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.

Bibliografski detalji
Glavni autori:	Suvra, Debashis Kar, Sen, Tanusree, Mou, Maysha Maliha, Rahman, Asifur
Daljnji autori:	Hossain, Muhammad Iqbal
Format:	Disertacija
Jezik:	English
Izdano:	Brac University 2021
Teme:	DDoS attacks Detection Artificial intelligence Machine learning.
Online pristup:	http://hdl.handle.net/10361/14730

Similar Items

Mitigating DDoS attacks using a resource sharing network
od: Khan, Farabi Fardin, i dr.
Izdano: (2022)

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

Real-time DDoS detection in software-defined networks using machine learning
od: Hasan, Kadir, i dr.
Izdano: (2024)

Intrusion of Malware (DDoS) detection in IoT devices using Machine Learning on Cyberspace
od: Al Amin, Istiak, i dr.
Izdano: (2022)

A machine learning based approach for DDos attack detection
od: Tahrim, Tasmiah, i dr.
Izdano: (2024)

Botnet detection In IoT devices using machine learning
od: Rouf, Shakir, i dr.
Izdano: (2020)

Multimodal human detection in disaster situations using deep learning & artificial intelligence
od: Rafat, Md. Tasbi, i dr.
Izdano: (2023)

Intrusion detection system for various IoT attacks on MQTT protocol
od: Farhan, i dr.
Izdano: (2022)

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

Heart attack prediction using machine learning and XAI
od: Ahsan, Mumtahina
Izdano: (2023)

Towards devising an effective and reliable means of fish detection and classification through the exploration of various deep learning algorithms
od: Farhan, Rafid, i dr.
Izdano: (2024)

Analysing neural network models for detecting panic attacks with uncertainty analysis
od: Tahmid, Ahnaf, i dr.
Izdano: (2024)

Demystifying machine learning models for IOT attack detection with explainable AI
od: Muna, Rabeya Khatun, i dr.
Izdano: (2021)

Impact of black-hole and jellyfish attacks in MANET using HTTP traffic
od: Ahmed, Faisal, i dr.
Izdano: (2017)

Disease detection system of mango leaves
od: Islam, Sabrina, i dr.
Izdano: (2024)

Exploring Alzheimer's disease prediction with XAI in various neural network models
od: Rahman, Quazi Ashikur, i dr.
Izdano: (2022)

Detection and classification of Mango Leaf diseases utilizing convolutional neural network models
od: Ferdous, Md.Rubaiat, i dr.
Izdano: (2024)

Exploring the intersection of machine learning and explainable artificial intelligence: An analysis and validation of ML models through XAI for intrusion detection
od: Rahman, Masroor, i dr.
Izdano: (2023)

Making AI intelligible :
od: Cappelen, Herman

Artificial Intelligence : a new synthesis /
od: Nilsson, Nils J., 1933-
Izdano: (1998)

Artificial intelligence /
od: Rich, Elaine
Izdano: (1991)

Artificial intelligence : a modern approach /
od: Russell, Stuart J. (Stuart Jonathan)
Izdano: (2003)

Introduction to artificial intelligence /
od: Charniak, Eugene
Izdano: (1985)

Principles of artificial intelligence /
od: Nilsson, Nils J., 1933-
Izdano: (1980)

Artificial intelligence /
od: Winston, Patrick Henry
Izdano: (1992)

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

Introduction to artificial intelligence /
od: Jackson, Philip C., 1949-
Izdano: (1985)

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

Vapor adsorption limitation of graphene nanoribbons in quasi conductance increment: a NEGF approach
od: Shakil, Shifur Rahman, i dr.
Izdano: (2016)

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

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

Deepfake detection using neural networks
od: Sakib, Sadman, i dr.
Izdano: (2021)

Introduction to AI robotics /
od: Murphy, Robin, 1957-
Izdano: (2000)

Intelligent systems and robotics /
Izdano: (2000)

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

Artificial intelligence in HR Management
od: Lamia, Ridwana Islam
Izdano: (2023)

PDFGuardian: An innovative approach to interpretable PDF malware detection using XAI with SHAP framework
od: Rahman, Tahsinur, i dr.
Izdano: (2023)

A deep learning based autonomous electric vehicle on unstructured road conditions
od: Adnan, Ashik, i dr.
Izdano: (2021)

Explainable AI (XAI) driven skin cancer detection using transformer and CNN based architecture
od: Radiah, Faiza, i dr.
Izdano: (2024)

Early detection of parkinson’s disease using image processing and artificial neural network
od: Rumman, Mosarrat, i dr.
Izdano: (2018)