A Distinguished Method for Network Intrusion Detection using Random Initialized Viterbi Algorithm in Hidden Markov Model
Intrusion Detection System (IDS) is a system that surveils the dubious network activity. There are several approaches which deal with intrusion detection and cyber-attack detection, but the most optimal IDS would be the one which can predict the upcoming threats along with detecting the present atta...
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| Vydané v: | 2022 OITS International Conference on Information Technology (OCIT) s. 273 - 277 |
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| Hlavní autori: | , , |
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| Jazyk: | English |
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01.12.2022
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| Abstract | Intrusion Detection System (IDS) is a system that surveils the dubious network activity. There are several approaches which deal with intrusion detection and cyber-attack detection, but the most optimal IDS would be the one which can predict the upcoming threats along with detecting the present attacks. The Machine Learning probabilistic models work remarkably in prediction of threats among these models, Hidden Markov Model (HMM) outperforms all other models. HMM is widely used in cryptanalysis, gene prediction, computational linguistic, speech analysis as well as its synthesis and network attacks detection and prediction. In this paper, we have proposed a distinct methodology using Viterbi algorithm of HMM which is initialized with the random parameter. Our methodology significantly upsurges the detection accuracy of the current state along with all states, it also enhances the prediction accuracy of the next feasible state when compared to existing approaches. |
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| AbstractList | Intrusion Detection System (IDS) is a system that surveils the dubious network activity. There are several approaches which deal with intrusion detection and cyber-attack detection, but the most optimal IDS would be the one which can predict the upcoming threats along with detecting the present attacks. The Machine Learning probabilistic models work remarkably in prediction of threats among these models, Hidden Markov Model (HMM) outperforms all other models. HMM is widely used in cryptanalysis, gene prediction, computational linguistic, speech analysis as well as its synthesis and network attacks detection and prediction. In this paper, we have proposed a distinct methodology using Viterbi algorithm of HMM which is initialized with the random parameter. Our methodology significantly upsurges the detection accuracy of the current state along with all states, it also enhances the prediction accuracy of the next feasible state when compared to existing approaches. |
| Author | Shukla, Pratyush Chaudhari, Narendra S P, Sharmila S |
| Author_xml | – sequence: 1 givenname: Sharmila S surname: P fullname: P, Sharmila S email: phd2201101012@iiti.ac.in organization: Indian Institute of Technology,Department of Computer Science and Engg.,Indore,Madhya Pradesh,India – sequence: 2 givenname: Pratyush surname: Shukla fullname: Shukla, Pratyush email: pratyush19shukla@gmail.com organization: Jaypee University of Engineering and Technology,Department of Computer Science and Engg.,Guna,India – sequence: 3 givenname: Narendra S surname: Chaudhari fullname: Chaudhari, Narendra S email: nsc@iiti.ac.in organization: Indian Institute of Technology,Department of Computer Science and Engg.,Indore,Madhya Pradesh,India |
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| Snippet | Intrusion Detection System (IDS) is a system that surveils the dubious network activity. There are several approaches which deal with intrusion detection and... |
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| StartPage | 273 |
| SubjectTerms | Computational modeling Hidden Markov Model Hidden Markov models Intrusion detection system Machine learning Network attack prediction Network intrusion detection pattern recognition Predictive models Speech analysis Viterbi algorithm Viterbi decoding algorithm |
| Title | A Distinguished Method for Network Intrusion Detection using Random Initialized Viterbi Algorithm in Hidden Markov Model |
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