Search Results - (( features selection detection algorithm ) OR ( java application based algorithm ))

A malware analysis and detection system for mobile devices / Ali Feizollah by Ali, Feizollah

“…We then used feature selection algorithms and deep learning algorithms to build a detection model. …”
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Evaluation of feature selection algorithm for android malware detection by Mazlan, Nurul Hidayah, A Hamid, Isredza Rahmi

“…This paper synthesizes an evaluation of feature selection algorithm by utilizing Term Frequency Inverse Document Frequency (TF-IDF) as the main algorithm in Android malware detection. …”
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Feature selection to enhance android malware detection using modified term frequency-inverse document frequency (MTF-IDF) by Mazlan, Nurul Hidayah

“…This research synthesizes an evaluation of feature selection algorithm by utilizing Term Frequency-Inverse Document Frequency (TF-IDF) as the main algorithm in Android malware detection. …”
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Enhanced grey wolf optimisation algorithm for feature selection in anomaly detection by Almazini, Hussein

“…Experimental results of the EBGWO algorithm on the NSL-KDD dataset in terms of number of selected features and classification accuracy are superior to other benchmark optimisation algorithms. …”
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Smart student timetable planner by Wong, Xin Tong

“…The project scope encompasses features such as secure login, course selection with conflict detection, timetable history, comparison between auto-generated and manual schedules, collaboration modules, and export functionality. …”
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Feature Selection and Classifier Parameter Estimation for Egg Signal Peak Detection using Gravitational Search Algorithm by Zuwairie, Ibrahim, Mohd Zaidi, Mohd Tumari, Asrul, Adam, Norrima, Mokhtar, Marizan, Mubin, Mohd Ibrahim, Shapiai

“…Using GSA, the parameter estimation of the classifier and the peak feature selection can be done simultaneously. Based on the experimental results, the significant peak features of the peak detection algorithm were obtained where the average test accuracy is 77.74%.…”
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Enhanced feature selections of Adaboost training for face detection using genetic algorithm (GABoost) by Mohd. Zin, Zalhan, Khalid, Marzuki, Yusof, Rubiyah

“…Often some of these features are irrelevant and does not contribute directly to the face detection algorithm. …”
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Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi by Atefi, Kayvan

“…Some of the previous researchers used a feature set selection which is introduced for IDS but there still shortage in their detection rate and selected amounts of features. …”
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Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System by Aljanabi, Mohammad, Mohd Arfian, Ismail, Mezhuyev, Vitaliy

“…Feature selection and classifier parameter tuning are important factors that affect the performance of any intrusion detection system. …”
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Automated feature selection using boruta algorithm to detect mobile malware by Che Akmal, Che Yahaya, Ahmad Firdaus, Zainal Abidin, Salwana, Mohamad, Ernawan, Ferda, Mohd Faizal, Ab Razak

“…This research proposed automated feature selection using Boruta algorithm to detect the malware. …”
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K-gen phishguard: an ensemble approach for phishing detection with k-means and genetic algorithm by Al-Hafiz, Ali Raheem, Jabir, Adnan J., Subramaniam, Shamala

“…This research presents a two-phase phishing detection system by employing unsupervised feature selection and supervised classification. …”
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Enhanced feature selections of Adaboost training for face detection using genetic algorithm by Mohd. Zin, Zalhan

“…This technique is referred to as GABoost for this training part of a face detection system. The GA carries out an evolutionary search to select features which results in a higher number of feature types and sets selected in less time. …”
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Feature selection algorithms for Malaysian dengue outbreak detection model by Husam I.S. Abuhamad, Azuraliza Abu Bakar, Suhaila Zainudin, Mazura Sahani, Zainudin Mohd Ali

“…This research aimed to identify the best features that lead to better predictive accuracy of dengue outbreaks using three different feature selection algorithms; particle swarm optimization (PSO), genetic algorithm (GA) and rank search (RS). …”
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Features selection for IDS in encrypted traffic using genetic algorithm by Barati, Mehdi, Abdullah, Azizol, Mahmod, Ramlan, Mustapha, Norwati, Udzir, Nur Izura

“…An encrypted malicious traffic is able to evade the detection by IDS. Feature selection for IDS is a fundamental step in detection procedure and aims to eliminate some irrelevant and unneeded features from the dataset. …”
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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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BFEDroid: A Feature Selection Technique to Detect Malware in Android Apps Using Machine Learning by Chimeleze C., Jamil N., Ismail R., Lam K.-Y., Teh J.S., Samual J., Akachukwu Okeke C.

“…Android (operating system); Android malware; Classification (of information); Feature Selection; Learning systems; Mobile security; Android apps; Classification models; Feature weight; Features selection; Machine learning algorithms; Machine-learning; Malware detection; Malwares; Memory usage; Selection techniques; Learning algorithms…”

Features selection for ids in encrypted traffic using genetic algorithm by Barati, Mehdi, Abdullah, Azizol, Mahmod, Ramlan, Mustapha, Norwati, Udzir, Nur Izura

“…This paper presents a hybrid feature selection using Genetic Algorithm and Bayesian Network to improve Brute Force attack detection in Secure Shell (SSH) traffic. …”
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Extremal region detection and selection with fuzzy encoding for food recognition by Razali @ Ghazali, Mohd Norhisham

“…Three algorithms were used to accomplish the task of feature representation. …”
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Degree of contribution (DoC) feature selection algorithm for structural brain MRI volumetric features in depression detection by Kuryati, Kipli, Abbas, Z. Kouzani

“…Brain volumetric changes at a structural level appear to have importance in depression biomarkers studies. An automated algorithm is developed to select brain sMRI volumetric features for the detection of depression…”
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Improved intrusion detection algorithm based on TLBO and GA algorithms by Aljanabi, Mohammad, Mohd Arfian, Ismail

“…The proposed method combined the New Teaching-Learning-Based Optimization Algorithm (NTLBO), Support Vector Machine (SVM), Extreme Learning Machine (ELM), and Logistic Regression (LR) (feature selection and weighting) NTLBO algorithm with supervised machine learning techniques for Feature Subset Selection (FSS). …”
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