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Analysis of Data Mining Tools for Android Malware Detection by Yusof, Robiah, Abdullah, Raihana Syahirah, Adnan, Nurul Syahirrah, Abd. Jalil, Nurlaily

“…Hence, the objective of this research is to identify the best machine learning technique or algorithm on selected tool for android malware detection. …”
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Sentiment mining in twitter for early depression detection / Najihah Salsabila Ishak by Ishak, Najihah Salsabila

“…A comparison between built-in Scikit Learn Naive Bayes algorithm, and the scratch Naive Bayes algorithm is used to measure its effectiveness in terms of accuracy. …”
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Effective mining on large databases for intrusion detection by Adinehnia, Reza, Udzir, Nur Izura, Affendey, Lilly Suriani, Ishak, Iskandar, Mohd Hanapi, Zurina

“…Data mining is a common automated way of generating normal patterns for intrusion detection systems. …”
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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 ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

“…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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A Recent Research on Malware Detection Using Machine Learning Algorithm: Current Challenges and Future Works by Gorment N.Z., Selamat A., Krejcar O.

“…Barium compounds; Cybersecurity; Data mining; Decision trees; Evolutionary algorithms; K-means clustering; Learning algorithms; Malware; Network security; Sodium compounds; Support vector machines; 'current; Comparatives studies; Cyber security; K-means; Machine learning algorithms; Malware attacks; Malware detection; Metaheuristic; Recent researches; Systematic literature review; Nearest neighbor search…”

Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan by Meisam , Gordan

“…In the modeling phase, amongst all DM algorithms, the applicability of machine learning, artificial intelligence and statistical data mining techniques were examined using Support Vector Machine (SVM), Artificial Neural Network (ANN) and Classification and Regression Tree (CART) to detect the hidden patterns in vibration data. …”
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A simultaneous spam and phishing attack detection framework for short message service based on text mining approach by Mohd Foozy, Cik Feresa

“…Additionally, the proposed framework also can detect the attack simultaneously using text mining approaches.…”
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A Review of Unsupervised Machine Learning Frameworks for Anomaly Detection in Industrial Applications by Usmani, U.A., Happonen, A., Watada, J.

“…Currently, academic literature does not really cover the topic of unsupervised machine learning techniques for anomaly detection. This paper provides an overview of the current deep learning and unsupervised machine learning techniques for anomaly detection and discusses the fundamental challenges in anomaly detection. …”
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Feature selection in intrusion detection, state of the art: A review by Rais, H.M., Mehmood, T.

“…These input features give information to the learning algorithms which used in intrusion detection system in the form of the detection method. …”
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Tracking student performance in introductory programming by means of machine learning by Khan I., Al Sadiri A., Ahmad A.R., Jabeur N.

Detection on ambiguous software requirements specification written in malay using machine learning by Zahrin, Mohd Firdaus

“…Hence, we propose a framework to detect ambiguity on SRS using supervised machine learning technique. …”
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Intrusion detection system for the internet of things based on blockchain and multi-agent systems by Liang, Chao, Shanmugam, Bharanidharan, Azam, Sami, Karim, Asif, Islam, Ashraful, Zamani, Mazdak, Kavianpour, Sanaz, Idris, Norbik Bashah

“…The results demonstrate the efficiency of deep learning algorithms when detecting attacks from the transport layer. …”
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Improving intrusion detection using genetic algorithm by Hashemi, V. Moraveji, Muda, Zaiton, Yassin, Warusia

“…To overcome this problem, a genetic algorithm approach is proposed. Genetic Algorithm (GA) is most frequently employed as a robust technology based on machine learning for designing IDS. …”
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A Cryptojacking Detection System With Product Moment Correlation Coefficient (Pmcc) Heatmap Intelligent by Kong, Jun Hao

“…This project research will present the PMCC Heatmap to choose the optimal attributes for using machine learning to detect cryptojacking in order to utilise machine learning to detect embedded malware. …”
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Cyberbullying detection and prevention: Data mining in social media by Sultan D., Suliman A., Toktarova A., Omarov B., Mamikov S., Beissenova G.

Building classification models from imbalanced fraud detection data / Terence Yong Koon Beh, Swee Chuan Tan and Hwee Theng Yeo by Terence, Yong Koon Beh, Swee, Chuan Tan, Hwee, Theng Yeo

“…Building classification models from such imbalanced data sets is a relatively new challenge in the machine learning and data mining community because many traditional classification algorithms assume similar proportions of majority and minority classes. …”
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Diabetes Diagnosis And Level Of Care Fuzzy Rule-Based Model Utilizing Supervised Machine Learning For Classification And Prediction by Mohd Aris, Teh Noranis, Abu Bakar, Azuraliza, Mahiddin, Normadiah, Zolkepli, Maslina

“…Most computer applications use machine learning and data mining techniques to aid classification and prediction of a disease. …”
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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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Exploring frogeye leaf spot disease severity in soybean through hyperspectral data analysis and machine learning with Orange Data Mining by Ang, Yuhao, Mohd Shafri, Helmi Zulhaidi, Al-Habshi, Mohammed Mustafa

“…No previous study has investigated Orange mining tool as visual programming approach in analysing hyperspectral reflectance data, especially in crop disease detection. …”
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