VANSec Attack Resistant VANETs Security Algorithm in terms of Trust Computation Error and Normalized Routing Overhead
VANET is an application and subclass of MANETs, a quickly maturing, promising, and emerging technology these days. VANETs establish communication among vehicles (V2V) and roadside infrastructure (V2I). As vehicles move with high speed, hence environment and topology change with time. There is no optimum routing protocol which ensures full-pledge on-time delivery of data to destination nodes, and an absolutely optimum scheme design for flawless packet exchange is still a challenging task. In VANETs, accurate and on-time delivery of fundamental safety alert messages (FSAMs) is highly important to withstand against maliciously inserted security threats affectively. In this paper, we have presented a new security-aware routing technique called VANSec. The presented scheme is more immune and resistive against different kinds of attacks and thwarts malicious node penetration attempts to the entire network. It is basically based on trust management approach. The aim of the scheme is to identify malicious data and false nodes. The simulation results of VANSec are compared with already existing techniques called trust and LT in terms of trust computation error (TCE), end-to-end delay (EED), average link duration (ALD), and normalized routing overhead (NRO). In terms of TCE, VANSec is 11.6% and 7.3% efficient than LT and trust, respectively, while from EED comparison we found VANSec to be 57.6% more efficient than trust and 5.2% more efficient than LT. Similarly, in terms of ALD, VANSec provides 29.7% and 7.8% more stable link duration than trust and LT do, respectively, and in terms of NRO, VANSec protocol has 27.5% and 14% lesser load than that of trust and LT, respectively.
open access article
Citation : Ahmed, S., Rehman, M., Ishtiaq, A., Khan, S., Ali, A. and Begum, S. (2018) VANSec: Attack-Resistant VANET Security Algorithm in Terms of Trust Computation Error and Normalized Routing Overhead. Journal of Sensors, 2018, 6576841.
ISSN : 1687-7268
Research Institute : Cyber Technology Institute (CTI)
Peer Reviewed : Yes