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The Scientific World Journal
Volume 2016, Article ID 3596345, 12 pages
Research Article

Angle and Context Free Grammar Based Precarious Node Detection and Secure Data Transmission in MANETs

1Department of Information Technology, Anna University, Chennai, Tamil Nadu 600025, India
2Department of Computer Science and Engineering, Adhiparasakthi College of Engineering, Vellore, Tamil Nadu 603319, India
3Department of Computer Science, College of Computer Science, King Khalid University, Abha 62529, Saudi Arabia
4Department of Electronics and Communication Engineering, PRIST University, Thanjavur, Tamil Nadu 613403, India

Received 5 August 2015; Accepted 12 November 2015

Academic Editor: Juan M. Corchado

Copyright © 2016 Anitha Veerasamy et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Growing attractiveness of Mobile Ad Hoc Networks (MANETs), its features, and usage has led to the launching of threats and attacks to bring negative consequences in the society. The typical features of MANETs, especially with dynamic topology and open wireless medium, may leave MANETs vulnerable. Trust management using uncertain reasoning scheme has previously attempted to solve this problem. However, it produces additional overhead while securing the network. Hence, a Location and Trust-based secure communication scheme (L&TS) is proposed to overcome this limitation. Since the design securing requires more than two data algorithms, the cost of the system goes up. Another mechanism proposed in this paper, Angle and Context Free Grammar (ACFG) based precarious node elimination and secure communication in MANETs, intends to secure data transmission and detect precarious nodes in a MANET at a comparatively lower cost. The Elliptic Curve function is used to isolate a malicious node, thereby incorporating secure data transfer. Simulation results show that the dynamic estimation of the metrics improves throughput by 26% in L&TS when compared to the TMUR. ACFG achieves 33% and 51% throughput increase when compared to L&TS and TMUR mechanisms, respectively.