Multi-Channel Based Sybil Attack Detection in Vehicular Ad Hoc Networks Using RSSI

Yao, Yuan; Xiao, Bin; Wu, Gaofei; Li, Xue; Yu, Zhiwen; Zhang, Kailong; Zhou, Xingshe

doi:10.1109/tmc.2018.2833849

Cited by 88 publications

(44 citation statements)

References 22 publications

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“…For this reason, the literature specifies an important limitation compared to the Dolev-Yao model: an attacker must be a node in the network, restricted by the same physical properties that restrict a normal node. Although their transmission range may be increased through power control [57], attackers are considered to have a limited physical presence [39]. In addition, it is commonly assumed that attackers are constrained to physical limitations such as the speed of light.…”

Section: A Definition and Attacker Modelmentioning

confidence: 99%

“…This will be especially challenging when combined with newly proposed MAC-protocols that exploit the additional spatial re-use enabled by transmit power variations, such as decentralized congestion control in ETSI [118]. Although some proposals [57] address this issue by looking at signals over time, this increases the detection latency.…”

Section: A Reoccurring Patternsmentioning

confidence: 99%

See 1 more Smart Citation

Survey on Misbehavior Detection in Cooperative Intelligent Transportation Systems

Heijden

Dietzel

Leinmüller

et al. 2019

IEEE Commun. Surv. Tutorials

192

148

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Cooperative Intelligent Transportation Systems (cITS) are a promising technology to enhance driving safety and efficiency. Vehicles communicate wirelessly with other vehicles and infrastructure, thereby creating a highly dynamic and heterogeneously managed ad-hoc network. It is these network properties that make it a challenging task to protect integrity of the data and guarantee its correctness. A major component is the problem that traditional security mechanisms like PKIbased asymmetric cryptography only exclude outsider attackers that do not possess key material. However, because attackers can be insiders within the network (i.e., possess valid key material), this approach cannot detect all possible attacks. In this survey, we present misbehavior detection mechanisms that can detect such insider attacks based on attacker behavior and information analysis. In contrast to well-known intrusion detection for classical IT systems, these misbehavior detection mechanisms analyze information semantics to detect attacks, which aligns better with highly application-tailored communication protocols foreseen for cITS. In our survey, we provide an extensive introduction to the cITS ecosystem and discuss shortcomings of PKI-based security. We derive and discuss a classification for misbehavior detection mechanisms, provide an in-depth overview of seminal papers on the topic, and highlight open issues and possible future research trends.

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Section: A Definition and Attacker Modelmentioning

confidence: 99%

Section: A Reoccurring Patternsmentioning

confidence: 99%

Survey on Misbehavior Detection in Cooperative Intelligent Transportation Systems

Heijden

Dietzel

Leinmüller

et al. 2019

IEEE Commun. Surv. Tutorials

192

148

View full text Add to dashboard Cite

show abstract

“…Prior work [75], [93] also do not account for GPS errors in the model. A distributed mechanism, Voiceprint [94], was proposed to detect Sybil attacks by analyzing RSSI (received signal strength indicator)-based measurements (e.g., by performing a similarity measures between the RSSI of an attacker and its Sybil nodes over time). However Voiceprint may not detect attacks if an adversary uses more than one radio.…”

Section: B Detecting Sybil Attacksmentioning

confidence: 99%

Securing Vehicle-to-Everything (V2X) Communication Platforms

Hasan

Mohan

Shimizu

et al. 2020

IEEE Trans. Intell. Veh.

159

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Modern vehicular wireless technology enables vehicles to exchange information at any time, from any place, to any network -forms the vehicle-to-everything (V2X) communication platforms. Despite benefits, V2X applications also face great challenges to security and privacy -a very valid concern since breaches are not uncommon in automotive communication networks and applications. In this survey, we provide an extensive overview of V2X ecosystem. We also review main security/privacy issues, current standardization activities and existing defense mechanisms proposed within the V2X domain. We then identified semantic gaps of existing security solutions and outline possible open issues.We also discuss possible open issues (Section VIII), summarize multiple industry/academic/government initiatives for securing V2X communications (Section IX-A) and compare our work with related surveys (Section IX-B). II. V2X PLATFORM : AN OVERVIEWThis section provides an overview of V2X communication interfaces (Section II-A) and discuss various network/communication models (Section II-B). A. Communication InterfacesThe internal architecture of a vehicle is interconnected with ECUs (electronic control units -embedded computing platform that monitor/control automotive systems) coupled with sensors and actuators. The communication between the vehicle and the outside world such as other vehicles or roadside units (RSUs) is performed via external interfaces (see Fig. 1). These vehicular external interfaces are attached to the telematics control unit (TCU) -also referred to as on-board unit (OBU) 1 -an ECU that provides wireless connectivity [7], [8]. A vehicle control unit coordinates with the OBU to collect and disseminate vehicular data [9]. The current standards for V2X communication are DSRC (dedicated short range communication) [10] in the United States, C-ITS (cooperative intelligent transport systems) [11] in Europe and ITS Connect [12] in Japan. Both DSRC and C-ITS operating in the 5.9 GHz ITS band while ITS Connect operating in 760 MHz band (refer to Section II-B1 for details). An alternative to DSRC/C-ITS is the next generation of cellular wireless mobile telecommunications technology (see Section II-B2). OBUs can also be equipped with interfaces for long-range communication. These long-range wireless channels can be classified as broadcast channels (signals can be broadcast to multiple vehicles without knowledge of the receiver's address) and addressable channels (where messages are sent to vehicles with specific addresses.) [13]. Examples of broadcast channels include the global navigation satellite system (GNSS), traffic message/satellite radio receivers, etc. Addressable channels are typically used for long-range voice/data transmissions and are intended to be used for cellular communications for mobile broadband [8].

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“…The proposed model performs the load balancing among the nodes with limited buffer space. However, none of these papers has considered security requirements IoT devices are list as follows: In [16], the authors have proposed a Sybil attack detection mechanism based on the count interval and affinity value of the observer and Sybil node. The affinity value was calculated using a graph.…”

Section: Related Workmentioning

confidence: 99%

A QoS-aware Secured Communication Scheme for IoT-based Networks

Khan¹,

Au²,

Yahya³

et al. 2019

Preprint

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The Internet of Things (IoT) is an emerging technology that aims to enable the interconnection of a large number of smart devices and heterogeneous networks. Ad hoc networks play an important role in the designing of IoT-enabled platforms due to their efficient, flexible, low-cost, and dynamic infrastructures. These networks utilize the available resources efficiently to maintain the Quality of Service (QoS) in a multi-hop communication. However, in a multi-hop communication, the relay nodes can be malicious, thus requiring a secured and reliable data transmission. In this paper, we propose a QoS-aware secured communication scheme for IoT-based networks (QoS-IoT). In QoS-IoT, a Sybil attack detection mechanism is used for the identification of Sybil nodes and their forged identities in multi-hop communication. %by high-power and mobile nodes. After Sybil nodes detection, an optimal contention window (CW) is selected for QoS provisioning, i.e., to achieve per-flow fairness and efficient utilization of the available bandwidth. In a multi-hop communication, the MAC layer protocols do not perform well in terms of fairness and throughput, especially when the nodes generate a large amount of data. It is because the MAC layer has no capability of providing QoS to prioritized or forwarding flows. We evaluate the performance of QoS-IoT in terms of Sybil attack detection, fairness, throughput, and buffer utilization. The simulation results show that the proposed scheme outperforms the existing schemes and significantly enhances the performance of the network with a large volume of data. Moreover, the proposed scheme is resilient against Sybil attack.

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Multi-Channel Based Sybil Attack Detection in Vehicular Ad Hoc Networks Using RSSI

Cited by 88 publications

References 22 publications

Survey on Misbehavior Detection in Cooperative Intelligent Transportation Systems

Survey on Misbehavior Detection in Cooperative Intelligent Transportation Systems

Securing Vehicle-to-Everything (V2X) Communication Platforms

A QoS-aware Secured Communication Scheme for IoT-based Networks

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