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2203421 |
| 024 |
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|3 10.54633/2333-023-049-010
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| 041 |
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|a eng
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| 044 |
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|b العراق
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| 100 |
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|9 772667
|a Al-Hammash, Mohammed Saeed Hashim
|e Author
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| 245 |
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|a Enhancement Methods of Intrusion Detection Systems Using Artificial Intelligence Methods "TLBO" Algorithm
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| 260 |
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|b جامعة ميسان - كلية التربية الأساسية
|c 2024
|g آذار
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| 300 |
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|a 105 - 112
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| 336 |
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|a بحوث ومقالات
|b Article
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| 520 |
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|b Many methods have been used to build intrusion detection system based on the objective to be achieved in the prescribed manner. Hybrid methods (multiple methods) usually give better results and accuracy. The recent developments and popularization of network & information technologies have necessitated the need for network information security. Human-based smart intrusion detection systems (IDSs) are built with the capability to either warn or intercept network intrusion; this is not possible with the conventional network security systems. However, most information security studies have focused on improvement of the effectiveness of smart network IDSs. This study used TLBO algorithm as a feature selection algorithm to choose the best subset features and SVM classifier to classify the packet if it is intrusion or normal packet, two machine learning datasets used to test the proposed algorithm, the results show that the proposed algorithm perform better than many of the existing work in IDS.
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| 653 |
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|a كشف التسلل
|a تقنيات المعلومات
|a أمن المعلومات
|a الذكاء الاصطناعي
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| 692 |
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|b IDS
|b TLBO
|b SVM
|b Feature Selection
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| 700 |
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|9 772669
|a Maarouf, Haitham
|e Co-Author
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| 773 |
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|4 التربية والتعليم
|4 العلوم الإنسانية ، متعددة التخصصات
|6 Education & Educational Research
|6 Humanities, Multidisciplinary
|c 010
|e Maisan Journal of Academic Studies
|f Maǧallaẗ Mīsān li-l-dirāsāt al-akādīmiyyaẗ
|l 049
|m مج23, ع49
|o 2333
|s مجلة ميسان للدراسات الأكاديمية
|v 023
|x 1994-697X
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| 856 |
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|u 2333-023-049-010.pdf
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| 930 |
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|d y
|p y
|q y
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| 995 |
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|a EduSearch
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| 995 |
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|a HumanIndex
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| 999 |
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|c 1458145
|d 1458145
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