2021
DOI: 10.1109/access.2021.3055422
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A Recurrent Reward Based Learning Technique for Secure Neighbor Selection in Mobile AD-HOC Networks

Abstract: Mobile ad-hoc network is an assortment of distinct attribute-based mobile devices that are autonomous and are cooperative in establishing communication. These nodes exploit wireless links for communication that causes injection of the adversaries in the network. Therefore, detection and mitigation of adversaries and anomalies in the network are mandatory to retain its performance. To strengthen this concept, in this article, a novel secure neighbor selection technique using recurrent reward-based learning is i… Show more

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Cited by 38 publications
(11 citation statements)
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“…This technique makes use of a learning approach for understanding the malicious behavior of mobile nodes. Usage of the learning scheme is also observed in Sankaran et al [30], where the selection mechanism of the neighboring mobile node is secured in MANET. The learning scheme is used for reviewing the secure routing consistency.…”
Section: Review Of Literaturementioning
confidence: 83%
“…This technique makes use of a learning approach for understanding the malicious behavior of mobile nodes. Usage of the learning scheme is also observed in Sankaran et al [30], where the selection mechanism of the neighboring mobile node is secured in MANET. The learning scheme is used for reviewing the secure routing consistency.…”
Section: Review Of Literaturementioning
confidence: 83%
“…The MANET consensus mechanism proposes multiple trust predictions based on exchanging group proposals [24]. Trust is defined as an individual's level of trust in any participating node's behavior [25]. Reference [26] Distinguished trust maintenance from several security measures in offering and maintaining security measures and interactions.…”
Section: Related Workmentioning
confidence: 99%
“…On the other side, the present frameworks for assessing each node's trust level in MANET have increasing computational power challenges. Numerous safe and power-aware multihop routing procedures have recently been developed for MANETs, including Hybrid Secure Multipath Routing Protocol (HSMRP) [23], Trust Aware Secure Energy Efficient Hybrid Protocol (TASEEHP) [24], Recurrent Reward-Based Learning (RRBL) [25], and Signcryption Technique (ST) [26]. These practices are highly successful in facing a range of security threats.…”
Section: Related Workmentioning
confidence: 99%
“…Traditional routing and clever machine learning paradigms are inherited by Sankaran et al in the classification of nodes based on their communication patterns. It is possible to build reliable and secure pathways to a destination by thoroughly studying the behavior of the nodes at various communication hop levels [31]. In order to help the optimization process, intelligent computing and decision-making algorithms use present and previous behavior of nodes to identify the adversary.…”
Section: Related Workmentioning
confidence: 99%