Detection and Prevention of Black Hole Attack in VANET Using Secured AODV Routing Protocol

Lachdhaf, Salim; Mazouzi, Mohammed; Abid, Mohamed

doi:10.5121/csit.2017.71503

Cited by 11 publications

(5 citation statements)

References 8 publications

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“…The test results in this study explain that the proposed protocol successfully addresses black hole attack with PDR performance, end-to-end delay, routing overhead, and throughput that is nearly identical to traditional AODV. Additionally, the proposed protocol has a high detection rate at both high and low node density [6]. However, the research has not shown the performance of SAODV in dealing with black hole attack with variation in number of packets sent.…”

Section: Introductionmentioning

confidence: 89%

“…According to prior research that assessed the performance of AODV on VANET, the fall in packet delivery ratio (PDR) on the performance of AODV in black hole attack reached 60% [6]. Therefore, a method that capable of protecting VANET from black hole attack is needed.…”

Section: Issn 2355-3286mentioning

confidence: 99%

“…This causes the source node to ignore RREP messages from other intermediate nodes and choose the route with the attacker node on it. Attacker node will drop the data that get through it, causing the data to never reach the destination node [6].…”

Section: Black Hole Attacksmentioning

confidence: 99%

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Black Hole Detection Using Modified Sequence Number in Vehicular Ad-hoc Network

Julda,

Kartikasari,

Primananda

2022

ULTIMA Computing

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Vehicular Ad-hoc Network (VANET) is a type of wireless network with Dedicated Short-Range Communication (DSRC) that enables communication between vehicles (V2V) and communication between vehicles to infrastructure around them (V2I). VANET has several security requirements to consider in order to maintain the network functionality. Availability is the most important security requirement due to its responsibility of maintaining the functionality of the network, attack on availability may cause the lack of availability and reduce the efficiency of VANET. One of the attack that threat the availability of VANET is black hole. In this paper, we address the problem of black hole attack in VANET, using Modified Sequence Number (MSN) as a detection method. The simulation is performed using NS-2 as a simulator and AODV as a routing protocol. Detection Rate (DR) and False Alarm Rate (FAR) are used to evaluate the performance of MSN algorithm in detecting black hole attack. Evaluation with variation in the number of CBR packets shows that MSN algorithm successfully detects black hole attacks with DR values reaching 69.0909% at 10 CBR packets and FAR values reaching 0.0037 at 20 CBR packets. We also evaluate the performance of MSN algorithm with variations of node density. The evaluation shows that MSN algorithm successfully detects black hole attack with DR values reaching 100% with a density of 10 and 20 nodes, with the percentage of FAR values reaching 0% in all numbers of node density.

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Section: Introductionmentioning

confidence: 89%

Section: Issn 2355-3286mentioning

confidence: 99%

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Black Hole Detection Using Modified Sequence Number in Vehicular Ad-hoc Network

Julda,

Kartikasari,

Primananda

2022

ULTIMA Computing

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“…An approach for detecting and preventing blackhole attacks in VANET applies to cooperative black hole attacks and gray hole attacks [9]. The solution suggested in this approach makes minor changes to the AODV protocol's RREQ message format using CRC-32.…”

Section: Threshold-based Techniquesmentioning

confidence: 99%

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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“…Thus, using QRT, routes and nodes that are considered suspicious are ignored for routing. Lachdhaf et al [14] proposed a strategy to detect and prevent isolated and cooperative black hole attacks using the AODV routing protocol. In the presented method, the Cyclic Redundancy Check 32 bits (CRC-32) is used to store the address of the destination in the RREQ message.…”

Section: Introductionmentioning

confidence: 99%

Security Improvements for Connected Vehicles Position-Based Routing

Silva¹

2021

Int. j. commun. netw. inf. secur.

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The constant growing on the number of vehicles is increasing the complexity of traffic in urban and highway environments. It is paramount to improve traffic management to guarantee better road usage and people’s safety. Through efficient communications, Vehicular Ad hoc Networks (VANETs) can provide enough information for traffic safety initiatives, daily traffic data processing, and entertainment information. However, VANETs are vulnerable to malicious nodes applying different types of net-work attacks, where an attacker can, for instance, forge its position to receive the data packet and drop the message. This can lead vehicles and authorities to make incorrect assumptions and decisions, which can result in dangerous situations. Therefore, any data dissemination protocol designed for VANET should consider security issues when selecting the next-hop forwarding node. In this paper, we propose a security scheme designed for position-based routing algorithms, which analyzes nodes position, transmission range, and hello packet interval. The scheme deals with malicious nodes performing network attacks, faking their positions forcing packets to be dropped. We used the Simulation of Urban MObility (SUMO) and Network Simulator-version 3 (NS-3) to compare our proposed scheme integrated with two well-known position-based algorithms. The results were collected in an urban Manhattan grid environment varying the number of nodes, the number of malicious nodes, as well as the number of source-destination pairs. The results show that the proposed security scheme can successfully improve the packet delivery ratio while maintaining low average end-to-end delay of the algorithms.

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Detection and Prevention of Black Hole Attack in VANET Using Secured AODV Routing Protocol

Abstract: ABSTRACT

Cited by 11 publications

References 8 publications

Black Hole Detection Using Modified Sequence Number in Vehicular Ad-hoc Network

Black Hole Detection Using Modified Sequence Number in Vehicular Ad-hoc Network

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

Security Improvements for Connected Vehicles Position-Based Routing

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