)
Intelligent connected vehicle classic system architecture
2.1 Classic System Architecture
![../images/485150_1_En_15_Chapter/485150_1_En_15_Fig2_HTML.png](../images/485150_1_En_15_Chapter/485150_1_En_15_Fig2_HTML.png)
Attack surfaces that ICV faces
2.2 Attack Surfaces
The intelligent connected vehicle has a complex system with many embedded Units. With many intelligent technologies being introduced into vehicle, the threats of malicious attack of automotive security are gradually increasing and the problems of information security are increasingly highlighted. It is not difficult to imagine that automobile manufacturers cannot come up with a strong security system for protecting vehicle networks unless they are very well aware of the attack surfaces that an automobile is facing and have a clear understanding of the existing vulnerabilities. Before helping them solve this puzzle, we first need to analyze the main threat surfaces ICV faces at present. Based on the ICV’s classic system architecture being presented in Fig. 1, in this section, there is an introduction of the attack surfaces threating ICV’s security. An illustration of these attack surfaces is shown in Fig. 2. The details of these seven attack surfaces are as follows.
Telematics Box (T-Box). Telematics Box is an electronic unit that integrates all kinds of chips, such as 3G/4G chip, wireless module, communication module, microcontroller (MCU), System on a Chip (SoC). It can be used to the interactive communication between the vehicle and the cloud-platform and connect with the cellular communication networks. In addition, some T-Boxs have the function of tracking with various satellite constellations (GPS, Galileo, GLONASS). As an important communication unit, T-Box’s security is critical for that of ICV. Therefore, hackers take it for granted that T-Box is one of the main breakthroughs used to compromise vehicles.
In-Vehicle Infotainment (IVI). In-Vehicle Infotainment is the centerpiece of the car’s sound and information system, which provides some direct user experience (UX) for car owners, such as music, applications, navigation. The IVI systems hack is possible and is a real concern [16]. The system is responsible for controlling some of the most vital functions of the car’s system. Specifically, IVI systems frequently utilize Bluetooth technology and/or smartphones to help drivers control the system with voice commands, touchscreen input, or physical controls, which exposes outside and provides a direct way to attack the vehicle.
Electronic Control Unit (ECU). During our research on attack surfaces for ICV, electronic control unit consists of all kinds of critical electronic units except T-Box and IVI, such as Central Computer (CEM), Engine Control Unit, Brake Control Module (BCM) and Remote Monitory System (RMS). All of these modules directly control the movement and behavior of the vehicle, and they can do harm to the vehicle once been attacked.
In-Vehicle Network (IVN). In-Vehicle Network is a general term for the internal network architecture of the car and mainly composed of various electronic modules and different types of buses, for example CAN bus, FlexRay, Ethernet, MOST and so on. All of the buses connects to ECU, T-Box and other critical components. IVN is the nerve center of the entire vehicle system and controls the normal operation of the car system. It is the last defensive line to protect the vehicle from being attacked.
Mobile Application (Mobile App). In this work, Mobile App is an automotive program or software application designed to run on a mobile device such as a phone/tablet, which can be used to control vehicle remotely. Besides, the source codes/files of app contain a great deal of privacy information and they can be reversed, recompiled or tempered. So its security plays a vital role in the field of automotive security.
Radio. In term of ICV information security, Radio refers to the technology of using radio waves to carry information in vehicle, such as sound and images, by systematically modulating properties of electromagnetic energy waves transmitted through space, such as their amplitude, frequency, stage, or pulse width. There are Wi-Fi, Bluetooth, Tire Pressure Monitoring System (TPMS), Remote Keyless Entry System (RKMS) and so on. For the security risks of radio, some hackers set up a radio listening station to find and decode hidden radio signals—just like the hackers who triggered the emergency siren system in Dallas, Texas, probably did [17].
Telematics Service Provider (TSP). In research about Telematics Service Provider’s security, it mainly serves as the cloud platform and some servers that are used to provide the services to the vehicles on the road, which plays a role in the connected car value chain centered on secure vehicle to cloud data management. Due to its close connection with the Internet, it has attracted the attention of many attackers and has become one of the most commonly used attack surface or path.
![../images/485150_1_En_15_Chapter/485150_1_En_15_Fig3_HTML.png](../images/485150_1_En_15_Chapter/485150_1_En_15_Fig3_HTML.png)
ICV-ISAD test method architecture
3 Test Methodology
Based on the ICV’s classic system architecture and seven attack surfaces it faces, in this section, a novel Intelligent Connected Vehicle (ICV) Information Security Attack and Defense (ICV-ISAD) test evaluation method is proposed and the design thoughts of test methodology are presented comprehensively. ICV-ISAD test method shows how to evaluate the information security of the car through testing method that aims to discover security vulnerabilities and threats as well as maps corresponding remediation measures. It is derived from the long-term large number of real automotive test experiments and is constantly optimized in the experiments. In this method, the implementation of the security evaluation realized from three stages, which are Threat and Risk Analysis, Test Execution as well as Remediation Measures.
3.1 Threat and Risk Analysis
Threats analysis
No. | Threat (Vulnerability) | Effect (Attack surface) |
---|---|---|
1 | Compromise of update procedures | IVI |
2 | Denial of service attacks | IVN, IVI, Mobile App |
3 | Unprivileged users access to vehicle systems | IVI, IVN |
4 | Hosted 3rd party software | IVI |
5 | Network design introduces vulnerabilities | IVN, T-Box, IVI, ECU |
6 | Physical manipulation of systems can enable an attack | IVI, T-Box |
7 | Spoofing of messages | IVN, IVI, Radio |
8 | Man in the middle attack | IVI, T-Box, Radio |
9 | OBD Diagnostic access | IVN, IVI |
10 | Unauthorized deletion/manipulation of system event logs | IVI, T-Box |
... | ... | ... |
Risks analysis
No. | Risk | Effect (Attack surface) |
---|---|---|
1 | Stealing personally identifiable information | IVI, T-Box, TSP |
2 | Manipulating a vehicle’s operation | IVN, IVI, Mobile App |
3 | Unauthorized vehicle system entry | IVN, IVI, T-Box |
4 | Compromise of over the air software update procedures | IVI |
5 | GPS spoofing | Radio |
6 | Disrupting TPMS signal | Radio |
7 | The installation package was tampered with | Mobile App |
8 | Transfer data is hijacked | Mobile App |
9 | Loss of information in the cloud | TSP |
10 | Information breach by unintended sharing of data | TSP |
... | ... | ... |
Test points
Attack surface | 1 | 2 | 3 | ... |
---|---|---|---|---|
IVN | Security access service | Subnet | Gateway | ... |
T-Box | Key usage | Hash function | SPI bus | ... |
IVI | Backdoor | Weak token | Port security | ... |
ECU | CAN bus isolation | Verification level | Secure storage | ... |
Mobile APP | Decompile | Process injection | Data security | ... |
Radio | Sniffing | Replay attack | Interference | ... |
TSP | CSRF vulnerability | Webshell getting | SQL injection | ... |
3.2 Testing Execution
In the second stage of ICV-ISAD test method, we will start the testing execution based on the threat and risk analysis. As we can see from the Fig. 3, the stage describes four layers, labeled 1 to 4. Layer 1 is the lowest layer in this stage.
Test cases
Surface | Test points | Test cases |
---|---|---|
IVN | Security access | 1 Connect the PC to the car through the OBD port |
2 Send 022701 via Vehicle Spy | ||
3 To test whether the ECU feeds back the seed or not | ||
4 Observe, analysis and record the results | ||
... | ... | ... |
T-Box | Key usage | 1 Confirm whether the encryption key is multi-purpose |
1 Confirm whether the authentication key is multi-purpose | ||
1 Confirm whether the random number generation key is multi-purpose | ||
1 Confirm if the digital signature key is multi-purpose | ||
... | ... | ... |
IVI | Backdoor | 1 To analyze whether the program has backdoor through the reverse engineering. Such as the hidden browser |
Port security | 1 Use nmap to find all open ports | |
2 Test whether the opened ports are secure or not | ||
... | ... | ... |
Test tools
No. | Tool name | Function description |
---|---|---|
1 | Burpsuite | Using to analyze network packets |
2 | jeb2 | Decompile apk application |
3 | Defensics | Fuzz testing by communication protocol |
4 | IDA-PRO | Decompile and dynamically debug binary file |
5 | Appscan | To discover vulnerabilities, hosts and services |
6 | Nmap | Test security of the ports and running services opened |
7 | Protecode | Analyze, detect and check the known vulnerabilities of binary codes |
... | ... | ... |
Test strategy for IVN’s security
Step | Description |
---|---|
1 | Analysis of vehicle network structure and bus type |
2 | Investigate the open bus service of the OBD interface |
3 | Call the corresponding test tools for different open services |
4 | Message reading and analysis |
5 | Diagnostic service test |
6 | Denial of service test |
7 | Brute force cracking test |
8 | Fuzz testing |
9 | Summary and analysis |
The Test and Evaluation (T&E) involves evaluating an automobile’s security from the component level to whole vehicle system as well as its integrated system. Components mainly refer to the units related to seven attack surfaces, such as IVI, T-Box and ECUs. Through black-box, gray-box and white-box testing, it analyzes the security of automotive systems (Fig. 1) to discover unknown vulnerabilities, threats and risks that the car faced based on the seven major attack surfaces (Fig. 2). In the overall execution process of Test and Evaluation Layer, it complies with test strategy and test procedure showed in the S&P Layer. Different test objects and different steps of the test will selectively call the corresponding test points, test tools and test cases in the Test Library Layer.
- 1
Use nmap to find all open ports.
- 2
Test whether the opened ports are secure or not.
![../images/485150_1_En_15_Chapter/485150_1_En_15_Fig4_HTML.png](../images/485150_1_En_15_Chapter/485150_1_En_15_Fig4_HTML.png)
Test procedure
In addition, as the number of the vehicle’s type and testing increases, the data of CAVD would be iterated and updated. Specifically, the vulnerabilities and threats found in the test are matched with that of the CAVD. For the existed vulnerabilities and threats in the library, the corresponding remediation measures or mitigations will be mapped and output from the CAVD. Otherwise for the unknown vulnerabilities and threats, some new protection schemes will be created and stored in the CAVD so as to map the corresponding vulnerabilities or threats next time.
3.3 Remediation Measures
![../images/485150_1_En_15_Chapter/485150_1_En_15_Fig5_HTML.png](../images/485150_1_En_15_Chapter/485150_1_En_15_Fig5_HTML.png)
The number of vulnerability for different car
4 Test Experimental Results
In our experiments, some different types of cars numbered 1 to 10 were selected to assess the performance of the proposed test evaluation method of ICV-ISAD. The vehicles participating in the experiment have intelligent and connected functions, which generally conform to the system framework shown in Fig. 1 and are faced with seven attack surfaces given in Fig. 2. The test experiment are aimed to evaluate the security of the whole vehicle and their components, such as IVI, T-Box, Mobile App, Radio and TSP, based on the black-box, gray-box and white-box testing.
4.1 Results and Analyses
![../images/485150_1_En_15_Chapter/485150_1_En_15_Fig6_HTML.png](../images/485150_1_En_15_Chapter/485150_1_En_15_Fig6_HTML.png)
The number of vulnerability in different severity level
![$$14.2 \% $$](../images/485150_1_En_15_Chapter/485150_1_En_15_Chapter_TeX_IEq1.png)
![$$ 30.2 \%$$](../images/485150_1_En_15_Chapter/485150_1_En_15_Chapter_TeX_IEq2.png)
![../images/485150_1_En_15_Chapter/485150_1_En_15_Fig7_HTML.png](../images/485150_1_En_15_Chapter/485150_1_En_15_Fig7_HTML.png)
Vulnerability severity for different vehicle units
4.2 Typical Vulnerabilities and Threats
In order to better illustrate the efficiency of the ICV-ISAD test method in automotive information security testing and evaluation experiments, we highlight several typical security issues found in the experiments as a result of ICV-ISAD test method, mainly introducing threats and vulnerabilities. Taking into account the privacy protection issues associated with the experimental results, we covered some sensitive information with mosaics.
![../images/485150_1_En_15_Chapter/485150_1_En_15_Fig8_HTML.png](../images/485150_1_En_15_Chapter/485150_1_En_15_Fig8_HTML.png)
SQL injection
To evaluate the security of key fobs by using ICV-ISAD test method, GQRX of test tools was called to detect the key frequency band of 315 MHz and 433 MHz at first. Then GNURADIO and USRP of test tools were called to capture and recorded the signal from the wireless key fob. Finally, the effect of the recorded signal was verified by a replay attack to test the security of wireless key fob. The results show that the replay attack is invalid for key fobs encrypted with rolling code, or else the replay attack can open the door and trunk. Specifically, the key fobs of No. 1 and No. 5 car have security risk for having no rolling codes, which can be replay attacked. During the evaluation of GPS security, we tried to cheat and temper the car localization by spoofing GPS signals using radio tools. The results show that it can be performed of GPS spoofing and tempered of the true automotive location if the car locate its position by GPS only, whereas it is difficult to do that in the condition of locating with Wi-Fi, 4G and GPS. In particular, the GPS of No. 1 and No. 3 car have the security risk of spoofing attack for positioning with GPS only.
SQL Injection. Based on the ICV-ISAD test method, when evaluating the TSP security of No. 4 car, we discovered a serious SQL injection vulnerability in one of the TSP’s URLs. Specifically, when we stitched the delay string after the one of the TSP’s URL, we found that the web page opened after the delay of 5 s, which indicated that its database have executed the spliced URL and it has time-based blind SQL injection. To further verify the vulnerability, we detected the address using sqlmap.py and found time-based blind SQL injection and union query SQL injection. Besides, a large amount of database information is exposed. As shown in Fig. 8.
![$$ID=350 $$](../images/485150_1_En_15_Chapter/485150_1_En_15_Chapter_TeX_IEq4.png)
![../images/485150_1_En_15_Chapter/485150_1_En_15_Fig9_HTML.png](../images/485150_1_En_15_Chapter/485150_1_En_15_Fig9_HTML.png)
Speed control ID
![../images/485150_1_En_15_Chapter/485150_1_En_15_Fig10_HTML.png](../images/485150_1_En_15_Chapter/485150_1_En_15_Fig10_HTML.png)
Speed control by accurate ID message
![../images/485150_1_En_15_Chapter/485150_1_En_15_Fig11_HTML.png](../images/485150_1_En_15_Chapter/485150_1_En_15_Fig11_HTML.png)
The cookie value returned
![../images/485150_1_En_15_Chapter/485150_1_En_15_Fig12_HTML.png](../images/485150_1_En_15_Chapter/485150_1_En_15_Fig12_HTML.png)
The exposure of user personal sensitive information
4.3 Remediation Measures
Remediation measures or recommendations
Vulnerability/Threat | Remediation measures & Recommendations |
---|---|
XSS vulnerability | 1 Set the value of httponly to true for vital cookie |
2 To convert character content to html entity by using the htmlspecialchars function | |
3 Filter or remove special html tags, such as | |
SQL injection | 1 Precompile and bind the variables of SQL statements with the function of PreparedStatement |
2 Front-end JS should have the ability to check for illegal characters | |
3 Filter the keywords reserved by the database in the SQL statement, such as AND, OR, EXEC | |
Gateway filtering | 1 OBD port shields each BUS and only reserves diagnostics function |
2 Add hardware Firewalls or other Encrypted Routes to enhance BUS filtering capabilities | |
Radio vulnerability | 1 Protect key fob from replayattack by using rollingcode |
2 Improve the strength of the wireless key fob’s signal encryption algorithm | |
3 Use 4G, Wi-Fi and GPS |
5 Conclusion
In this paper, we proposed a novel approach to address the security evaluation problem for ICV based on the attack and defense technology. The proposed ICV-ISAD test method not only helps OEMs secure the car through vulnerability discovery, but also provides the specific remediation measures or recommendations that can be implemented in the vehicle with security risks. Specifically, we explored the ICV’s classic system architecture which presents the main automotive units, system buses, and mutual communication relationship, as well as we discussed seven attack surfaces that ICV faces by and large. Based on the classic system architecture and the seven attack surfaces, ICV-ISAD test method has been elaborated from the three stages of threat and risk analysis, test execution, and remediation measures. Also, a special focus has been put to the stage of test execution, which includes the main components and core technologies of ICV-ISAD test method. Experimental results of 10 vehicles security tests show that ICV-ISAD test method can effectively discover security vulnerabilities and threats to evaluate vehicle’s security. In addition, some remediation measures or recommendations could be mapped from the CAVD of ICV-ISAD test method to mitigate the corresponding vulnerabilities.
Acknowledgments
The work described in this article has been supported by Automotive Data Center of China Automotive Technology and Research Center Co., Ltd. that provides the laboratory, all the cars, test tools and support required to carry out this research successfully.
The work in this article concerning CAVD has been supported by China Automotive Technology and Research Center Co., Ltd. through the project “Development of Automobile Information Security Vulnerability Database and Emergency Response Platform” under Contract No. 18190122.