Analysis of malware prediction based on infection rate using machine learning techniques

Analysis of malware prediction based on infection rate using machine learning techniques

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2019.

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς:	Zawad, Safir, Mansur, Raiyan, Evan, Nahian, Asad, Ashub Bin
Άλλοι συγγραφείς:	Hossain, Muhammad Iqbal
Μορφή:	Thesis
Γλώσσα:	en_US
Έκδοση:	Brac University 2020
Θέματα:	Human learning techniques Malware prediction Neural Networks
Διαθέσιμο Online:	http://hdl.handle.net/10361/14056

Παρόμοια τεκμήρια

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Automated fabric color prediction
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Performance analysis of machine learning algorithms for Malware classification
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Machine learning as an indicator for breast cancer prediction
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Machine learning for stress prediction
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PDFGuardian: An innovative approach to interpretable PDF malware detection using XAI with SHAP framework
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Use of machine learning and weather predictions to bridge the gap between consumer demands and the market requirements of food crops
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Stock price prediction
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Predicting peak performance of a cricket player using machine learning and data analytics
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Breast cancer prediction using different machine learning models
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Covid-19 infected lung detection using machine learning
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Android platform to find blood donors and predicting most suitable donors
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A computer vision based approach for stalking detection using CNN-LSTM hybrid model
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Epileptic seizure prediction using bandpass filtering and convolutional neural network
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Intrusion of Malware (DDoS) detection in IoT devices using Machine Learning on Cyberspace
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Flood prediction using machine learning models
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Predicting regional accents of Bengali language using deep learning
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