Abstract

Nodes in a mobile computing system are vulnerable to clone attacks due to their mobility. In such attacks, an adversary accesses a few network nodes, generates replication, then inserts this replication into the network, potentially resulting in numerous internal network attacks. Most existing techniques use a central base station, which introduces several difficulties into the system due to the network's reliance on a single point, while other ways generate more overhead while jeopardising network lifetime. In this research, an intelligent double hashing-based clone node identification scheme was used, which reduces communication and memory costs while performing the clone detection procedure. The approach works in two stages: in the first, the network is deployed using an intelligent double hashing procedure to avoid any network collisions and then in the second, the clone node identification procedure searches for any clone node in the network. This first phase verifies the node prior to network deployment, and then, whenever a node wants to interact, it executes the second level of authentication. End-to-end delay, which is bound to increase owing to the injection of clone nodes, and packet loss, which is reduced by the double hashing technique, were used to evaluate the performance of the aforementioned approach.

Highlights

  • Mobile computing is extensively used in many industries where a fast and efficient response is essential

  • Several clone node detection techniques and fault detection techniques have been proposed in the literature, with the majority of them focusing on the node’s location, because each node in the network has a unique node id and spatial coordinates, and if two different nodes in the network claim the same node id but with different spatial coordinates, it clearly indicates the presence of a clone node and its attack

  • Mobile computing systems are susceptible to a wide range of attacks from attackers

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Summary

Introduction

Mobile computing is extensively used in many industries where a fast and efficient response is essential. The use of mobile computing in the system has numerous constraints that must be addressed, such as the nodes in such systems having resource issues such as low cost, battery, bandwidth, memory, and so on, which must be handled in such a way that it does not directly affect network health. Nodes in such a network communicate with one another and with a base station, emphasising the importance of all nodes’ legitimacy [1].

Related Work
System Model and Assumptions
Network Deployment Phase
Clone Node Detection Phase
Simulation Parameters
Method
Findings
Conclusion
Full Text
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