A convolutional neural network based model with improved activation function and optimizer for effective intrusion detection and classification

A convolutional neural network based model with improved activation function and optimizer for effective intrusion detection and classification

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2020.

Xehetasun bibliografikoak
Egile Nagusiak:	Kabir, Solaiman, Sakib, Sadman, Hossain, Md. Akib, Islam, Safi
Beste egile batzuk:	Hossain, Muhammad Iqbal
Formatua:	Thesis
Hizkuntza:	English
Argitaratua:	Brac University 2021
Gaiak:	Intrusion Detection System (IDS) Multiclass classi fication CNN DNN Machine learning.
Sarrera elektronikoa:	http://hdl.handle.net/10361/14733

Antzeko izenburuak

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Urban sound classification using convolutional Neural Network and long short term memory based on multiple features
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Performance analysis of deep learning algorithms for Intrusion Detection System(IDS) of IoT Security
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Malicious data classification in packet data network through hybrid meta deep learning
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Application of deep learning in MRI classification of Schizophrenia
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Training free non-intrusive load monitoring of electronic appliances battery charging with low sampling rate
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Classification of Bangladeshi soil texture using convolutional neural network
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Integration of handcrafted and deep neural features for Melanoma classification
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Aﬀective state recognition through analysis of electroencephalogram signals by using extreme gradient boosting
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Segmentation based Kidney Tumor Classification using Deep Neural Network
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Bangali Handwritten characters classification using Deep Convolutional Neural Network
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An efficient approach for binary classification in brain tumor detection using convolutional neural network
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Speech command classification based on deep neural networks
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Efficient and effective automated surveillance agents using kernel tricks
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Dynamic spam detection system and most relevant features identiﬁcation using random weight network
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Interior design drawings - coordination plan (Architectural Consultant Drawings)
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Do Elections Always Motivate Incumbents? : Experimentation vs. Career Concerns /
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Detecting Deepfake images using deep convolutional neural network
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Bengali hand sign language recognition using convolutional neural networks
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FoodieCal: a convolutional neural network based food detection and calorie estimation system
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Brain tumor detection with convolutional neural network
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Vulgar and spam comment identification using Gluon Natural Language Processing and Convolution Neural Networks
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Argitaratua: (2019)

Explainable Deepfake video detection using Convolutional Neural Network and CapsuleNet
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Application of deep convolutional neural network in multiclass skin cancer classification using custom CNN architecture
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Alzheimer’s Disease detection and classification using transfer learning techniques and ensembling operations on convolutional neural networks
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Analyzing CV/resume using natural language processing and machine learning
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Argitaratua: (2018)

Leaf classification by feature extraction using CNN
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Argitaratua: (2020)

A system to prevent social violence using convolutional neural network
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Early prediction of Alzheimer's disease using convolutional neural network
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Design and evaluation of convolutional neural network for detection of Alzheimer’s disease using MRI data
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Skin cancer detection and classification using multiple optimized deep convolutional neural network
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Corn leaf disease detection using deep convolution neural network
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SWIFT and RTGS operations of Southeast Bank Limited
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Detection of amyotrophic lateral sclerosis using signal processing and machine learning
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Predicting stock market trend from twitter feed and building a framework for Bangladesh
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Exploring the intersection of machine learning and explainable artificial intelligence: An analysis and validation of ML models through XAI for intrusion detection
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