A novel machine learning-based attacker detection system to secure location aided routing in MANETs
by R. Suma; B.G. Premasudha; V. Ravi Ram
International Journal of Networking and Virtual Organisations (IJNVO), Vol. 22, No. 1, 2020

Abstract: The proposed work deals with the improvisation of the performance of location-based routing in mobile ad hoc network (MANET). A machine learning-based attacker detection (MLAD) algorithm that uses multipath routing is proposed to facilitate efficient routing even in the presence of attackers. The proposed algorithm adopts the location aided routing (LAR) to optimise the search process and to reduce the search area for new routes in MANETs. Learning automata (LA) is implemented to optimise the path selection and to reduce overhead in the network. Extended identity-base cryptography (EIBC) is used for efficient key management in providing system security. The proposed system implements privacy preserving communication system (PPCS) for maintaining privacy in end-to-end communication. This method decouples the location information from the node's identifier and abstracts the communication happening among nodes. The simulation results of the proposed method reveal its reliability and strength in securing LAR in MANETs.

Online publication date: Mon, 10-Feb-2020

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Networking and Virtual Organisations (IJNVO):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com