A machine learning based approach for DDos attack detection

A machine learning based approach for DDos attack detection

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2023.

Bibliografiske detaljer
Main Authors:	Tahrim, Tasmiah, Sharan, MD Asif, Monsur, Meshaq, Hasan, MD Abid, Azad, Tanzina Binte
Andre forfattere:	Shakil, Arif
Format:	Thesis
Sprog:	English
Udgivet:	Brac University 2024
Fag:	DDoS attack Cyber-security Machine learning Random forest classifier HTTP based protocol Transport layer Application layer Computer security HTTP (Computer network protocol)
Online adgang:	http://hdl.handle.net/10361/23575

Lignende værker

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

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

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

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

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

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

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

SCAMM: detection and prevention of SQL injection attacks using a machine learning approach
af: Alam, Auninda, et al.
Udgivet: (2021)

Multi-layer security analysis and implementation of smartphone based ATM
af: Farid, Imran, et al.
Udgivet: (2017)

Analysis of cybersecurity threats to financial and accounting data: implications for organizational risk management
af: Sadiq, Sadavi
Udgivet: (2024)

Fortifying federated learning: security against model poisoning attacks
af: Anan, Fabiha, et al.
Udgivet: (2024)

Boundary layer theory.
af: Schlichting, Hermann, 1907-
Udgivet: (2001)

Implementation of machine learning to estimate the air pollutants such as Carbon dioxide, methane, nitrous oxide and total greenhouse gas emissions in Bangladesh
af: Biswas, Sunanda, et al.
Udgivet: (2022)

Rating detection by reviews using ML and NLP towards mobile phone recommendation
af: Sarker, Md Wafi, et al.
Udgivet: (2023)

Detecting online recruitment fraud by using machine learning
af: Ghosh, Gitanjali, et al.
Udgivet: (2021)

Cyber threats and scams in FinTech organizations: a brief overview of financial fraud cases, future challenges, and recommended solutions in Bangladesh
af: Hossain, Md. Jafrin, et al.
Udgivet: (2023)

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

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

Identification of fake news using machine learning in distributed system
af: Saif, Mehruz, et al.
Udgivet: (2021)

FakeDetect: Bangla fake news detection model based on different machine learning classifiers
af: Sraboni, Tasnuba, et al.
Udgivet: (2021)

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

An in depth analysis of neural network with application in finance
af: Tasnim, Noshin, et al.
Udgivet: (2019)

Skin disease detection and classification using deep learning
af: Shuvon, Mehedi Hasan, et al.
Udgivet: (2022)

Environmental monitoring with the help of Internet of Things (loT) and machine learning
af: Alam, Md. Sakirul, et al.
Udgivet: (2021)

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

A counseling system to predict the study path for freshmen
af: Usha, Rowshni Tasneem, et al.
Udgivet: (2019)

Utilizing machine learning to project the nancial outcomes of reconnecting with potential customers of the same industry
af: Hossain, Shoumik, et al.
Udgivet: (2022)

Development of IoT based network for monitoring appliances
af: Haque, S M Azmi, et al.
Udgivet: (2019)

ShielDroid: a hybrid ML and DL approach for real-time malware detection system in Android
af: Ahmed, Md Faisal, et al.
Udgivet: (2021)

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

Prostate cancer detection using deep learning neural network with transfer learning approach
af: Badhon, Ariful Islam Mahmud, et al.
Udgivet: (2022)

Voice recognition using machine learning and central database to enhance security system
af: Nur, Mir Md. Taosif, et al.
Udgivet: (2022)

SNMP, SNMPv2, SNMPv3, and RMON 1 and 2 /
af: Stallings, William
Udgivet: (1999)

Heart disease prediction using machine learning algorithms
af: Ali, Musfiq, et al.
Udgivet: (2019)

A machine learning approach to analyze and predict rainfall in different regions of Bangladesh
af: Rahee, Arnob, et al.
Udgivet: (2021)

Parking data analysis
af: Ahamed, Kasfi, et al.
Udgivet: (2023)

Role of cyber security in ensuring safety and security of data in financial institutions
af: Zamee, Zahin Shahriar
Udgivet: (2024)

Performance of geographic routing protocol in mobile ad-hoc networks
af: Uddin, Jia, et al.
Udgivet: (2016)

Computer vision based skin disease detection using machine learning
af: Jayeb, Ahmad Wasiq, et al.
Udgivet: (2023)

Public vehicle ETA system using machine learning
af: Kabir, Md. Miraz, et al.
Udgivet: (2018)