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              <text>Group Key Management Techniques forSecure Load Balanced Routing Model</text>
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              <text>Ad hoc networks; Cryptography; Group key; Wireless sensors</text>
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              <text>Remote sensor organizations (WSNs) assume a vital part in giving ongoing information admittance to IoT applications. Be that as it may, open organization, energy limitation, and absence of brought together organization make WSNs entirely defenseless against different sorts of pernicious assaults. In WSNs, recognizing vindictive sensor gadgets and dispensing with their detected data assume a vital part for strategic applications. Standard cryptography and confirmation plans cannot be straightforwardly utilized in WSNs on account of the asset imperative nature of sensor gadgets. In this manner, energy productive and low idleness procedure is needed for limiting the effect of malignant sensor gadgets. In this research work presents a secured and burden balanced controlling contrive for heterogeneous bunch-based WSNs. SLBR shows a predominant trust-based security metric that beats the issue when sensors proceed to influence from extraordinary to terrible state and the other way around; besides, SLBR alters stack among CH. In this way, underpins fulfilling superior security, allocate transmission, and vitality efficiency execution. Trials are driven to calculate this presentation of developed SLBR demonstrate over existing trust-based controlling show, particularly ECSO. The result accomplished appears SLBR demonstrate fulfills favored execution over ECSO as distant as vitality capability (i.e., arrange lifetime considering to begin with sensor contraption downfall and total sensor contraption passing), correspondence overhead, throughput, allocate planning idleness, and harmful sensor contraption mis-classification rate and recognizable verification.  2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.</text>
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              <text>Bondada P.; Samanta D.</text>
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              <text>Studies in Computational Intelligence, Vol-1029, pp. 65-76.</text>
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              <text>&lt;a href="https://doi.org/10.1007/978-981-19-0489-9_6" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1007/978-981-19-0489-9_6&lt;/a&gt;
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              <text>Bondada P., Dayananda Sagar Research Foundation, University of Mysore (UoM), Karnataka, Mysore, India; Samanta D., Dayananda Sagar Research Foundation, University of Mysore (UoM), Karnataka, Mysore, India, Department of Computer Science, CHRIST Deemed to be University, Bengaluru, India</text>
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