Access control is a unique platform in network security as it is a medium for establishing integrity, confidentiality and availability of information in network system. Computer network environment grows daily with increase in information dissemination and user identities which invariably has opened gaps for threats. However, these threats affect computing network immensely by causing harm and loss to organizations. An efficient network security mechanism is therefore required to protect computing information from threats. Several network access control models have been proposed such as identity-based access control, location-based access control, bandwidth management access control among others. However, earlier access control models lack reliability, sustainability, dynamic and adaptive features on real time access request. Therefore, the Monte Carlo Game Theoretic Network Access Control (MCGT-NAC) model proposes a real time control platform for optimal decision making. In this research, ten (10) entities among which are Patch Status, Registration and Location were selected to identify the user’ status in real time at a given instance with decision tree processes of selection, expansion, simulation and backpropagation. Consequently, decision optimization was achieved by traversing through the entities and obtaining best outcome through series of iterations.

Authors: Oluwabunmi Y.Ogunlola, Otasowie Owolafe, Aderonke F. Thompson, Boniface Kayode Alese

Published in: International Conference for Internet Technology and Secured Transactions (ICITST-2021)

  • Date of Conference: 7-9 December 2021
  • DOI: 10.20533/ICITST.2021.0006
  • ISBN: 978-1-913572-39-6
  • Conference Location: Virtual (London, UK)