J Wang, M Neil, N Fenton - Computers & Security, 2020 - Elsevier
… We propose using BayesianNetworks (BNs) as an alternative way to implement, extend the FAIR model and eliminate its restrictions, which is described in Section 4 and 7. …
… model with several traditional popular machinelearning methods such as the naive Bayes classifier, logistic regression, support vector machines… -based Bayesiannetwork to classify the …
… Although the complete prevention of any cyberattack is an … By automatically “attacking” existing security systems, ML … of ML models organized in a BayesianNetwork Classifier (BNC) […
… cyber-intrusion (Biringer, Vugrin, & Warren, 2016). This research uses a Bayesiannetwork (BN) to address a range of possible cyber … to mitigate the consequences of a cyber-disruption. …
… The authors proposed a Bayesiannetworkmodel to evaluate and ensure the cybersecurity … to accumulate some information about the target computersecurity ML model. The extracted …
J Bharadiya - European Journal of Technology, 2023 - ajpojournals.org
… tackle a variety of issues in computer and informationsecurity. This paper covers and emphasizes several machine-learning applications in cybersecurity. Machinelearning: One of the …
… between the smart grids sub-systems through dynamic Bayesiannetworks. To capture the patterns in system behavior, the authors proposed the use of a restricted Boltzmann …
… key machinelearning techniques applied in cybersecurity … of using machinelearning techniques for cybersecurity. We … of machinelearning techniques, and how machinelearning …
… In the literature, machinelearning based IDS models / methods have generally obtained … attack detection capability of IDS datasets. In this research, we presented a machinelearning …