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- W2359969261 abstract "Exactly assessing the security risk of a network is the key to improving the security level of a network.The Hidden Markov Model based real time network security risk quantification method can get the risk value and evaluate the threat dynamically and timely,whose input is Intrusion Detection System alerts.But it's complex to configure and it tends to acquire errors.These faults are resolved in an optimized method presented in this paper.The optimized method improves the accuracy and simplifies the configuration with automatically calculate matrixes in HMM.First,it combines IDS alert,host information and asset value to define the threat of an attack.The threat is more accurate than the alert and is applied to classify attacks.Second,the new method uses the genetic algorithm to generate the HMM status transformation matrix and observation matrix automatically,and it defines risk description rules as the genetic algorithm optimization target.The risk description rule provides a formal method to characterize the network security risk,and the rule base can be used as the test criterion for other risk assessment methods.At last,the comparative experiment and DARPA 2000 data experiment obtain good results and prove that this method is practical to measure the risk of network security." @default.
- W2359969261 created "2016-06-24" @default.
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- W2359969261 date "2009-01-01" @default.
- W2359969261 modified "2023-09-25" @default.
- W2359969261 title "An Optimized Method for Real Time Network Security Quantification" @default.
- W2359969261 hasPublicationYear "2009" @default.
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