| Autor: |
Vardhan, G. J., Manikavelan, D., Narendran, R |
| Předmět: |
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| Zdroj: |
AIP Conference Proceedings; 2024, Vol. 3161 Issue 1, p1-6, 6p |
| Abstrakt: |
The focus of this study lies in assessment of Hidden Markov Model in User Authentication and compared over accuracy of Support Vector Machine algorithm to increase the security of client authentication. This research study utilizes a dataset of 4000 tuples, known as the keystroke-dynamics dataset. The research project includes using two algorithms, Novel HMM (N=10) and SVM (N=10). ClinCalc software was used to calculate the iterations size for each group, which was set at 10 with a pretest power value of 0.8 and a significance threshold α=0.05. The independent sample t-test yielded a statistically significant result with a significance level of 0.000 (p<0.05), Indicates a statistically significant distinction between the two algorithms. Based on the results, the novel HMM method (84.76% accuracy) has significantly higher mean accuracy compared to SVM (71.61%). When compared to HMM performs significantly better than the Decision tree. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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