Performance analysis of deep learning algorithms for Intrusion Detection System(IDS) of IoT Security

Performance analysis of deep learning algorithms for Intrusion Detection System(IDS) of IoT Security

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022.

Bibliografiska uppgifter
Huvudupphovsmän:	Fiha, Yeamin Jahan, Farjana, Mithila, Bin Masum, Syed Rifat, Soron, Mehedi Bin Sarwar, Alif, Mia Fahim Hasan
Övriga upphovsmän:	Hossain, Muhammad Iqbal
Materialtyp:	Lärdomsprov
Språk:	en_US
Publicerad:	Brac University 2022
Ämnen:	Deep learning Intrusion Detection System IoT Security RNN GRU LSTM KDD-99 NSL-KDD IDS Vanilla LSTM Bidirectional LSTM Stacked LSTM Machine learning. Intrusion detection systems (Computer security) Internet of things
Länkar:	http://hdl.handle.net/10361/17213

Liknande verk

Bangla hate speech detection on social media using attention-based recurrent neural network
av: Das, Amit Kumar, et al.
Publicerad: (2022)

Dhaka Stock Exchange stock price prediction using Machine Learning and Deep Learning Models
av: Barua, Debalina
Publicerad: (2023)

A convolutional neural network based model with improved activation function and optimizer for effective intrusion detection and classification
av: Kabir, Solaiman, et al.
Publicerad: (2021)

Deep learning approaches to EEG and fMRI data: a comparative study for sleep stage classification
av: Tanvir, Farhan, et al.
Publicerad: (2024)

Hybrid recommendation system of intelligent captioning using deep learning networks
av: Wasi, Ahamed Al, et al.
Publicerad: (2024)

Short term load forecasting based on Internet of Things (IoT)
av: Uz Zaman, Mahdi, et al.
Publicerad: (2018)

Human sentiment analysis using natural language processing
av: Shamya, Md. Shamiul Haque Khan, et al.
Publicerad: (2024)

Predicting suicidal intent from social media text post using machine learning
av: Chowdhury, Md. Mubin Ul Islam, et al.
Publicerad: (2023)

A texture based industrial fault diagnosis model using Gammatone Filter Bank and transfer learning
av: Morshed, Atique, et al.
Publicerad: (2021)

Novel approach to detect hate speech and profanity on online platforms
av: Pritha, Barha Meherun, et al.
Publicerad: (2022)

Forecasting bitcoin price considering macro economic factors and media influence using bidirectional LSTM and random forest regressor as ensemble model
av: Ghose, Swattic, et al.
Publicerad: (2023)

Anomaly detection In IoT using machine learning algorithms
av: Arko, Aritro Roy, et al.
Publicerad: (2019)

Recognizing sentimental emotions in text by using Machine Learning
av: Bushra, Tabassum Khan, et al.
Publicerad: (2023)

Dhaka Stock Market analysis with ARIMA-LSTM Hybrid Model
av: Arnob, Raisul Islam, et al.
Publicerad: (2020)

Mental health analysis of cancer-diagnosed patients with the lowest survival rate and their caregivers
av: Orchi, Irin Hoque, et al.
Publicerad: (2023)

Predicting effectiveness of marketing through analyzing emotional context in advertisement using deep learning
av: Arafat, Sheikh Mohammad, et al.
Publicerad: (2021)

RansomListener: Ransom call sound investigation using LSTM and CNN Architectures
av: Rahman, Rafeed, et al.
Publicerad: (2021)

Optical flow based violence detection from video footage using hybrid MobileNet and Bi-LSTM
av: Haque, Tashfia, et al.
Publicerad: (2024)

Multimodal fake news detection using text and image
av: Biswas, Trisha, et al.
Publicerad: (2024)

Sentiment analysis to determine employee job satisfaction using machine learning techniques
av: Mouli, Nazifa, et al.
Publicerad: (2023)

Analyzing Schizophrenic-prone text from social media content: a novel approach through ML and NLP
av: Rodela, Raisa Rahman, et al.
Publicerad: (2024)

Learning a deep neural network for predicting phishing website
av: Das, Robat, et al.
Publicerad: (2019)

Predicting crime using deep learning
av: Shihab, Muhammad Nafees, et al.
Publicerad: (2024)

Comparative analysis of machine learning models for stock price analysis across different dataset sizes
av: Srabon, Abir Alam, et al.
Publicerad: (2023)

Visualization of security vulnerabilities through intrusion detection system
av: Ahmed, Ibrar, et al.
Publicerad: (2010)

Prediction of genetic mutation from clinical data of sickle cell disease using few-shot siamese bidirectional LSTM and federated learning
av: Alam, Salman, et al.
Publicerad: (2023)

Analyzing area-wise air pollution level using machine learning for a better future
av: Sihan, Sk. Atik Tajwar, et al.
Publicerad: (2021)

Real-time crime detection using convolutional LSTM and YOLOv7
av: Sakiba, Cyrus, et al.
Publicerad: (2023)

Automatic helmet-less biker detection using deep learning
av: Ratul, Md. Ibrahim, et al.
Publicerad: (2024)

Voice impersonation detection using LSTM based RNN and explainable AI
av: Barua, Kawshik, et al.
Publicerad: (2022)

An integrated approach: fake review detection using convBERT-BiLSTM classification
av: Mahmud, Md. Anas, et al.
Publicerad: (2024)

Data security model using deep learning and edge computing for Internet of Things (IoT) in smart city
av: Aziz, Md. Yasin, et al.
Publicerad: (2021)

Analysis of financial data on the time series using data from the stock market
av: Shachcha, Ifad Bhuiyan, et al.
Publicerad: (2022)

Text classification with an efficient preprocessing technique for cross-language and multilingual data
av: Khan, Towhid, et al.
Publicerad: (2023)

A hybrid deep learning model and explainable AI-based Bengali hate speech multi-label classification and interpretation
av: Shakil, Mahmudul Hasan
Publicerad: (2023)

Violent activity detection through surveillance camera using deep learning
av: Miah, Parvez, et al.
Publicerad: (2023)

Recognition of Bangladeshi sign language from 2D videos using openpose and LSTM based RNN
av: Dewanjee, Tanmoy, et al.
Publicerad: (2021)

Bangla speech recognition using 1D CNN and LSTM with different dimension reduction techniques
av: Nirjhor, S M Mahsanul Islam, et al.
Publicerad: (2019)

A computer vision based approach for stalking detection using CNN-LSTM hybrid model
av: Iqbal, Shahriar, et al.
Publicerad: (2023)

RED-LSTM: Real time emotion detection using LSTM
av: Labiba, Mansura Rahman, et al.
Publicerad: (2023)