MISO- V: Misbehavior Detection for Collective Perception Services in Vehicular Communications

Liu, Xiruo; Yang, Lixin; Álvarez, Ignacio; Sivanesan, Kathiravetpillai; Merwaday, Arvind; Oboril, Fabian; Buerkle, Cornelius; Sastry, Manoj; Baltar, Leonardo Gomes

doi:10.1109/iv48863.2021.9575970

Cited by 10 publications

(4 citation statements)

References 8 publications

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“…In [2], a probability of trustworthiness is estimated for each pair of peers, by checking the consistency of their object lists and their respective detection probabilities across space. More recently, [11] compared occupied or free space in the form of grids and verified that detected objects matched with these grids. In [1], sensors estimate a probability of existence for each object.…”

Section: Related Workmentioning

confidence: 93%

“…A trust parameter representing the sensor's information reliability is fixed for each sensors. Our method can be seen as an unification of [3,2,11] where fault detection generates untrustworthiness and confirmation creates trustworthiness.…”

Section: Related Workmentioning

confidence: 99%

“…m osi j and m fsi j model that trustworthy information should match with the local one. The received F S is compared using the method of [11] in m fsi j . Received objects O j are matched using an assignment function noted A and compared using the similarity function m S defined in [13].…”

Section: Confirmation Through Free Space and Objectsmentioning

confidence: 99%

See 2 more Smart Citations

Evidential Trustworthiness Estimation for Cooperative Perception

Lima

Cherfaoui

2022

Belief Functions: Theory and Applications

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Intelligent Vehicles can exchange their perception information using wireless technology in a cooperative and decentralized manner. This has the potential to extend the range of perception and thus improve anticipation for complex driving maneuvers and decision making. However, information received from other peers can be erroneous and has to be used carefully. In this paper, we present a method that allows each peer to assign a trust in the information received from other peers based on comparisons with its current knowledge of the world. We describe how this process is managed using the Dempster-Shafer theory. We also present how positive and negative evidence cues can be developed in this problem, in particular by using detectability grids. An experimental evaluation, carried out with real vehicles, is reported to show that this formalism behaves correctly.

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Section: Related Workmentioning

confidence: 93%

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Evidential Trustworthiness Estimation for Cooperative Perception

Lima

Cherfaoui

2022

Belief Functions: Theory and Applications

View full text Add to dashboard Cite

show abstract

“…In [19], the authors provide a generic design framework that is independent of perception algorithms and analyzes the misbehavior detection system based on the framework against ghost vehicle attacks in the mixed environment. MISO-V (Multiple Independent Sources of Observations over V2X) [20] addresses the data reliability challenges of CPM by exploiting the inherently overlapping nature of perceptual observations from multiple vehicles to verify the semantic correctness of V2X data.…”

Section: Related Workmentioning

confidence: 99%

Misbehavior Detection Using Collective Perception under Privacy Considerations

Tsukada¹,

Arii²,

Ochiai³

et al. 2021

Preprint

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In cooperative ITS, security and privacy protection are essential. Cooperative Awareness Message (CAM) is a basic V2V message standard, and misbehavior detection is critical for protection against attacking CAMs from the inside system, in addition to node authentication by Public Key Infrastructure (PKI). On the contrary, pseudonym IDs, which have been introduced to protect privacy from tracking, make it challenging to perform misbehavior detection. In this study, we improve the performance of misbehavior detection using observation data of other vehicles. This is referred to as collective perception message (CPM), which is becoming the new standard in European countries. We have experimented using realistic traffic scenarios and succeeded in reducing the rate of rejecting valid CAMs (false positive) by approximately 15 percentage points while maintaining the rate of correctly detecting attacks (true positive).

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Intelligent Transportation System Based on Internet of Things (IoT)-Based Cloud Applications

Tyagi¹,

Sreenath²

2022

Disruptive Technologies and Digital Transformations for Society 5.0

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MISO- V: Misbehavior Detection for Collective Perception Services in Vehicular Communications

Cited by 10 publications

References 8 publications

Evidential Trustworthiness Estimation for Cooperative Perception

Evidential Trustworthiness Estimation for Cooperative Perception

Misbehavior Detection Using Collective Perception under Privacy Considerations

Intelligent Transportation System Based on Internet of Things (IoT)-Based Cloud Applications

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