Improving CAN bus security by assigning dynamic arbitration IDs

Islam, Riadul; Refat, Rafi Ud Daula

doi:10.1007/s12198-020-00208-0

Cited by 17 publications

(15 citation statements)

References 13 publications

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“…To secure CAN bus, researchers proposed several techniques [18,19,20]. Wolf et al [18] proposed a firewall signature-based architecture for securing vehicular communication gateways.…”

Section: Existing Attack Prevention Methodologiesmentioning

confidence: 99%

GGNB: Graph-Based Gaussian Naive Bayes Intrusion Detection System for CAN Bus

Islam¹,

Devnath²,

Samad³

et al. 2021

Preprint

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The national highway traffic safety administration (NHTSA) identified cybersecurity of the automobile systems are more critical than the security of other information systems. Researchers already demonstrated remote attacks on critical vehicular electronic control units (ECUs) using controller area network (CAN). Besides, existing intrusion detection systems (IDSs) often propose to tackle a specific type of attack, which may leave a system vulnerable to numerous other types of attacks. A generalizable IDS that can identify a wide range of attacks within the shortest possible time has more practical value than attack-specific IDSs, which is not a trivial task to accomplish. In this paper we propose a novel graph-based Gaussian naive Bayes (GGNB) intrusion detection algorithm by leveraging graph properties and PageRankrelated features. The GGNB on the real rawCAN data set [1] yields 99.61%, 99.83%, 96.79%, and 96.20% detection accuracy for denial of service (DoS), fuzzy, spoofing, replay, mixed attacks, respectively. Also, using OpelAstra data set [2], the proposed methodology has 100%, 99.85%, 99.92%, 100%, 99.92%, 97.75% and 99.57% detection accuracy considering DoS, diagnostic, fuzzing CAN ID, fuzzing payload, replay, suspension, and mixed attacks, respectively. The GGNB-based methodology requires about 239× and 135× lower training and tests times, respectively, compared to the SVM classifier used in the same application. Using Xilinx Zybo Z7 field-programmable

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“…To secure CAN bus, researchers proposed several techniques [18,19,20]. Wolf et al [18] proposed a firewall signature-based architecture for securing vehicular communication gateways.…”

Section: Existing Attack Prevention Methodologiesmentioning

confidence: 99%

GGNB: Graph-Based Gaussian Naive Bayes Intrusion Detection System for CAN Bus

Islam¹,

Devnath²,

Samad³

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…Due to the widespread use of CAN, there has been a significant amount of work on CAN security [2]- [9], [12], [21]- [27]. Researchers incorporate conventional validation techniques to identify invalid CAN ID [21].…”

Section: Related Workmentioning

confidence: 99%

“…An attack can be performed through either a weak or a strong agent [6]. A weak agent can spoof the CAN bus by injecting messages with high priority (ID 0000, denial of service (DoS) attack [7]) or with any arbitration ID (spoofing [8] or Fuzzy attack [3], [9]). On the other hand, a strong agent uses two attackers at the same time to perform attacks.…”

Section: Introductionmentioning

confidence: 99%

Graph-Based Intrusion Detection System for Controller Area Networks

Islam

Refat

Yerram

et al. 2022

IEEE Trans. Intell. Transport. Syst.

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The controller area network (CAN) is the most widely used intra-vehicular communication network in the automotive industry. Because of its simplicity in design, it lacks most of the requirements needed for a security-proven communication protocol. However, a safe and secured environment is imperative for autonomous as well as connected vehicles. Therefore CAN security is considered one of the important topics in the automotive research community. In this paper, we propose a fourstage intrusion detection system that uses the chi-squared method and can detect any kind of strong and weak cyber attacks in a CAN. This work is the first-ever graph-based defense system proposed for the CAN. Our experimental results show that we have a very low 5.26% misclassification for denial of service (DoS) attack, 10% misclassification for fuzzy attack, 4.76% misclassification for replay attack, and no misclassification for spoofing attack. In addition, the proposed methodology exhibits up to 13.73% better accuracy compared to existing ID sequence-based methods.

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“…e analysis of CAN inaccessibility is considered at the time of communication of message bits from a source node to [49]. As soon as the first bit of a dataset is transmitted, bit error detection as per a transmitting node can take place.…”

Section: Bit and Cyclic Redundancy Check (Crc) Errorsmentioning

confidence: 99%

Adaptive Fault-Tolerant System and Optimal Power Allocation for Smart Vehicles in Smart Cities Using Controller Area Network

Biswal

Singh

Pattanayak

et al. 2021

Security and Communication Networks

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Nowadays, the power consumption and dependable repeated data collection are causing the main issue for fault or collision in controller area network (CAN), which has a great impact for designing autonomous vehicle in smart cities. Whenever a smart vehicle is designed with several sensor nodes, Internet of Things (IoT) modules are linked through CAN for reliable transmission of a message for avoiding collision, but it is failed in communication due to delay and collision in communication of message frame from a source node to the destination. Generally, the emerging role of IoT and vehicles has undoubtedly brought a new path for tomorrow’s cities. The method proposed in this paper is used to gain fault-tolerant capability through Probabilistic Automatic Repeat Request (PARQ) and also Probabilistic Automatic Repeat Request (PARQ) with Fault Impact (PARQ-FI), in addition to providing optimal power allocation in CAN sensor nodes for enhancing the performance of the process and also significantly acting a role for making future smart cities. Several message frames are needed to be retransmitted on PARQ and fault impact (PARQ-FI) calculates the message with a response probability of each node.

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Improving CAN bus security by assigning dynamic arbitration IDs

Cited by 17 publications

References 13 publications

GGNB: Graph-Based Gaussian Naive Bayes Intrusion Detection System for CAN Bus

GGNB: Graph-Based Gaussian Naive Bayes Intrusion Detection System for CAN Bus

Graph-Based Intrusion Detection System for Controller Area Networks

Adaptive Fault-Tolerant System and Optimal Power Allocation for Smart Vehicles in Smart Cities Using Controller Area Network

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