What is it about?
Behavioral Intrusion Prediction Model on Bayesian Network over Healthcare Infrastructure" addresses the limitations of traditional intrusion detection methods for detecting polymorphic and stealthy malware attacks in production networks. The study proposes a new Predictive Intrusion Model based on a Bayesian Network, utilizing a previously built Feature Selection Model.
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Why is it important?
This is important as existing intrusion detection methods struggle with the polymorphic and stealthy nature of malware attacks. Furthermore classical model requires labeled datasets for training, which are often unavailable in real-world production networks. This model uses unlabeled dataset.
Perspectives
As an author this approach suggest a new unsupervised learning approach focusing on behavioral study to identify traffic patterns. Current stealthy attacks can evade the AV and many signature based detection systems.
Mohammad Hafiz Mohd Yusof
Universiti Teknologi MARA
Read the Original
This page is a summary of: Behavioral Intrusion Prediction Model on Bayesian Network over Healthcare Infrastructure, Computers Materials & Continua, January 2022, Tsinghua University Press,
DOI: 10.32604/cmc.2022.023571.
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