Real time performance analysis on DDoS attack detection using machine learning

Real time performance analysis on DDoS attack detection using machine learning

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

Bibliografiske detaljer
Main Authors:	Suvra, Debashis Kar, Sen, Tanusree, Mou, Maysha Maliha, Rahman, Asifur
Andre forfattere:	Hossain, Muhammad Iqbal
Format:	Thesis
Sprog:	English
Udgivet:	Brac University 2021
Fag:	DDoS attacks Detection Artificial intelligence Machine learning.
Online adgang:	http://hdl.handle.net/10361/14730

Lignende værker

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

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

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

Intrusion of Malware (DDoS) detection in IoT devices using Machine Learning on Cyberspace
af: Al Amin, Istiak, et al.
Udgivet: (2022)

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

Botnet detection In IoT devices using machine learning
af: Rouf, Shakir, et al.
Udgivet: (2020)

Multimodal human detection in disaster situations using deep learning & artificial intelligence
af: Rafat, Md. Tasbi, et al.
Udgivet: (2023)

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

A semi-supervised federated learning approach leveraging pseudo-labeling for Knee Osteoarthritis severity detection
af: Rifat, Rakib Hossain
Udgivet: (2024)

Heart attack prediction using machine learning and XAI
af: Ahsan, Mumtahina
Udgivet: (2023)

Towards devising an effective and reliable means of fish detection and classification through the exploration of various deep learning algorithms
af: Farhan, Rafid, et al.
Udgivet: (2024)

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

Demystifying machine learning models for IOT attack detection with explainable AI
af: Muna, Rabeya Khatun, et al.
Udgivet: (2021)

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

Disease detection system of mango leaves
af: Islam, Sabrina, et al.
Udgivet: (2024)

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

Detection and classification of Mango Leaf diseases utilizing convolutional neural network models
af: Ferdous, Md.Rubaiat, et al.
Udgivet: (2024)

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

Making AI intelligible :
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Udgivet: (1991)

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Udgivet: (2003)

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Udgivet: (1985)

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Udgivet: (1980)

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Udgivet: (1992)

Artificial intelligence at MIT : expanding frontiers /
Udgivet: (1990)

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Udgivet: (1985)

The role of Artificial Intelligence (AI) in the detection and diagnosis of chronic diseases – a review
af: Zaman, Mumtahina
Udgivet: (2022)

Vapor adsorption limitation of graphene nanoribbons in quasi conductance increment: a NEGF approach
af: Shakil, Shifur Rahman, et al.
Udgivet: (2016)

The impact of artificial intelligence on the financial sector
af: Siddiqui, Ria
Udgivet: (2024)

Implementing A.I based solutions to understand & predict consumer sentiment
af: Bin Ahmed, Omar
Udgivet: (2023)

Deepfake detection using neural networks
af: Sakib, Sadman, et al.
Udgivet: (2021)

Introduction to AI robotics /
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Udgivet: (2000)

Intelligent systems and robotics /
Udgivet: (2000)

Artificial intelligence : a modern approach /
af: Russell, Stuart J. (Stuart Jonathan)
Udgivet: (2016)

Artificial intelligence in HR Management
af: Lamia, Ridwana Islam
Udgivet: (2023)

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

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

Explainable AI (XAI) driven skin cancer detection using transformer and CNN based architecture
af: Radiah, Faiza, et al.
Udgivet: (2024)

Early detection of parkinson’s disease using image processing and artificial neural network
af: Rumman, Mosarrat, et al.
Udgivet: (2018)