DOCSLIB.ORG

Security Control Mechanism for Safety Critical Functions Operating on an Automotive Controller Area Network

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Security Control Mechanism for Safety Critical Functions Operating on an Automotive Controller Area Network Security Control Mechanism for Safety Critical Functions Operating on an Automotive Controller Area Network A Thesis Presented in Partial Fulfillment of the Requirements for the Degree Master of Science in the Graduate School of The Ohio State University By Matt Appel, Graduate Program in Electrical and Computer Engineering The Ohio State University 2020 Master's Examination Committee: Prof. Girogio Rizzoni, Advisor Prof. Ness Shroff Prof. Qadeer Ahmed c Copyright by Matt Appel 2020 Abstract Safety-critical systems in automotive design are facing new challenges associated with advancements in autonomous functionality and connectivity. One of those chal- lenges is security in these systems. There are a multitude of different problems with all of these additional connectivity and sensing units. The focus of this thesis is on the internal communication of Network Control Systems(NCS) of a vehicle. The Controller Area Network (CAN) is the primary network used in safety-critical vehi- cle operation and is lacking inherent security. This thesis presents a security control mechanism for CAN that uses vehicle models to detect and mitigate malicious mes- sages on CAN. The security control mechanism is an Intrusion Detection System (IDS) that uses an unknown input observer implementation to address stealth, re- play, and covert attacks. The goal of this method is to address performance challenges in the authentication of an entire CAN bus. It uses vehicle dynamic behavior to au- thenticate messages rather than using encryption methods to require CAN message authentication when the vehicle is not under attack reducing the burden caused by implementing and continually using secure communication protocols on top of CAN. A case study on a throttle control request of an engine by an Autonomous Vehicle Control Unit (AVCU) test and demonstrate the security control mechanisms. ii Dedicated to my family: mother Teresa Appel, father Andrew Appel, and brother Jason Appel for providing their support, their motivation, and their time to help me achieve my goals. iii Acknowledgments I would like to thank all of my colleagues at The Center for Automotive Research for there great support and all of the opportunities that they have provided. I want to also thank Dr. Qadeer Ahmed and Pradeep Oruganti for all the support over the past couple years. The creation and development CyberSecuirty@CAR Lab has been a challenging and rewarding task and I am thankful o have been apart of that team. I would also like to thank my parents and family for there continued support in getting me to this point. No matter what they have always been there for me and supported my dreams and goals. I will forever be grateful to everyone who has helped me throughout this process, without the proper opportunities, support and guidance none of this would have been possible. iv Vita February 17, 1995 . Born - Mayfield Heights, USA 2018 . .B.S. Electrical and Computer Engineer The Ohio State University 2018-present . .Graduate Research Associate, The Ohio State University: Center for Automotive Research Publications Appel, Matthew Andrew, and Qadeer Ahmed. Intelligent Vehicle Monitoring for Safety and Security. No. 2019-01-0129. SAE Technical Paper, 2019. Oruganti, Pradeep Sharma, Matt Appel, and Qadeer Ahmed. "Hardware-in-loop based Automotive Embedded Systems Cybersecurity Evaluation Testbed." In Pro- ceedings of the ACM Workshop on Automotive Cybersecurity, pp. 41-44. 2019. Fields of Study Major Field: Electrical and Computer Engineering v Table of Contents Page Abstract . ii Dedication . iii Acknowledgments . iv Vita......................................... v List of Tables . ix List of Figures . x 1. Introduction . 1 2. Background . 5 2.1 Introduction to Transportation Security . 5 2.1.1 Cyber Security Domain . 5 2.1.2 Threat Models . 7 2.1.3 Layered Security . 9 2.1.4 Security Assurance . 10 2.2 Automotive Security Review . 12 2.2.1 First Formal Projects out of the EU . 14 2.2.2 Penetration Testing . 15 2.2.3 Automotive Security Standards . 17 2.2.4 Security Recommendations . 19 2.2.5 Automotive Security Layers . 20 2.3 Security Layer Targeted in this Thesis . 22 vi 3. Intra-Vehicle Networks and Controller Area Network . 23 3.1 Vehicle Electrical and Electronic Architecture . 23 3.2 Controller Area Network . 26 3.2.1 CAN Security Challenges . 28 3.3 Related work in CAN Security . 32 3.3.1 CAN secure communication protocols . 33 3.3.2 Intrusion Detection Systems . 33 3.3.3 Cyber Physical System Security, Model-Based Methods . 38 3.4 Thesis Contribution and Gap Analysis . 38 4. Observer based CAN Intrusion Detection and Mitigation Mechanism . 40 4.1 CPS Attack Monitor Preliminaries . 40 4.1.1 CPS Attack Monitor . 41 4.1.2 Observability under Adversarial Attack . 45 4.1.3 Unknown Input Observer . 46 4.2 Attack Model . 48 4.2.1 CAN Attack Scenario Being Addressed . 48 4.2.2 Attacks on Observer-Based Security Mechanisms . 49 4.3 UIO based IDS algorithm for CAN . 51 4.3.1 NCS Graphical Analysis for CAN Tasks, Messages, and Re- sources . 51 4.3.2 Formulation of a Secure CAN Message . 54 4.3.3 Connecting CPS System Model to CAN Network Graph . 56 4.3.4 UIO based Dynamic Monitor for Attacks on CAN Sensor Messages . 58 4.3.5 Security Mechanism for Trust of Message under Sensor Attack 60 4.3.6 Security Mechanism for Control Input Under Attack . 62 4.3.7 Limitations . 62 5. Autonomous Vehicle Engine Throttle Control Case Study . 64 5.1 NCS Graph Analysis for Engine Throttle Control . 64 5.2 Engine . 66 5.2.1 Continuous Time Engine Model . 70 5.2.2 Bilinear Approximation Discretization State Space Model . 72 5.2.3 Zero Order Hold State Space Model . 73 5.2.4 ZOH Engine Model Structure Graph and Attack Set . 74 5.3 UIO Construction for AV Engine Control Security Mechanism . 76 5.4 IDS and Mitigation Security Mechanism . 77 vii 5.4.1 Pressure Sensor Attack Detector and Security Mechanism Design . 78 5.4.2 Throttle Actuator Attack Detector and Security Mechanism Design . 79 6. Implementation, Simulation and Results . 80 6.1 Model in the Loop Testing . 80 6.1.1 UIO test in the Crank Angle Domain . 80 6.1.2 Time Domain and CAN simulation . 85 6.2 HIL Test Bench Design . 89 6.2.1 Real-time Machine Setup . 90 6.2.2 Results on Preliminary HIL setup . 91 7. Conclusion and Future Work . 94 Appendices 96 A. Engine Model . 96 Bibliography . 98 viii List of Tables Table Page 2.1 ASIL table used to determine what the safety level is for an E/E com- ponent [29] . 18 3.1 Table showing the list of challenges associated with the security of CAN [40] . 32 3.2 The different types of In-Vehicle anomaly detectors, referred to by sensor types, with the approach in this thesis potentially classified as both a plausibility, S-7, and/or consistency, S-8, type. [48, Table I] . 36 3.3 The type of anomaly sensor needed can be determined by the design scenario. In our case, a specification approach is not enough; there are multiple messages for which the payload data is available. How- ever, there could be multiple busses and different network types. This approach could be both checking plausibility of the payload data and also checking for consistency on either side of a gateway [48, Table II] 37 4.1 Basic NCS graph notation for tasks, resources, and messages . 52 4.2 Notation for trusted and CAN message sets in NCS . 56 ix List of Figures Figure Page 2.1 Layers and components of the cyber domain [68] . 6 2.2 Model types based on different attributes [69] . 9 2.3 Pyramid that shows the general attack surfaces for ITS technology . 10 2.4 Mobility landscape including various V2X communication surfaces that present security risks to vehicles [11] . 13 2.5 Depiction showing the large number of common attack vectors on a vehicle [20] . 14 2.6 Security mechanisms for a vehicle as a function of the attack progres- sion over time and the type of component being targeted [70] . 20 3.1 A common E/E architecture that would be found on a vehicle today [32] 24 3.2 Communication connections in future AV controllers [32] . 25 3.3 Potential vehicle E/E architecture in future cars showing the high level of attack vectors involved in intra-vehicle communication [32] . 26 3.4 The relationship between CAN and OSI model showing it is only a layer 1/2 protocol which contributes to inherent struggles with security [58] 27 3.5 CAN Packet Description: (a) is a standard packet, (b) is an extended frame packet [28] . 28 3.6 Simplified view of the CAN packet showing the relationship between ArbID, data payload, and messages . 29 x 4.1 Different attack types: (a) is a stealth attack, (b) is a replay attack, (c) is a covert attack [55] . 50 4.2 An example resource graph . 53 4.3 An example process graph . 53 4.4 Example mapping of the process graph in Fig. 4.3 to the resource graph in Fig. 4.2 . 54 5.1 Network setup for the computational units relevant to this case study 65 5.2 Resource graph for AV throttle request . 66 5.3 Process graph for throttle control task . 67 5.4 Mapping of process graph to resource graph focused on targeting the messages used for the observer and vulnerable CAN messages . 68 5.5 Engine Model I/O . 69 5.6 Structural digraph for the zero order hold engine model showing a link size of 1 for a vulnerable state x1, pressure, and its associated output reading y1 ................................
Load more

Recommended publications
  • Intrusion Detection System for Automotive Controller Area Network (CAN) Bus System: a Review Siti-Farhana Lokman* , Abu Talib Othman and Muhammad-Husaini Abu-Bakar
    Lokman et al. EURASIP Journal on Wireless Communications and Networking (2019) 2019:184 https://doi.org/10.1186/s13638-019-1484-3 REVIEW Open Access Intrusion detection system for automotive Controller Area Network (CAN) bus system: a review Siti-Farhana Lokman* , Abu Talib Othman and Muhammad-Husaini Abu-Bakar Abstract The modern vehicles nowadays are managed by networked controllers. Most of the networks were designed with little concern about security which has recently motivated researchers to demonstrate various kinds of attacks against the system. In this paper, we discussed the vulnerabilities of the Controller Area Network (CAN) within in- vehicle communication protocol along with some potential attacks that could be exploited against it. Besides, we present some of the security solutions proposed in the current state of research in order to overcome the attacks. However, the main goal of this paper is to highlight a holistic approach known as intrusion detection system (IDS) which has been a significant tool in securing networks and information systems over the past decades. To the best of our knowledge, there is no recorded literature on a comprehensive overview of IDS implementation specifically in the CAN bus network system. Thus, we proposed an in-depth investigation of IDS found in the literature based on the following aspects: detection approaches, deployment strategies, attacking techniques, and finally technical challenges. In addition, we also categorized the anomaly-based IDS according to these methods, e.g., frequency- based, machine learning-based, statistical-based, and hybrid-based as part of our contributions. Correspondingly, this study will help to accelerate other researchers to pursue IDS research in the CAN bus system.
    [Show full text]
  • Automotive Cybersecurity: Foundations for Next-Generation Vehicles
    Automotive Cybersecurity: Foundations for Next-Generation Vehicles Michele Scalas, Student Member, IEEE Giorgio Giacinto, Senior Member, IEEE Department of Electrical and Electronic Engineering Department of Electrical and Electronic Engineering University of Cagliari University of Cagliari Cagliari, Italy Cagliari, Italy [email protected] [email protected] Abstract—The automotive industry is experiencing a serious Vehicle-to-Vehicle), with a generic infrastructure (V2I) or with transformation due to a digitalisation process and the transition pedestrians (V2P). The typical application of these models is to the new paradigm of Mobility-as-a-Service. The next-generation smart cities, with the aim of optimising traffic management, vehicles are going to be very complex cyber-physical systems, whose design must be reinvented to fulfil the increasing demand sending alerts in case of incidents, coordinating a fleet of of smart services, both for safety and entertainment purposes, vehicles. causing the manufacturers’ model to converge towards that of As regards autonomous driving, it consists in expanding the IT companies. Connected cars and autonomous driving are the current Advanced Driver Assistance Systems (ADASs), such preeminent factors that drive along this route, and they cause the as lane keeping and braking assistants, in order to obtain a necessity of a new design to address the emerging cybersecurity issues: the ”old” automotive architecture relied on a single closed fully autonomous driverless car. The Society of Automotive network, with no external communications; modern vehicles are Engineers (SAE) provides, in fact, six possible levels of going to be always connected indeed, which means the attack autonomy, from level 0, with no assistance, to level 5, where surface will be much more extended.
    [Show full text]
  • Securing the Modern Vehicle: a Study of Automotive Industry Cybersecurity Practices
    Securing the Modern Vehicle: A Study of Automotive Industry Cybersecurity Practices An independent study commissioned by and Table of Contents Executive Summary ............................................................................................ 1 Organizational Dynamics and Challenges ........................................................... 3 Technical Dynamics and Challenges .................................................................... 6 Product Development and Security Testing Practices ......................................... 9 Supply Chain and Third-Party Component Challenges ........................................ 13 Conclusions ........................................................................................................ 14 Methods ............................................................................................................. 15 Appendix: Detailed Survey Results ..................................................................... 18 Ponemon Institute .............................................................................................. 29 Executive Summary Today’s vehicle is a connected, mobile computer, which has introduced an issue the automotive industry has little experience dealing with: cybersecurity risk. Automotive manufacturers have become as much software as transportation companies, facing all the challenges inherent to software security. Synopsys and SAE International partnered to commission this independent survey of the current cybersecurity practices in the automotive
    [Show full text]
  • A PRACTICAL METHOD of IDENTIFYING CYBERATTACKS February 2018 INDEX
    In Collaboration With A PRACTICAL METHOD OF IDENTIFYING CYBERATTACKS February 2018 INDEX TOPICS EXECUTIVE SUMMARY 4 OVERVIEW 5 THE RESPONSES TO A GROWING THREAT 7 DIFFERENT TYPES OF PERPETRATORS 10 THE SCOURGE OF CYBERCRIME 11 THE EVOLUTION OF CYBERWARFARE 12 CYBERACTIVISM: ACTIVE AS EVER 13 THE ATTRIBUTION PROBLEM 14 TRACKING THE ORIGINS OF CYBERATTACKS 17 CONCLUSION 20 APPENDIX: TIMELINE OF CYBERSECURITY 21 INCIDENTS 2 A Practical Method of Identifying Cyberattacks EXECUTIVE OVERVIEW SUMMARY The frequency and scope of cyberattacks Cyberattacks carried out by a range of entities are continue to grow, and yet despite the seriousness a growing threat to the security of governments of the problem, it remains extremely difficult to and their citizens. There are three main sources differentiate between the various sources of an of attacks; activists, criminals and governments, attack. This paper aims to shed light on the main and - based on the evidence - it is sometimes types of cyberattacks and provides examples hard to differentiate them. Indeed, they may of each. In particular, a high level framework sometimes work together when their interests for investigation is presented, aimed at helping are aligned. The increasing frequency and severity analysts in gaining a better understanding of the of the attacks makes it more important than ever origins of threats, the motive of the attacker, the to understand the source. Knowing who planned technical origin of the attack, the information an attack might make it easier to capture the contained in the coding of the malware and culprits or frame an appropriate response. the attacker’s modus operandi.
    [Show full text]
  • Specification-Based Automotive Intrusion Detection Using Controller Area Network
    This is the author's version of an article that has been published in this journal. Changes were made to this version by the publisher prior to publication. The final version of record is available at http://dx.doi.org/10.1109/TVT.2019.2961344 IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, VOL. XX, NO. XX, XXX 2019 1 SAIDuCANT: Specification-based Automotive Intrusion Detection using Controller Area Network (CAN) Timing Habeeb Olufowobi, Clinton Young, Joseph Zambreno, Senior Member, IEEE, and Gedare Bloom, Senior Member, IEEE Abstract—The proliferation of embedded devices in modern and attacks [2]. Vulnerabilities across the autonomous vehi- vehicles has opened the traditionally-closed vehicular system to cles, vehicular ad-hoc networks, vehicle-to-vehicle, vehicle-to- the risk of cybersecurity attacks through physical and remote infrastructure, connected car, intelligent transportation system, access to the in-vehicle network such as the controller area network (CAN). The CAN bus does not implement a security and even traditional (non-connected) automobiles motivate protocol that can protect the vehicle against the increasing cyber adversaries to launch cyberattacks against vehicles [3]. Unfor- and physical attacks. To address this risk, we introduce a novel tunately, today’s car lacks the necessary security mechanisms algorithm to extract the real-time model parameters of the CAN to protect the vehicular system from attack. bus and develop SAIDuCANT, a specification-based intrusion A critical asset to secure is the automotive in-vehicle detection system (IDS) using anomaly-based supervised learning with the real-time model as input. We evaluate the effectiveness of network, which facilitates communication between ECUs over SAIDuCANT with real CAN logs collected from two passenger multiple physical networks and protocols, with the most preva- cars and on an open-source CAN dataset collected from real- lent being the controller area network (CAN).
    [Show full text]
  • Kaspersky Transportation Systems Security Portfolio
    Driving automotive cybersecurity Introduction IHS Markit forecasts that by 2023, worldwide sales Connected cars are more than just physical cars of connected cars will reach 72.5 million units, with digital technology – they are vehicles with up from 24 million units in 2015. That means almost connected infrastructures that include mobile 69% of passenger vehicles sold will be exchanging data with external sources, bringing new services systems and more. As a result, we end up with and business models to bear in automotive connected car ecosystems with multiple entry markets*. points that are vulnerable to cyberattacks. But there’s still a long way to go to guarantee Kaspersky has introduced a set of products connected vehicles are safe and secure for and serv passengers. For that to happen there needs cybersecurity to connected cars and their to be a transformation in the multiple approaches infrastructures and to support the development used across the automotive industry. of new mobility technologies, including autonomous, electric and shared technologies. Transportation System Security Automotive In-vehicle Infrastructure services security security Kaspersky Kaspersky Kaspersky Transportation Kaspersky Kaspersky Kaspersky Kaspersky Security Penetration Tailored Threat Cybersecurity Automotive Mobile Security Fraud Threat Assessment Testing Intelligence for ECUs Adaptive SDK Prevention Intelligence Reporting Platform for Vehicle SOC * Ihsmarkit.com/topic/autonomous-connected-car.html Uncover the Security Risks Security Assessment The Security Assessment service is the ideal starting point for addressing the cybersecurity agenda for connected cars and their infrastructures. It detects vulnerabilities, software architecture inconsistencies, and gaps in ECUs, hardware and software security mechanisms both in manufactured vehicles and future models and their components.
    [Show full text]
  • Detecting and Preventing Automotive Hardware Security Vulnerabilities
    Detecting and Preventing Automotive Hardware Security Vulnerabilities Ensuring hardware security, one chip at a time. VISIT: TORTUGALOGIC.COM Automating the Automotive Security Development Lifecycle Connected and autonomous vehicles present a exposed not one but a chain of security issues. promising target, much like retailers or banks, For Fiat-Chrysler vehicles, it was a remote attack where hackers can troll for personal details and that could be performed against vehicles located identity theft. anywhere in the United State that caused a 1.4 million vehicle recall as well as changes to the Is your vehicle secure? Tesla found out the hard Sprint carrier network. way. Hacking typically begins by finding a series of vulnerability issues that create a path through European vehicles are also not immune. A study the car’s maze of defenses. So, when research- by German auto club ADAC found hackers could ers at the Chinese firm Tencent revealed they wirelessly open any BMW, Mini and Rolls-Royce could burrow through the Wi-Fi connection of vehicles in minutes. An estimated 2.2 million a Tesla S, all the way to its driving systems and vehicles equipped with BMW’s ConnectedDrive then remotely activate the vehicle’s brakes, they service were vulnerable. Connected and autonomous vehicles present a promising target, much like retailers or banks, where hackers can troll for credit card numbers, home addresses, e-mail information and other personal details required for identity theft. Hackers bent on identity theft are expected to infiltrate vehicles through the infotainment portal, as the Jeep hackers did, as well as with malicious apps that appear harmless or even helpful but steal personal information.
    [Show full text]
  • Comprehensive Experimental Analyses of Automotive Attack Surfaces
    Comprehensive Experimental Analyses of Automotive Attack Surfaces Stephen Checkoway, Damon McCoy, Brian Kantor, Danny Anderson, Hovav Shacham, and Stefan Savage University of California, San Diego Karl Koscher, Alexei Czeskis, Franziska Roesner, and Tadayoshi Kohno University of Washington Abstract This situation suggests a significant gap in knowledge, Modern automobiles are pervasively computerized, and and one with considerable practical import. To what ex- hence potentially vulnerable to attack. However, while tent are external attacks possible, to what extent are they previous research has shown that the internal networks practical, and what vectors represent the greatest risks? within some modern cars are insecure, the associated Is the etiology of such vulnerabilities the same as for threat model — requiring prior physical access — has desktop software and can we think of defense in the same justifiably been viewed as unrealistic. Thus, it remains an manner? Our research seeks to fill this knowledge gap open question if automobiles can also be susceptible to through a systematic and empirical analysis of the remote remote compromise. Our work seeks to put this question attack surface of late model mass-production sedan. to rest by systematically analyzing the external attack We make four principal contributions: surface of a modern automobile. We discover that remote Threat model characterization. We systematically exploitation is feasible via a broad range of attack vectors synthesize a set of possible external attack vectors as (including mechanics tools, CD players, Bluetooth and a function of the attacker’s ability to deliver malicious cellular radio), and further, that wireless communications input via particular modalities: indirect physical access, channels allow long distance vehicle control, location short-range wireless access, and long-range wireless tracking, in-cabin audio exfiltration and theft.
    [Show full text]
  • Document Title Security Models
    HEAVENS – HEAling Vulnerabilities to ENhance Software Security and Safety Dnr 2012-04625 Document Title Security models Document Type Deliverable Document Number D2 Aljoscha Lautenbach, [email protected], Chalmers Document Responsible Mafijul Islam, [email protected], Volvo AB Document Version 2.0 Document Status Released (March 18, 2016) Dissemination Level Public Last Change March 18, 2016 Project Acronym HEAVENS Project Title HEAling Vulnerabilities to ENhance Software Security and Safety Research Program Vinnova/FFI (Fordonsutveckling/Vehicle Development), Sweden Diary Number 2012-04625 Project Duration April 2013 – March 2016 Project Coordinator Mats Olsson, [email protected] , Volvo AB © 2016 The HEAVENS Consortium HEAVENS (Dnr 2012-04625) Deliverable D2 Security models This page is intentionally left blank © 2016 The HEAVENS Consortium 2(100) HEAVENS (Dnr 2012-04625) Deliverable D2 Security models Executive Summary This deliverable (D2 Security models, Release 2, Version 2.0) presents the results and achievements of work package WP2 (Security models) of the HEAVENS project. The goal of this deliverable is to present a systematic approach of deriving security requirements for the automotive Electrical and/or Electronic (E/E) systems. It suggests an adaption of generic security engineering process for the automotive domain. The deliverable presents state-of-the-art threat analysis and risk assessment methodologies, processes, frameworks and tools, considering various industrial domains, for example, IT security, telecommunications, software engineering and defense. It presents the results obtained from performing a critical review of the state-of-the-art threat analysis and risk assessment in the context of the automotive industry. Based on this, a new security model − HEAVENS security model − for the automotive industry is proposed to facilitate deriving security requirements for the automotive E/E systems.
    [Show full text]
  • Protecting the Fleet…And the Car Business 1 International”), a Swiss Entity
    Protecting the fleet… and the car business Today’s cyber-physical threats disrupt automotive operating models Sponsored by KPMG’s U.S. Manufacturing Institute Automotive Center www.kpmg.com/us/automotive © 2017 KPMG LLP, a Delaware limited liability partnership and the U.S. member firm of the KPMG network of independent member firms affiliated with KPMG International Cooperative (“KPMG International”), a Swiss entity. All rights reserved. The KPMG name and logo are registered trademarks or trademarks of KPMG International. NDPPS 698248 Contents Ready for a car hack…times one million? 2 What is hiding in the wireless communication fog? 5 Cyber disruption will transform automotive businesses 10 Steering the way to more secure fleets 14 Making the right turns ahead 19 How KPMG can help 20 About the authors 21 © 2017 KPMG LLP, a Delaware limited liability partnership and the U.S. member firm of the KPMG network of independent member firms affiliated with KPMG International Cooperative (“KPMG Protecting the fleet…and the car business 1 International”), a Swiss entity. All rights reserved. The KPMG name and logo are registered trademarks or trademarks of KPMG International. NDPPS 698248 Software complexity 160 Ready for a car hack… Ford F-150 (2016) times one million? Modern vehicles are marvels of innovation. Even today’s most popular models are chock full of technology and connectivity. The average car contains more than 150 million lines of code, plus multiple individual computers and a vast number of wireless connections to internal and external communication channels1. It can stream music, send texts, offer real-time traffic information and personalized roadside assistance, detect nearby activity through sensors, and even drive autonomously in controlled situations.2 This immense amount of on-vehicle technology has created automobiles that have more lines of code than a 2016 Ford F-150, an F-35 fighter, and a Boeing 787.1 Moreover, vehicles and their users are data hungry.
    [Show full text]
  • Masquerade Detection in Automotive Security
    San Jose State University SJSU ScholarWorks Master's Projects Master's Theses and Graduate Research Spring 5-20-2019 Masquerade Detection in Automotive Security Ashraf Saber San Jose State University Follow this and additional works at: https://scholarworks.sjsu.edu/etd_projects Part of the Artificial Intelligence and Robotics Commons, and the Other Computer Sciences Commons Recommended Citation Saber, Ashraf, "Masquerade Detection in Automotive Security" (2019). Master's Projects. 705. DOI: https://doi.org/10.31979/etd.65bn-7anq https://scholarworks.sjsu.edu/etd_projects/705 This Master's Project is brought to you for free and open access by the Master's Theses and Graduate Research at SJSU ScholarWorks. It has been accepted for inclusion in Master's Projects by an authorized administrator of SJSU ScholarWorks. For more information, please contact [email protected]. Masquerade Detection in Automotive Security A Project Presented to The Faculty of the Department of Computer Science San José State University In Partial Fulfillment of the Requirements for the Degree Master of Science by Ashraf Saber May 2019 © 2019 Ashraf Saber ALL RIGHTS RESERVED The Designated Project Committee Approves the Project Titled Masquerade Detection in Automotive Security by Ashraf Saber APPROVED FOR THE DEPARTMENT OF COMPUTER SCIENCE SAN JOSÉ STATE UNIVERSITY May 2019 Dr. Mark Stamp Department of Computer Science Dr. Thomas Austin Department of Computer Science Fabio Di Troia Department of Computer Science ABSTRACT Masquerade Detection in Automotive Security by Ashraf Saber In this paper, we consider intrusion detection systems (IDS) in the context of a controller area network (CAN), which is also known as the CAN bus.
    [Show full text]
  • Towards a Standardized Mapping from Automotive Security Levels to Security Mechanisms
    Towards a Standardized Mapping from Automotive Security Levels to Security Mechanisms Downloaded from: https://research.chalmers.se, 2021-09-28 23:19 UTC Citation for the original published paper (version of record): Rosenstatter, T., Olovsson, T. (2018) Towards a Standardized Mapping from Automotive Security Levels to Security Mechanisms IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC: 1501-1507 http://dx.doi.org/10.1109/ITSC.2018.8569679 N.B. When citing this work, cite the original published paper. research.chalmers.se offers the possibility of retrieving research publications produced at Chalmers University of Technology. It covers all kind of research output: articles, dissertations, conference papers, reports etc. since 2004. research.chalmers.se is administrated and maintained by Chalmers Library (article starts on next page) Towards a Standardized Mapping from Automotive Security Levels to Security Mechanisms Thomas Rosenstatter Tomas Olovsson Department of Computer Science and Engineering Department of Computer Science and Engineering Chalmers University of Technology Chalmers University of Technology Email: [email protected] Email: [email protected] Abstract—Modern vehicles are becoming targets and need to requirements. Currently missing in proposed models is how be secured throughout their lifetime. There exist several risk to select required security mechanisms for each component assessment models which can be used to derive security levels and function based on the security level when following that describe to what extent components, functions and messages (signals), need to be protected. These models provide methods the risk assessment process. In this paper, we address this to gather application specific security requirements based on problem by first suggesting that the risk assessment process identified threat and item combinations that need to be coped should result in five security levels, similar to the Automotive with.
    [Show full text]