Detecting Low-Rate Replay-Based Injection Attacks on In-Vehicle Networks

Katragadda, Satya; Darby, Paul; Roché, Andrew; Gottumukkala, Raju

doi:10.1109/access.2020.2980523

Cited by 31 publications

(16 citation statements)

References 26 publications

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“…Moreover, using a public key encryption scheme for symmetric key exchange in CoMAD also helps mitigating mirroring attacks. Additional functionalities on detecting the adversary may also be implemented, as in [49].…”

Section: ) Mirroringmentioning

confidence: 99%

CoMAD: Context-Aware Mutual Authentication Protocol for Drone Networks

2021

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Drone technology is developing very rapidly. Flying devices accomplishing various applications are becoming an integral part of our daily life undoubtedly. Drones are characterized by extreme mobility, decent computing power, scalability, and a very short lifetime due to energy constraints. The rise of drones inevitably enabled swarms and drone networking applications. Drone networks is a pathbreaking subclass of flying ad-hoc networks with unique capabilities and specific requirements. One very important challenge with swarms is the device authentication problem, in other words, proving the identity of a single or a group of drones that request to join the swarm. In this paper, we tackle this emerging problem and propose a novel context-aware mutual authentication protocol. The proposed protocol provides authentication for groups of drones and supports recovering a swarm in case of network separation. Likewise, the protocol can handle drone joins and leaves. Moreover, the protocol is not dependent on network infrastructure, secure storage, and secure channels. We tested the protocol using an automated formal security protocol verification tool, called Scyther. The tests resulted in the complete verification of the authentication and secrecy claims for arbitrary network instances and all defined use-cases. The protocol is also shown to have proven performance advantages over the existing schemes.INDEX TERMS Authentication, drone networks, security, swarms, wireless ad-hoc networks.

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Section: ) Mirroringmentioning

confidence: 99%

CoMAD: Context-Aware Mutual Authentication Protocol for Drone Networks

2021

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“…Their proposed IDS have achieved good results at message frequency anomaly, but for the data-field content, only the injection of a large number of abnormal messages to the CAN bus can be detected. Satya and Raju [4] proposed an IDS for in-vehicle CAN bus using sequence mining algorithm, which can detect various forms of replay attacks. Taylor et al [5] proposed a frequency-based IDS for in-vehicle CAN bus.…”

Section: B Related Workmentioning

confidence: 99%

Signature-Based Intrusion Detection System (IDS) for In-Vehicle CAN Bus Network

Jin

Chung

2021

2021 IEEE International Symposium on Circuits and Systems (ISCAS)

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In-vehicle CAN (Controller Area Network) bus network does not have any network security protection measures, which is facing a serious network security threat. However, most of the intrusion detection solutions requiring extensive computational resources cannot be implemented in invehicle network system because of the resource constrained ECUs. To add additional hardware or to utilize cloud computing, we need to solve the cost problem and the reliable communication requirement between vehicles and cloud platform, which is difficult to be applied in a short time. Therefore, we need to propose a short-term solution for automobile manufacturers. In this paper, we propose a signature-based light-weight intrusion detection system, which can be applied directly and promptly to vehicle's ECUs (Electronic Control Units). We detect the anomalies caused by several attack modes on CAN bus from real-world scenarios, which provide the basis for selecting signatures. Experimental results show that our method can effectively detect CAN traffic related anomalies. For the content related anomalies, the detection ratio can be improved by exploiting the relationship between the signals.

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“…Jin, Chung, and Xu propose a signature-based intrusion detection system [9] that can detect replay and interruption attacks. Katragadda, Darby, et al [10] propose a system to detect low-rate replay attacks however it their solution works only for specific types of replay attacks. Wu, Kurachi, et al [11] use statistical measurements related to the message id to attempt to thwart replay and reverse-engineering attacks on the CAN.…”

Section: Background and Related Workmentioning

confidence: 99%

Design of Anomaly Detection Functions for Controller Area Networks

Tanksale

2021

IEEE Open J. Intell. Transp. Syst.

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Vehicles are becoming increasingly autonomous and connected, leading to an increase in the types of security threats to vehicles. Controller Area Network (CAN) is a serial bus system that is used to connect sensors and controllers (Electronic Control Units -ECUs) within a vehicle. ECUs vary widely in processing power, storage, memory, and connectivity. There is a need for efficient security countermeasures for protecting the CAN from various attacks. In this paper, we present a novel process to efficiently design functions that can be used for anomaly detection. Our earlier work successfully demonstrated the use of Long Short-Term Memory (LSTM) Networks to perform anomaly detection. This paper focuses on the efficient design and testing of functions that are attack-resistant and can be used in our anomaly detection engine. Once trained, our system is capable of efficiently detecting anomalies in real-time. We report the results of our anomaly detection function design process. We also present the results of our overall anomaly detection engine that are used as inputs to our detection engine. Our function design process and anomaly detection engine have been tested on data from real automobiles. We present the results of our experiments and analyze our findings.

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Detecting Low-Rate Replay-Based Injection Attacks on In-Vehicle Networks

Cited by 31 publications

References 26 publications

CoMAD: Context-Aware Mutual Authentication Protocol for Drone Networks

CoMAD: Context-Aware Mutual Authentication Protocol for Drone Networks

Signature-Based Intrusion Detection System (IDS) for In-Vehicle CAN Bus Network

Design of Anomaly Detection Functions for Controller Area Networks

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