Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
February 17, 2026
Neural Networks and Rules-based Systems used to Find Rational and
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Anomaly detection systems are extensively used security tools to detect cyber-threats and attack activities in computer systems and networks. In this paper, we present Text Mining-Based Anomaly Detection (TMAD) model. We discuss n-gram text categorization and focus our attention on a main contribution of method TF-IDF (Term frequency, inverse document frequency), which enhance the performance commonly term weighting schemes are used, where the weights reflect the importance of a word in a specific document of the considered collection. Mahalanobis Distances Map (MDM) and Support Vector Machine (SVM) are used to discover hidden correlations between the features and among the packet payloads. Experiments have been accomplished to estimate the performance of TMAD against ISCX dataset 2012 intrusion detection evaluation dataset. The results show TMAD has good accuracy.
Mohsen Kakavand. 2015. \u201cA Text Mining-Based Anomaly aZDetection Model in Network Security\u201d. Global Journal of Computer Science and Technology - G: Interdisciplinary GJCST-G Volume 14 (GJCST Volume 14 Issue G5): .
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
The methods for personal identification and authentication are no exception.
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Neural Networks and Rules-based Systems used to Find Rational and
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Anomaly detection systems are extensively used security tools to detect cyber-threats and attack activities in computer systems and networks. In this paper, we present Text Mining-Based Anomaly Detection (TMAD) model. We discuss n-gram text categorization and focus our attention on a main contribution of method TF-IDF (Term frequency, inverse document frequency), which enhance the performance commonly term weighting schemes are used, where the weights reflect the importance of a word in a specific document of the considered collection. Mahalanobis Distances Map (MDM) and Support Vector Machine (SVM) are used to discover hidden correlations between the features and among the packet payloads. Experiments have been accomplished to estimate the performance of TMAD against ISCX dataset 2012 intrusion detection evaluation dataset. The results show TMAD has good accuracy.
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