Dynamic Tree Routing Protocol with Convex Hull Optimization for Optimal Routing Paths

Anitha, Cuddapah; Sivakumar, C.; Vani, Rajasekar; Velliangiri, S.

doi:10.1109/icears53579.2022.9752367

Cited by 2 publications

(1 citation statement)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Internal attacks are more severe as compared to external attacks and it is critical to develop such protocols that can detect and identify the attackers within the IoT [2]. Some of the challenges of spoofing attacks are communication of false information within the IoT system, vulnerability of IoT devices, compromising the decision-making process, manipulation of the operation of the IoT system [3], repeated routing loops [4,5] passive listening of the communication and showing itself as a legitimate device within the IoT pool of devices to operate malicious activities [6], and severeness of spoofing attack on time-dependent IoT devices such as robotic arms in the industry [7].…”

Section: Introductionmentioning

confidence: 99%

Development of a Model for Spoofing Attacks in Internet of Things

et al. 2022

View full text Add to dashboard Cite

Internet of Things (IoT) allows the integration of the physical world with network devices for proper privacy and security in a healthcare system. IoT in a healthcare system is vulnerable to spoofing attacks that can easily represent themselves as a legal entity of the network. It is a passive attack and can access the Medium Access Control address of some valid users in the network to continue malicious activities. In this paper, an algorithm is proposed for detecting spoofing attacks in IoT using Received Signal Strength (RSS) and Number of Connected Neighbors (NCN). Firstly, the spoofing attack is detected, located and eliminated through Received Signal Strength (RSS) in an inter-cluster network. However, the RSS is not useful against intra-cluster spoofing attacks and therefore the NCN is introduced to detect, identify and eliminate the intra-cluster spoofing attack. The proposed model is implemented in Network Simulator 2 (NS-2) to compare the performance of the proposed algorithm in the presence and absence of spoofing attacks. The result is that the proposed model increases the detection and prevention of spoofing.

show abstract