Anomaly detection In IoT using machine learning algorithms

Anomaly detection In IoT using machine learning algorithms

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

Bibliografische gegevens
Hoofdauteurs:	Arko, Aritro Roy, Khan, Saadat Hasan, Preety, A a Anjum, Biswas, Mehrab Hossain
Andere auteurs:	Chakrabarty, Amitabha
Formaat:	Thesis
Taal:	English
Gepubliceerd in:	Brac University 2019
Onderwerpen:	IoT (Internet of Things) Anomaly detection Intrusion detection Machine learning algorithms Sensor data Network data UNSW-NB15 Machine learning Internet of things Intrusion detection systems (Computer security) Anomaly detection (Computer security)
Online toegang:	http://hdl.handle.net/10361/12776

Gelijkaardige items

Performance analysis of intrusion detection systems using the PyCaret machine learning library on the UNSW-NB15 dataset
door: Abdullah, et al.
Gepubliceerd in: (2021)

Performance analysis of deep learning algorithms for Intrusion Detection System(IDS) of IoT Security
door: Fiha, Yeamin Jahan, et al.
Gepubliceerd in: (2022)

IoT based automated entry system with integration of Covid-19 symptom detection
door: Ruhin, Rubaiyat Alam, et al.
Gepubliceerd in: (2024)

Fault detection and predictive maintenance in IoT-based building management system using machine learning
door: Sabuj, Khaja Sheikh Imran, et al.
Gepubliceerd in: (2022)

Automated intruder detection from image sequences using minimum volume sets
door: Ahmed, Tarem, et al.
Gepubliceerd in: (2016)

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

Advance waterway transport system based on Internet of Things (IoT)
door: Miah, MD Imtiaj, et al.
Gepubliceerd in: (2024)

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

IoT based Road accident controlling model using Wireless Body Area Network and GPS
door: Islam, Nayem-Ul, et al.
Gepubliceerd in: (2021)

Modeling and simulation of a gas detecting device for providing safety; and reducing the risk of accidents due to gas explosion or fire
door: Khan, Rafsan, et al.
Gepubliceerd in: (2022)

ML based performance assurance and VoC management of highly convergence mobile operator network.
door: Rahman, Md. Arifur
Gepubliceerd in: (2024)

IoT based health monitoring system for pregnant women & children
door: Ohana, Fariha Islam, et al.
Gepubliceerd in: (2022)

Machine learning based data processing and latency reduction in the internet of things for agriculture
door: Rahman, Sajeed Ur, et al.
Gepubliceerd in: (2019)

Fault detection in waste water treatment plant using statistical analysis & machine learning
door: Haque, Md. Ezazul, et al.
Gepubliceerd in: (2019)

Learning algorithms for anomaly detection from images
door: Ahmed, Tarem, et al.
Gepubliceerd in: (2018)

IoT security risk analysis
door: Sakib, Nazmus, et al.
Gepubliceerd in: (2020)

Botnet detection In IoT devices using machine learning
door: Rouf, Shakir, et al.
Gepubliceerd in: (2020)

Implementation of an IoT based home automation system using real time sensors
door: Mandal, Dipta, et al.
Gepubliceerd in: (2019)

3G and 4G paging success rate based mobile network anomaly detection using supervised and unsupervised learning
door: Ahasan, Md Rakibul
Gepubliceerd in: (2022)

Detecting anomalies in human eyes using structural similarity index measurement
door: Jahan, Monwar, et al.
Gepubliceerd in: (2019)

Real-time DDoS detection in software-defined networks using machine learning
door: Hasan, Kadir, et al.
Gepubliceerd in: (2024)

Introducing AI in garment fault detection using YOLOv5 to reduce bottleneck
door: Sanjana, Jasia, et al.
Gepubliceerd in: (2024)

Analyzing security threats and mitigation techniques for fog computing in IoT-enabled smart cities
door: Emon, Sheikh Sadi, et al.
Gepubliceerd in: (2024)

The application of Internet Of Things (IoT) to the traditional power grid
door: Morshed, Ragib, et al.
Gepubliceerd in: (2020)

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

A deep learning based autonomous electric vehicle on unstructured road conditions
door: Adnan, Ashik, et al.
Gepubliceerd in: (2021)

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

Multi images retrieved for automatic intruder detection using kernel-based learning algorithm
door: Shahrear, S.M Fardin, et al.
Gepubliceerd in: (2016)

Flood monitoring and warning system for embankment using IoT
door: Dutta, Aparup, et al.
Gepubliceerd in: (2022)

Using deep learning algorithms to detect violent activities
door: Ammar, S.M. Rojin, et al.
Gepubliceerd in: (2019)

The influence of IoT-based agrotech system in Bangladesh on developing urban farming
door: Barua, Pranto
Gepubliceerd in: (2023)

Internet of Things (IoT) based air quality index measurement system for Dhaka city
door: Aurangajeb, Raoha, et al.
Gepubliceerd in: (2022)

Multi-modal hate speech detection using machine learning
door: Shill, Ponkoj Chandra, et al.
Gepubliceerd in: (2021)

TinyML for emotion detection in voice signals: evaluating and proposing algorithms for IoT wearable devices
door: Ahmed, Hasibul Hasan, et al.
Gepubliceerd in: (2024)

IoT based air components collection for machine learning reinforcement
door: Islam, Tanjima, et al.
Gepubliceerd in: (2024)

Hate speech detection using machine learning techniques
door: Manzoor, Tahbib, et al.
Gepubliceerd in: (2024)

Real-time foul detection in football matches using machine learning techniques
door: Siddiqui, Bishal Sadi, et al.
Gepubliceerd in: (2024)

IoT smart meter for electricity consumers
door: Wali-ur- Rahman, Md., et al.
Gepubliceerd in: (2019)

Malicious data classification in packet data network through hybrid meta deep learning
door: Tapu, Sakib Uddin, et al.
Gepubliceerd in: (2023)

Anomaly clustering based on correspondence analysis
door: Islam, Humayra
Gepubliceerd in: (2018)