Detection of black hole attack in wireless sensor network using UAV

Motamedi, Maryam; Yazdani, Nasser

doi:10.1109/ikt.2015.7288749

Cited by 20 publications

(7 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Motamedi and Nasser [65] developed a method using Unmanned Aerial Vehicles (UAV) to take the place of mobile agents and applied a dynamic threshold to determine whether the detected node is a black hole node. This method was applied in a stationary network.…”

Section: Black Hole Attack (Bha)mentioning

confidence: 99%

Data Collection for Security Measurement in Wireless Sensor Networks: A Survey

Xie

Yan

Yao

et al. 2019

IEEE Internet Things J.

154

View full text Add to dashboard Cite

Wireless Sensor Network (WSN) is an indispensible part of IoT that has been applied in many fields to monitor environments and collect data from surroundings. However, WSNs are highly susceptible to attacks due to its unique characteristics: large-scale, self-organization, dynamic topology and constrained resources. A number of systems have been proposed to effectively detect varieties of attacks in WSNs. However, most previous surveys on WSN attacks focus on detection methods for only one or two types of attacks and lack detailed performance analysis. Additionally, the literature lacks comprehensive studies on security-related data (in short security data) collection in WSNs. In this paper, we first provide an overview of WSNs and classify the attacks in WSNs based on protocol stack layers. For the purpose of WSN security measurement, we then research attack detection methods of eleven mainstream attacks. We extract security data that play an important role for detecting security anomaly towards security measurement. We further elaborate the advantages and disadvantages of the existing detection methods based on a number of evaluation criteria. Finally, we highlight a number of open problems in this research field based on our thorough survey and conclude this paper with possible future research directions.

show abstract

Section: Black Hole Attack (Bha)mentioning

confidence: 99%

Data Collection for Security Measurement in Wireless Sensor Networks: A Survey

Xie

Yan

Yao

et al. 2019

IEEE Internet Things J.

154

View full text Add to dashboard Cite

show abstract

“…On the other hand, in the Black hole attack, malicious nodes send a route reply message to the sender in return receive packets from sender node and discard packets instead of forwarding to the destination node. In their research, Motamedi et al [107] show the detection procedure of Black hole attack in WSN using unmanned aerial vehicles (UAVs). Furthermore, Bansal et al [104] discussed the anomaly-based detection on leach protocol in WSN and Kaur and Singh [105] presented a way to identify and mitigate the Black hole attack in WSN.…”

Section: G Routing Attackmentioning

confidence: 99%

Review on Security of Internet of Things Authentication Mechanism

et al. 2019

View full text Add to dashboard Cite

Internet of things (IoT) is considered as a collection of heterogeneous devices, such as sensors, Radio-frequency identification (RFID) and actuators, which form a huge network, enabling non-internet components in the network to produce a better world of services, like smart home, smart city, smart transportation, and smart industries. On the other hand, security and privacy are the most important aspects of the IoT network, which includes authentication, authorization, data protection, network security, and access control. Additionally, traditional network security cannot be directly used in IoT networks due to its limitations on computational capabilities and storage capacities. Furthermore, authentication is the mainstay of the IoT network, as all components undergo an authentication process before establishing communication. Therefore, securing authentication is essential. In this paper, we have focused on IoT security particularly on their authentication mechanisms. Consequently, we highlighted enormous attacks and technical methods on the IoT authentication mechanism. Additionally, we discussed existing security verification techniques and evaluation schemes of IoT authentication. Furthermore, analysis against current existing protocols have been discussed in all parts and provided some recommendation. Finally, the aim of our study is to help the future researcher by providing security issues, open challenges and future scopes in IoT authentication.

show abstract

“…The drawback of this it cannot secure the WMN from intruder purely. Motamedi M [15] introduce the method to detect the black hole attack on the wireless network that cause misfortune of essential information. In this method uses the UAV and SPRT for the better result to detecting the black hole attack.…”

Section: Related Workmentioning

confidence: 99%

A Novel Hybrid and Secure Clustering Black hole Attacks Mitigation Technique in Wireless LAN

Singh¹,

Dhir²

2018

IJET

View full text Add to dashboard Cite

Wireless LAN is a dynamic network with large number of mobile nodes. As the traffic increases over the wireless, it will lead to number of problems like congestion and packet loss. This congestion and packet loss problems occurs due to the attacks in wirel ess LAN.Out of the various attacks black hole attack is most dangerous attack which drops all of the packets received from the source node and which act as a black hole in the universe. In this paper we are providing solution against this attack. We propose a Novel Hybrid and Secure Clustering Black hole Attack Mitigation Technique in Wireless LAN. This technique firstly detects the black hole attack by using threshold values against different parameters, after this clustering approach is used for secure path from source to destination by reducing overhead in the network. Most of existing mechanisms are not as efficient because by isolating black hole attack overhead is increased . A HSBM approach has remarkable advantage over these existing techniques. We simulate the proposed technique by using NS2 simulator and proved that our technique effectively detects the black hole attack in terms of throughput, packet loss, end to end packet delivery ratio, delay.

show abstract

Detection of black hole attack in wireless sensor network using UAV

Cited by 20 publications

References 13 publications

Data Collection for Security Measurement in Wireless Sensor Networks: A Survey

Data Collection for Security Measurement in Wireless Sensor Networks: A Survey

Review on Security of Internet of Things Authentication Mechanism

A Novel Hybrid and Secure Clustering Black hole Attacks Mitigation Technique in Wireless LAN

Contact Info

Product

Resources

About