Optimizing packet routing and security in MANETs with the H-MAntnetSVM algorithm for energy efficiency and blackhole detection

Abstract

With increasing use of mobile adhoc networks (MANETs) in various applications, the demand for powerful routing protocols has also surged to cater for possible failures or security threats within the network. The operation of efficient packet routing proves highly essential in maintaining reliable communication in MANETs. Energy efficiency plays a crucial role in determining the suitability of a routing technique in MANETS. Packet transmission can be threatened by many types of attacks as Black Hole, gray hole, and sybil attacks. This research proposes a novel hybrid Antnet and Support Vector Machine-The H-MAntnetSVM routing algorithm for energy-efficient routing and Black Hole detection of optimal routing solution. It is basically an adaptive machine learning algorithm that makes the overall network function more effectively in shifting scenarios. The Antnet protocol increases energy usage and provides effective packet routing, while the integration of SVM identifies alibes and basically isolates them so that they do not disturb the routing process. The results obtained with the proposed method show 92.31 % accuracy in detecting the Black Hole attack and 75 % improvement in throughput along with 13.34 % enhancement in the packet delivery ratio. This gives a prominent development in terms of network performance and safety against Black Hole threats.