Intelligent Detection of Black Hole Attacks for Secure Communication in Autonomous and Connected Vehicles

Hassan, Zohaib; Mehmood, Amjad; Maple, Carsten; Khan, Muhammad Altaf; Aldegheishem, Abdulaziz

doi:10.1109/access.2020.3034327

Cited by 42 publications

(21 citation statements)

References 53 publications

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“…To evaluate the enhancement in routing performance achieved by SBGM mechanism, we first created the Attack-AODV (original AODV modified to perform the attack) protocol to simulate the smart black and gray hole attack in the network. Then, we compared the proposed approach (SBGM-AODV) with the Attack-AODV, and existing methods, Tyagi and Dembla [19], SVODR [43], Verma et al [12], and IDBA [8] based on packet delivery ratio, throughput, average end-to-end delay, and packet drop percentage.…”

Section: Results Analysis and Performance Comparison In Highway Scenariomentioning

confidence: 99%

“…Figure 13 shows that in the case of Attack-AODV, the average delay is higher because malicious nodes drop data packets fully/selectively. The proposed SBGM outperforms the existing approaches in SVODR [43] and IDBA [8].…”

Section: Average End-to-end Delaymentioning

confidence: 87%

“…From Fig. 14 it is visible that proposed SBGM gives the lowest packet drop of 3.2% when compared to Attack-AODV, and IDBA [8].…”

Section: Packet Dropmentioning

confidence: 97%

“…Hassan et al [8] introduced a blackhole attack detection scheme for autonomous vehicles in VANET. In this scheme, the attack is determined based on four parameters: hop count, end-to-end delay, packet delivery ratio, and sequence number.…”

Section: Threshold-based Techniquesmentioning

confidence: 99%

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Detection and Mitigation of Smart Blackhole and Gray Hole Attacks in VANET Using Dynamic Time Warping

Krishnan

Kumar

2021

Wireless Pers Commun

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VANET topology is highly dynamic, wherein the vehicles frequently move across locations. Due to the continually changing topology and lack of security infrastructure, routing protocols in VANET are vulnerable to several attacks. In this paper, we focus on the black hole and the gray hole attacks due to its severity. In black hole and gray hole attacks, the attacker gains access to the wireless network and drops the received packets fully/ selectively that impacts on the safety applications of VANET. This paper presents a novel security approach called Smart Blackhole and Gray hole Mitigation (SBGM) to detect and mitigate both black hole and gray hole nodes in VANET using a time series analysis of the dropped packets of each node. The computation of the packet drop distance threshold based on Dynamic Time Warping improves the detection accuracy in SBGM. We assess the performance of SBGM using AODV and OLSR routing protocols under low-dense and high-dense traffic scenarios in terms of Packet Delivery Ratio, Throughput, Average Endto-End Delay, and Packet Drop percentage. From the experimental results, it is evident that the proposed SBGM outperforms the existing techniques in detecting the black and gray hole attacks. The proposed SBGM achieves a detection rate of 99.87% in highway scenarios and 99.68% in urban scenarios.

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Section: Results Analysis and Performance Comparison In Highway Scenariomentioning

confidence: 99%

Section: Average End-to-end Delaymentioning

confidence: 87%

“…From Fig. 14 it is visible that proposed SBGM gives the lowest packet drop of 3.2% when compared to Attack-AODV, and IDBA [8].…”

Section: Packet Dropmentioning

confidence: 97%

Section: Threshold-based Techniquesmentioning

confidence: 99%

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Detection and Mitigation of Smart Blackhole and Gray Hole Attacks in VANET Using Dynamic Time Warping

Krishnan

Kumar

2021

Wireless Pers Commun

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“…Over time, various routing protocols and security mechanisms have been developed [18]. Out of these, the ad hoc on-demand distance vector (AODV) [19] was found to be one of the most famous and commonly used routing protocols in VANETs [20,21]. AODV is also known as a demand-driven protocol since it discovers a new route only when it is required, rather than in advance.…”

Section: Introductionmentioning

confidence: 99%

An Efficient Dynamic Solution for the Detection and Prevention of Black Hole Attack in VANETs

Malik

Khan

Faisal

et al. 2022

Sensors

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Rapid and tremendous advances in wireless technology, miniaturization, and Internet of things (IoT) technology have brought significant development to vehicular ad hoc networks (VANETs). VANETs and IoT together play a vital role in the current intelligent transport system (ITS). However, a VANET is highly vulnerable to various security attacks due to its highly dynamic, decentralized, open-access medium, and protocol-design-related concerns. Regarding security concerns, a black hole attack (BHA) is one such threat in which the control or data packets are dropped by the malicious vehicle, converting a safe path/link into a compromised one. Dropping data packets has a severe impact on a VANET’s performance and security and may cause road fatalities, accidents, and traffic jams. In this study, a novel solution called detection and prevention of a BHA (DPBHA) is proposed to secure and improve the overall security and performance of the VANETs by detecting BHA at an early stage of the route discovery process. The proposed solution is based on calculating a dynamic threshold value and generating a forged route request (RREQ) packet. The solution is implemented and evaluated in the NS-2 simulator and its performance and efficacy are compared with the benchmark schemes. The results showed that the proposed DPBHA outperformed the benchmark schemes in terms of increasing the packet delivery ratio (PDR) by 3.0%, increasing throughput by 6.15%, reducing the routing overhead by 3.69%, decreasing the end-to-end delay by 6.13%, and achieving a maximum detection rate of 94.66%.

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Internet of Things security framework based on near field communication with Otway Rees protocol

Jaber

Yussof

Ali³

et al. 2022

Trans Emerging Tel Tech

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Internet of Things (IoT) devices are crucial in different industries because they provide high‐functioning services to the IoT network connectivity. The IoT devices collect sensitive data, which comes under potential risk while transmitting data from one location to another. The data transmission is performed using various communication protocols that give security to the data. The intermediate attacks such as jamming, collision, flooding, worm‐hole, black‐hole and so forth create several security‐related issues. These intermediate attacks affect data privacy, trust, user identity, which completely affects the IoT device performance. So, this article introduces the near field communication (NFC) protocol with the Otway Rees protocol for making the secure communication process. In IoT applications based on short‐range communication, intermediate attacker issues have been reduced by combining NFC protocol features with Otway Rees protocol features. The NFC protocol provides baseline security trustworthiness while making the communication in the IoT environment cost‐effective. IoT communication is protected while cost‐effective using the security model, ensuring data integrity and confidentiality. In addition to this, the user and servers are authenticated for every session, which provides data security. Moreover, the discussed system is implemented using the NS2 simulation tool, ensuring security and trust with minimum complexity. Even in abnormal traffic conditions, our proposed method resulted in data transmission speeds (up to 289 Kb/s), and this feature can improve processing times.

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Intelligent Detection of Black Hole Attacks for Secure Communication in Autonomous and Connected Vehicles

Cited by 42 publications

References 53 publications

Detection and Mitigation of Smart Blackhole and Gray Hole Attacks in VANET Using Dynamic Time Warping

Detection and Mitigation of Smart Blackhole and Gray Hole Attacks in VANET Using Dynamic Time Warping

An Efficient Dynamic Solution for the Detection and Prevention of Black Hole Attack in VANETs

Internet of Things security framework based on near field communication with Otway Rees protocol

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