Real Time Intrusion Prediction based on Optimized Alerts with Hidden Markov Model

2012 ◽  
Vol 7 (2) ◽  
Author(s):  
Alireza Shameli Sendi ◽  
Michel Dagenais ◽  
Masoume Jabbarifar ◽  
Mario Couture
2019 ◽  
Vol 19 (4) ◽  
pp. 396-403 ◽  
Author(s):  
Hyeon-Gu Do ◽  
Seongrim Choi ◽  
Jaemin Hwang ◽  
Ara Kim ◽  
Byeong-Gyu Nam

2006 ◽  
Vol 2006 (1) ◽  
pp. 048085 ◽  
Author(s):  
Jeffrey Schuster ◽  
Kshitij Gupta ◽  
Raymond Hoare ◽  
AlexK Jones

2011 ◽  
Vol 63-64 ◽  
pp. 178-181
Author(s):  
Hong Zhi Liu ◽  
Li Gao

A new method of Quality Control for Information Engineering Surveillance based on Hidden Markov Model (HMM) has been proposed and the related model been built by us. The process of information engineering quality surveillance can be seen as a two-layered random process. The five elements of HMM correspond with the process of quality surveillance through abstracting the characteristics of the surveillance process. Software quality can be estimated under the model. In this paper, we divided the five elements. Therefore, the model was improved from single dimension to multi-dimension, trained by Baum-Welch algorithm. Experimental results show that the proposed model proves to be feasible and real-time when it is used for quality control.


2017 ◽  
Vol 33 (4) ◽  
pp. 843-862 ◽  
Author(s):  
Neha Baranwal ◽  
G. C. Nandi ◽  
Avinash Kumar Singh

2017 ◽  
Vol 112 ◽  
pp. 833-843 ◽  
Author(s):  
Mahdi Washha ◽  
Aziz Qaroush ◽  
Manel Mezghani ◽  
Florence Sedes

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