Energy efficient random forest classifier-based secure routing for opportunistic internet of things Online publication date: Wed, 29-May-2024
by Sanjay K. Dhurandher; Nisha Kandhoul; Isaac Woungang; Han-Chieh Chao
International Journal of Ad Hoc and Ubiquitous Computing (IJAHUC), Vol. 46, No. 2, 2024
Abstract: Opportunistic internet of things (OppIoT) is a class of opportunistic networks, where the data are transmitted in a broadcast manner and shared among the nodes (i.e., IoT devices and human communities' devices) through opportunistic contact. In such networks, taking into consideration the energy level of each node while performing the routing of data is of utmost importance. This paper proposes an energy-efficient secure routing protocol that uses a random forest classifier (called ESRFCSec) for device behaviour predictions and for protecting the OppIoT network against packet collusion attacks. Through simulations, ESRFCSec is shown to achieve a prediction accuracy of 97.97%. It is also shown to be superior to three benchmark routing schemes in terms of node's residual energy, delivery probability, average latency, number of dead nodes, and number of dropped packets.
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