Search Results - (( security classification mining algorithm ) OR ( java application bee algorithm ))

Prediction of college student academic performance using data mining techniques. by Abd Jalil, Azura, Mustapha, Aida, Santa, Dzulizah, Zain, Nurul Zaiha, Radwan, Rizalina

“…The classification algorithms used are the Decision Tree, Naïve Bayesian, and Multilayer Perception with the highest classification accuracy by the Naive Bayes algorithm with accuracy of 95.3%. …”
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Machine Learning Algorithm for Malware Detection: Taxonomy, Current Challenges, and Future Directions by Gorment N.Z., Selamat A., Cheng L.K., Krejcar O.

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An enhanced classification framework for intrusions detection system using intelligent exoplanet atmospheric retrieval algorithm by Slamet, ., Izzeldin Ibrahim, Mohamed Abdelaziz

“…Currently, many companies use data mining for various implementations. One form of implementation is intrusion detection system (IDS). …”
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Feature Subset Selection in Intrusion Detection Using Soft Computing Techniques by AHMAD, IFTIKHAR

“…This research work uses the Knowledge Discovery and Data mining (KDD) cup dataset, which is considered benchmark for evaluating security detection mechanisms. …”
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A framework for malware identification based on behavior by Mohamad Fadli, Zolkipli

“…The IF-THEN Prediction Rules which is generated using the data mining technique, ID3 Algorithm is used. In the implementation of malware target classification, Structure Level Rules are utilized to classify malware into possible target class. …”
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Feature Subset Selection in Intrusion Detection Using Soft Computing Techniques by Iftikhar , Ahmad, Azween, Abdullah

“…This research work uses the Knowledge Discovery and Data mining (KDD) cup dataset, which is considered benchmark for evaluating security detection mechanisms. …”
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An enhanced classification framework for intrusions detection system using intelligent exoplanet atmospheric retrieval by Slamet, Slamet, Izzeldin, Ibrahim Mohamed Abdelaziz

“…Currently, many companies use data mining for various implementations. One form of implementation is intrusion detection system (IDS). …”
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Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

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Named entity recognition using a new fuzzy support vector machine. by Mansouri, Alireza, Affendy, Lilly Suriani, Mamat, Ali

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Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi by Atefi, Kayvan

“…Experiments demonstrate and prove that the proposed EBPSO method produces better accuracy mining data and selecting subset of relevant features comparing other algorithms. …”
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Sentiment Analysis of Cyberbullying in Social Media Using Decision Trees by Sulaiman, Aliza Sharina

“…This has also risen the possibilities and advancement of security threats. This study uses data mining techniques from the views of users written ion Twitter to use in sentiment analysis of decision tree classification. …”
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Activity recognition based on accelerometer sensor using combinational classifiers by Zainudin, Muhammad Noorazlan Shah, Sulaiman, Md. Nasir, Mustapha, Norwati, Perumal, Thinagaran

“…Publicly accelerometer dataset obtained from Wireless Sensor Data Mining (WISDM) lab has been used in this study. The result of classification was validated using 10-fold cross validation algorithm in order to make sure all the experiments perform well.…”
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An improved hybrid learning approach for better anomaly detection by Mohamed Yassin, Warusia

“…In this thesis, an improved hybrid mining approach is proposed through combination of K-Means clustering and classification techniques. …”
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Activity Recognition Based On Accelerometer Sensor Using Combinational Classifiers by Muhammad Noorazlan Shah, Zainuddin, Md Nasir, Sulaiman, Norwati, Mustapha, Thinagaran, Perumal

“…Publicly accelerometer dataset obtained from Wireless Sensor Data Mining (WISDM) lab has been used in this study. The result of classification was validated using 10-fold cross validation algorithm in order to make sure all the experiments perform well.…”
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A hybrid interpretable deep structure based on adaptive neuro‑fuzzy inference system, decision tree, and K‑means for intrusion detection by Jia, Lu, Yin Chai, Wang, Chee Siong, Teh, Xinjin, Li, Liping, Zhao, Fengrui, Wei

“…Meanwhile, for improving the efciency of training and predicting, Pearson Correlation analysis, standard deviation, and a new adaptive K-means are used to select attributes and make fuzzy interval decisions. The proposed algorithm was trained, validated, and tested on the NSL-KDD (National security lab–knowledge discovery and data mining) dataset. …”
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An integrated anomaly intrusion detection scheme using statistical, hybridized classifiers and signature approach by Mohamed Yassin, Warusia

“…Subsequently, NB+RF, a hybrid classification algorithm is used to distinguish similar and dissimilar content behaviours of a packet. …”
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A New Model for Trojan Detection using Machine Learning Inspired by Al-Furqan Verse by Madihah Mohd Saudi, Areej Mustafa Abuzaid, Masrur Ibrahim

Collective interaction filtering with graph-based descriptors for crowd behaviour analysis by Wong, Pei Voon

“…Crowd behaviour analysis plays an important role in high security interests in public areas such as railway stations, shopping centres, and airports, where large populations gather. …”
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