Demystifying machine learning models for IOT attack detection with explainable AI

Demystifying machine learning models for IOT attack detection with explainable AI

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.

Bibliographische Detailangaben
Hauptverfasser:	Muna, Rabeya Khatun, Maliha, Homaira Tasnim, Hasan, Mahedi
Weitere Verfasser:	Hossain, Muhammad Iqbal
Format:	Abschlussarbeit
Sprache:	English
Veröffentlicht:	Brac University 2021
Schlagworte:	Xg-boost Explainable AI XAI Lime Shap ELI5 IoT attack SMOTE PCA Machine learning Internet of things
Online Zugang:	http://hdl.handle.net/10361/15553

Ähnliche Einträge

XOPSIS: an explainable AI method based on the order of preference by similarity to ideal solution
von: Rahman, Anika
Veröffentlicht: (2024)

Heart attack prediction using machine learning and XAI
von: Ahsan, Mumtahina
Veröffentlicht: (2023)

Bank loan prediction using machine learning
von: Mahottam, Parthosarothi, et al.
Veröffentlicht: (2023)

Personalization in federated recommendation system using SVD++ with explainability
von: Patwary, Kabbya Kantam, et al.
Veröffentlicht: (2022)

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

Demystifying black-box learning models of rumor detection from social media posts
von: Tafannum, Faiza, et al.
Veröffentlicht: (2021)

Early stage detection and classification of colon cancer using deep learning and explainable AI on histopathological images
von: Hossain, Mainul, et al.
Veröffentlicht: (2022)

Analysis on dengue severity using machine learning approach
von: Sayeed, Sanjana, et al.
Veröffentlicht: (2021)

Exploring Alzheimer's disease prediction with XAI in various neural network models
von: Rahman, Quazi Ashikur, et al.
Veröffentlicht: (2022)

PDFGuardian: An innovative approach to interpretable PDF malware detection using XAI with SHAP framework
von: Rahman, Tahsinur, et al.
Veröffentlicht: (2023)

Analysis on IOT Botnet and DDOS attack
von: Nur, Md. Walid Bin
Veröffentlicht: (2018)

Mobile sensors based human activity recognition using machine learning with explainable ML
von: Rahman, Raihan, et al.
Veröffentlicht: (2021)

Explainable artificial intelligence and model calibration for water quality prediction
von: Hellen, Nakayiza
Veröffentlicht: (2022)

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

Intrusion detection system for various IoT attacks on MQTT protocol
von: Farhan, et al.
Veröffentlicht: (2022)

Mitigating DDoS attacks using a resource sharing network
von: Khan, Farabi Fardin, et al.
Veröffentlicht: (2022)

Real time performance analysis on DDoS attack detection using machine learning
von: Suvra, Debashis Kar, et al.
Veröffentlicht: (2021)

Exploring the intersection of machine learning and explainable artificial intelligence: An analysis and validation of ML models through XAI for intrusion detection
von: Rahman, Masroor, et al.
Veröffentlicht: (2023)

Impact of black-hole and jellyfish attacks in MANET using HTTP traffic
von: Ahmed, Faisal, et al.
Veröffentlicht: (2017)

Quantum lattice learning and explainable artificial intelligence for maternal and child healthcare
von: Marvin, Ggaliwango
Veröffentlicht: (2022)

Speech emotion detection using supervised, unsupervised and feature selection algorithms
von: Rifat, Abu Nuraiya Mahfuza Yesmin, et al.
Veröffentlicht: (2019)

The recruitment and selection process of Eli Nursing Home
von: Huq, Naureen
Veröffentlicht: (2019)

Demystify the blackbox model of automated detection of lung and kidney diseases from X-ray and CT radiographs
von: Islam, Md. Nazmul
Veröffentlicht: (2023)

A study on the efficacy of natural language generation techniques for similar writing personalities
von: Anwar, Ahmed, et al.
Veröffentlicht: (2024)

Finding habitable exo planets using boosting algorithm
von: Rahman, Md. Mashfiq, et al.
Veröffentlicht: (2020)

Prediction of diabetes induced complications using different machine learning algorithms
von: Rahman, Tahsinur, et al.
Veröffentlicht: (2018)

Analysing neural network models for detecting panic attacks with uncertainty analysis
von: Tahmid, Ahnaf, et al.
Veröffentlicht: (2024)

EAI4CC: deciphering lung and colon cancer categorization within a federated learning framework harnessing the power of explainable artificial intelligence
von: Mim, Ankhi Akter, et al.
Veröffentlicht: (2024)

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

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

Evaluating the effectiveness of CNN-based models for diabetic retinopathy detection
von: Niaz, H.M, et al.
Veröffentlicht: (2024)

Interpretable MOOC dropout prediction using different Ensemble Methods and XAI
von: Khan, Labib Hasan, et al.
Veröffentlicht: (2023)

Classification and Explanation of Different Internet of Things (IoT) Network Attacks using Machine Learning, Deep Learning and XAI
von: Tasnim, Anika, et al.
Veröffentlicht: (2022)

MalFam: a comprehensive study on malware families with state-of-the-art CNN architectures with classifications and XAI
von: Haque, Abid Hossain, et al.
Veröffentlicht: (2024)

An approach to detect epileptic seizure using XAI and machine learning
von: Bijoy, Emam Hasan, et al.
Veröffentlicht: (2022)

Federated ensemble-learning for transport mode detection in vehicular edge network
von: Alam, MD. Mustakin, et al.
Veröffentlicht: (2023)

Prediction on large scale data using extreme gradient boosting
von: Sawon, Md.Tariq Hasan, et al.
Veröffentlicht: (2016)

Advanced artificial intelligence self balanced robot for home security
von: Shourove, MD. Niaz Sharif, et al.
Veröffentlicht: (2018)

A machine learning based approach for DDos attack detection
von: Tahrim, Tasmiah, et al.
Veröffentlicht: (2024)

An interpretable deep learning approach to detect Alzheimer using MRI images
von: Oni, Farhan Anzum, et al.
Veröffentlicht: (2023)