Open AccessMalware Risk Analysis on the Campus Network with Bayesian Belief Network
Author(s) -
Aliyu Mohammed,
Haitham A. Jamil,
Sulaiman Mohd Nor,
Muhammad Nadzir Marsono
Publication year - 2013
Publication title -
international journal of network security and its applications/international journal of network security and applications
Language(s) - English
Resource type - Journals
eISSN - 0975-2307
pISSN - 0974-9330
DOI - 10.5121/ijnsa.2013.5409
Subject(s) - bayesian network , computer science , malware , network analysis , campus network , bayesian probability , artificial intelligence , data science , machine learning , computer security , engineering , electrical engineering
A security network management system is for providing clear guidelines on risk evaluation and assessmentfor enterprise networks. The threat and risk assessment is conducted to safeguard enterprise networkservices to maintain system confidentiality, integrity, and availability through effective control strategies.In this paper, based on our previous work in analyzing integrated information security management andmalware propagation on the campus network through mathematical modelling, we proposed BayesianBelief Network with inference level indicator to enable the decision maker to understand and provideappropriate mitigation decisions on the risks posed. We experimentally placed monitoring sensors on thecampus network that gives the threat alert priority levels and magnitude on the vulnerable informationassets. These methods will give a direction on the belief inferred due to malware prevalence on theinformation security assets for better understanding