A taxonomy and survey of cyber-physical intrusion detection approaches for vehicles

Loukas, George; Karapistoli, Eirini; Panaousis, Emmanouil; Sarigiannidis, Panagiotis; Bezemskij, Anatolij; Vuong, Tuan

doi:10.1016/j.adhoc.2018.10.002

Cited by 98 publications

(44 citation statements)

References 84 publications

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“…In these methods, the packet transmitted through tunnels are received rather promptly or with less hop counts compared to ordinary packets, which are transmitted through a multi-hop route. Through this technique, an illusion is established that the two tunnel end points are close [5]. Therefore, the hostile nodes are established as decoys between the source and destination nodes, and are able to perform subversions such as packet droppings and manipulation.…”

Section: Cyber Security Threatsmentioning

confidence: 99%

Securing of Unmanned Aerial Systems (UAS) against security threats using human immune system

Fotohi

2020

Reliability Engineering & System Safety

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UASs form a large part of the fighting ability of the advanced military forces. In particular, these systems that carry confidential information are subject to security attacks. Accordingly, an Intrusion Detection System (IDS) has been proposed in the proposed design to protect against the security problems using the human immune system (HIS). The IDSs are used to detect and respond to attempts to compromise the target system. Since the UASs operate in the real world, the testing and validation of these systems with a variety of sensors is confronted with problems. This design is inspired by HIS. In the mapping, insecure signals are equivalent to an antigen that are detected by antibody-based training patterns and removed from the operation cycle. Among the main uses of the proposed design are the quick detection of intrusive signals and quarantining their activity. Moreover, SUAS-HIS method is evaluated here via extensive simulations carried out in NS-3 environment. The simulation results indicate that the UAS network performance metrics are improved in terms of false positive rate, false negative rate, detection rate, and packet delivery rate. detection methods to track and to eliminate. In specific, to increase the chance of successfully intercepting a ballistic missile, it is essential to have swift detection and tracking system, capable of detecting and tracking the missile right after it is launched. The designers working on ballistic missile defense networks are aiming the system to be capable of intercepting the missiles during their initial 2 to 5 minutes of flight, which is called the boost phase. During the boost phase, if the trajectory of the missile is directly away from the trajectory of the UAV, it will easily recede from the range of the sensors on the UAV. Hence, the routing of the information used in the network of the sensors of the ballistic missile should be addressed using networks of hybrid wireless sensors capable of complying with high availability and requirements mandated due to security. To demonstrate the UAVs' applications that have an innate time sensitivity, and to signify the urgency of providing security in communication channels, this case is discussed in the following paper [2,3]. However, despite the advantage's UAVs provide through various applications, since there are situations where no pilot monitors the activities, they are potentially vulnerable against cyber threats. This intensifies the emergence to design secure and reliable UASs and overcome the challenges to avoid damage and destruction to other systems as well as human lives [2,3].A number of attacks, such as Wormhole (WH), Black hole (BH), Gray hole (GH), and Fake Information Dissemination (FID), illegally penetrate the system. Once an unmanned system is affected by an attack, removing the threat and bringing the system back online is a laborious task. It should be mentioned that the common methods to secure information, such as encryption or intrusion detection [4], are inadequate when dealing with such risks. T...

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Section: Cyber Security Threatsmentioning

confidence: 99%

Securing of Unmanned Aerial Systems (UAS) against security threats using human immune system

Fotohi

2020

Reliability Engineering & System Safety

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“…The basic principle of an IDS for an in-vehicle detection system is the same as that of an IDS for general communication networks, where the research literature is already quite extensive and in many cases, research outputs have led to commercial developments. There are already surveys in the literature, which extensively identify and catalog the different IDS for in-vehicle networks [ 4 , 5 , 6 ]. One simplistic classification of the methods to design and implement the IDS divides the literature in two main categories.…”

Section: Related Workmentioning

confidence: 99%

On the Application of Entropy Measures with Sliding Window for Intrusion Detection in Automotive In-Vehicle Networks

Baldini

2020

Entropy

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The evolution of modern automobiles to higher levels of connectivity and automatism has also increased the need to focus on the mitigation of potential cybersecurity risks. Researchers have proven in recent years that attacks on in-vehicle networks of automotive vehicles are possible and the research community has investigated various cybersecurity mitigation techniques and intrusion detection systems which can be adopted in the automotive sector. In comparison to conventional intrusion detection systems in large fixed networks and ICT infrastructures in general, in-vehicle systems have limited computing capabilities and other constraints related to data transfer and the management of cryptographic systems. In addition, it is important that attacks are detected in a short time-frame as cybersecurity attacks in vehicles can lead to safety hazards. This paper proposes an approach for intrusion detection of cybersecurity attacks in in-vehicle networks, which takes in consideration the constraints listed above. The approach is based on the application of an information entropy-based method based on a sliding window, which is quite efficient from time point of view, it does not require the implementation of complex cryptographic systems and it still provides a very high detection accuracy. Different entropy measures are used in the evaluation: Shannon Entropy, Renyi Entropy, Sample Entropy, Approximate Entropy, Permutation Entropy, Dispersion and Fuzzy Entropy. This paper evaluates the impact of the different hyperparameters present in the definition of entropy measures on a very large public data set of CAN-bus traffic with millions of CAN-bus messages with four different types of attacks: Denial of Service, Fuzzy Attack and two spoofing attacks related to RPM and Gear information. The sliding window approach in combination with entropy measures can detect attacks in a time-efficient way and with great accuracy for specific choices of the hyperparameters and entropy measures.

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“…Possible cyber, physical and cyber-physical attack classification is presented in [ 16 ] together with a taxonomy of intrusion detection software (IDS). Three main cyber-physical attack targets are identified: Confidentiality, integrity, and availability.…”

Section: Related Workmentioning

confidence: 99%

In-Vehicle Situation Monitoring for Potential Threats Detection Based on Smartphone Sensors

Kashevnik

Ponomarev

Shilov

et al. 2020

Sensors

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This paper presents an analysis of modern research related to potential threats in a vehicle cabin, which is based on situation monitoring during vehicle control and the interaction of the driver with intelligent transportation systems (ITS). In the modern world, such systems enable the detection of potentially dangerous situations on the road, reducing accident probability. However, at the same time, such systems increase vulnerabilities in vehicles and can be sources of different threats. In this paper, we consider the primary information flows between the driver, vehicle, and infrastructure in modern ITS, and identify possible threats related to these entities. We define threat classes related to vehicle control and discuss which of them can be detected by smartphone sensors. We present a case study that supports our findings and shows the main use cases for threat identification using smartphone sensors: Drowsiness, distraction, unfastened belt, eating, drinking, and smartphone use.

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A taxonomy and survey of cyber-physical intrusion detection approaches for vehicles

Cited by 98 publications

References 84 publications

Securing of Unmanned Aerial Systems (UAS) against security threats using human immune system

Securing of Unmanned Aerial Systems (UAS) against security threats using human immune system

On the Application of Entropy Measures with Sliding Window for Intrusion Detection in Automotive In-Vehicle Networks

In-Vehicle Situation Monitoring for Potential Threats Detection Based on Smartphone Sensors

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