@Article{cmc.2020.012255,
AUTHOR = {Ganeshan Keerthana, Panneerselvam Anandan, Nandhagopal Nachimuthu},
TITLE = {Robust Hybrid Artificial Fish Swarm Simulated Annealing Optimization Algorithm for Secured Free Scale Networks against Malicious Attacks},
JOURNAL = {Computers, Materials \& Continua},
VOLUME = {66},
YEAR = {2021},
NUMBER = {1},
PAGES = {903--917},
URL = {http://www.techscience.com/cmc/v66n1/40487},
ISSN = {1546-2226},
ABSTRACT = {Due to the recent proliferation of cyber-attacks, highly robust wireless
sensor networks (WSN) become a critical issue as they survive node failures.
Scale-free WSN is essential because they endure random attacks effectively.
But they are susceptible to malicious attacks, which mainly targets particular significant nodes. Therefore, the robustness of the network becomes important for
ensuring the network security. This paper presents a Robust Hybrid Artificial Fish
Swarm Simulated Annealing Optimization (RHAFS-SA) Algorithm. It is introduced for improving the robust nature of free scale networks over malicious
attacks (MA) with no change in degree distribution. The proposed RHAFS-SA
is an enhanced version of the Improved Artificial Fish Swarm algorithm (IAFSA)
by the simulated annealing (SA) algorithm. The proposed RHAFS-SA algorithm
eliminates the IAFSA from unforeseen vibration and speeds up the convergence
rate. For experimentation, free scale networks are produced by the Barabási–
Albert (BA) model, and real-world networks are employed for testing the outcome on both synthetic-free scale and real-world networks. The experimental
results exhibited that the RHAFS-SA model is superior to other models interms
of diverse aspects.},
DOI = {10.32604/cmc.2020.012255}
}