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| 005 | 20251125111038.0 | ||
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| 008 | 250506t20232023my a|||fs|||| 000 0 eng d | ||
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_aTHE0010036 (Local) _qHardback |
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_aUMPSA _beng _cUMPSA _erda |
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| 090 | _aPSM .K43 2023 r Bc. | ||
| 100 | 0 |
_aShaesta Khan Sheh Rahman, _eauthor. |
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| 245 | 1 | 0 |
_aExploration of machine learning approach to predictive models on common vulnerabilities and exposure (CVE) dataset / _cShaesta Khan Binti Sheh Rahman |
| 264 | 1 |
_aKuantan Pahang : _bUMPSA, _c2023 |
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| 264 | 4 | _c© 2023 | |
| 300 |
_axiv, 84 pages : _bIllustrations (some colour) ; _e1 CD-ROM. |
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| 336 |
_2rdacontent _atext |
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_2rdamedia _aunmediated |
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| 338 |
_2rdacarrier _avolume |
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_2rda _atext file _bPDF |
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| 500 | _aCenter for Mathematical Sciences | ||
| 502 | _aBachelor of Applied Science In Data Analytics With Honour -- Universiti Malaysia Pahang – 2023 | ||
| 504 | _aIncludes bibliographical references | ||
| 520 | 3 | _aThreat intelligence involves gathering and analysing information on cyber threats to improve organizations' understanding of attackers and enable a faster response to issues. Hackers are becoming more sophisticated and can exploit vulnerabilities, leading to various security risks. This study aims to predict Common Vulnerability and Exposure by analysing different models and methods, enhancing proactive vulnerability management, and strengthening cybersecurity practices. The dataset used in this study is obtained from Kaggle. Unsupervised machine learning methods is utilised which is clustering algorithms. Clustering algorithms like K-means, Gaussian Naive Bayes, and DBSCAN are utilized for predictive modelling. In effectively determining the class labels or results of the data it was trained on or tested against, the Gaussian Naive Bayes model achieved an accuracy rate of 99.79% among these models. The goal is to provide a proof of concept to Cybersecurity Malaysia, offering insights into the CVE model. | |
| 610 | 2 | 0 |
_aCenter for Mathematical Sciences _xDissertations |
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_aUniversities and colleges _xDissertations |
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| 650 | 0 |
_aFinal Year Report _xDissertations |
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_2lcc _cPSM |
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