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.

Opis bibliograficzny
Główni autorzy:	Tahrim, Tasmiah, Sharan, MD Asif, Monsur, Meshaq, Hasan, MD Abid, Azad, Tanzina Binte
Kolejni autorzy:	Shakil, Arif
Format:	Praca dyplomowa
Język:	English
Wydane:	Brac University 2024
Hasła przedmiotowe:	DDoS attack Cyber-security Machine learning Random forest classifier HTTP based protocol Transport layer Application layer Computer security HTTP (Computer network protocol)
Dostęp online:	http://hdl.handle.net/10361/23575

Podobne zapisy

Real time performance analysis on DDoS attack detection using machine learning
od: Suvra, Debashis Kar, i wsp.
Wydane: (2021)

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

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

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

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

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

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

SCAMM: detection and prevention of SQL injection attacks using a machine learning approach
od: Alam, Auninda, i wsp.
Wydane: (2021)

Multi-layer security analysis and implementation of smartphone based ATM
od: Farid, Imran, i wsp.
Wydane: (2017)

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

Fortifying federated learning: security against model poisoning attacks
od: Anan, Fabiha, i wsp.
Wydane: (2024)

Boundary layer theory.
od: Schlichting, Hermann, 1907-
Wydane: (2001)

Implementation of machine learning to estimate the air pollutants such as Carbon dioxide, methane, nitrous oxide and total greenhouse gas emissions in Bangladesh
od: Biswas, Sunanda, i wsp.
Wydane: (2022)

Rating detection by reviews using ML and NLP towards mobile phone recommendation
od: Sarker, Md Wafi, i wsp.
Wydane: (2023)

Detecting online recruitment fraud by using machine learning
od: Ghosh, Gitanjali, i wsp.
Wydane: (2021)

Cyber threats and scams in FinTech organizations: a brief overview of financial fraud cases, future challenges, and recommended solutions in Bangladesh
od: Hossain, Md. Jafrin, i wsp.
Wydane: (2023)

Learning a deep neural network for predicting phishing website
od: Das, Robat, i wsp.
Wydane: (2019)

Classification and Explanation of Different Internet of Things (IoT) Network Attacks using Machine Learning, Deep Learning and XAI
od: Tasnim, Anika, i wsp.
Wydane: (2022)

Identification of fake news using machine learning in distributed system
od: Saif, Mehruz, i wsp.
Wydane: (2021)

FakeDetect: Bangla fake news detection model based on different machine learning classifiers
od: Sraboni, Tasnuba, i wsp.
Wydane: (2021)

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

An in depth analysis of neural network with application in finance
od: Tasnim, Noshin, i wsp.
Wydane: (2019)

Skin disease detection and classification using deep learning
od: Shuvon, Mehedi Hasan, i wsp.
Wydane: (2022)

Environmental monitoring with the help of Internet of Things (loT) and machine learning
od: Alam, Md. Sakirul, i wsp.
Wydane: (2021)

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

A counseling system to predict the study path for freshmen
od: Usha, Rowshni Tasneem, i wsp.
Wydane: (2019)

Utilizing machine learning to project the nancial outcomes of reconnecting with potential customers of the same industry
od: Hossain, Shoumik, i wsp.
Wydane: (2022)

Development of IoT based network for monitoring appliances
od: Haque, S M Azmi, i wsp.
Wydane: (2019)

ShielDroid: a hybrid ML and DL approach for real-time malware detection system in Android
od: Ahmed, Md Faisal, i wsp.
Wydane: (2021)

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

Prostate cancer detection using deep learning neural network with transfer learning approach
od: Badhon, Ariful Islam Mahmud, i wsp.
Wydane: (2022)

Voice recognition using machine learning and central database to enhance security system
od: Nur, Mir Md. Taosif, i wsp.
Wydane: (2022)

SNMP, SNMPv2, SNMPv3, and RMON 1 and 2 /
od: Stallings, William
Wydane: (1999)

Heart disease prediction using machine learning algorithms
od: Ali, Musfiq, i wsp.
Wydane: (2019)

A machine learning approach to analyze and predict rainfall in different regions of Bangladesh
od: Rahee, Arnob, i wsp.
Wydane: (2021)

Parking data analysis
od: Ahamed, Kasfi, i wsp.
Wydane: (2023)

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

Performance of geographic routing protocol in mobile ad-hoc networks
od: Uddin, Jia, i wsp.
Wydane: (2016)

Computer vision based skin disease detection using machine learning
od: Jayeb, Ahmad Wasiq, i wsp.
Wydane: (2023)

Public vehicle ETA system using machine learning
od: Kabir, Md. Miraz, i wsp.
Wydane: (2018)