Analisis Serangan DDoS Menggunakan Metode Jaringan Saraf Tiruan

Analisis Serangan DDoS Menggunakan Metode Jaringan Saraf Tiruan

DDoS attack (Distribute Denial of Service) is one of the weapons of choice from hackers because it’s proven it has become threat on the internet worlds. The frequent of DDoS attacks creates a threat to internet users or servers, so that requires the introduction of several new methods that occur, on...

Fuld beskrivelse

Bibliografiske detaljer
Main Authors:	M. Alfine Ridho, Molavi Arman
Format:	Article
Sprog:	English
Udgivet:	LPPM ISB Atma Luhur 2020-10-01
Serier:	Jurnal Sisfokom
Fag:	ddos neural netwok fixed moving window traffic log intrusion detection system
Online adgang:	http://jurnal.atmaluhur.ac.id/index.php/sisfokom/article/view/945

Lignende værker

ANALISIS STATISTIK LOG JARINGAN UNTUK DETEKSI SERANGAN DDOS BERBASIS NEURAL NETWORK
af: Arif Wirawan Muhammad
Udgivet: (2016-12-01)

Rekayasa Fitur Berbasis Machine Learning untuk Mendeteksi Serangan DDoS
af: Muhammad Nur Faiz, et al.
Udgivet: (2022-08-01)

DDoS Detection Mechanism Using Trust-Based Evaluation System in VANET
af: M. Poongodi, et al.
Udgivet: (2019-01-01)

Entropic DDoS Detection for Quantum Networks
af: Del Rajan
Udgivet: (2022-12-01)

Detection of Application Layer DDoS Attack Based on SIS Epidemic Model
af: Dalia Nashat, et al.
Udgivet: (2021-01-01)

HADEC: Hadoop-based live DDoS detection framework
af: Sufian Hameed, et al.
Udgivet: (2018-07-01)

Toward the Protection of IoT Networks: Introducing the LATAM-DDoS-IoT Dataset
af: Josue Genaro Almaraz-Rivera, et al.
Udgivet: (2022-01-01)

Physical Assessment of an SDN-Based Security Framework for DDoS Attack Mitigation: Introducing the SDN-SlowRate-DDoS Dataset
af: Noe M. Yungaicela-Naula, et al.
Udgivet: (2023-01-01)

Recent Analysis of Forged Request Headers Constituted by HTTP DDoS
af: Abdul Ghafar Jaafar, et al.
Udgivet: (2020-07-01)

A novel optimization-driven deep learning framework for the detection of DDoS attacks
af: Raj Kumar Batchu, et al.
Udgivet: (2024-11-01)

SD-Honeypot Integration for Mitigating DDoS Attack Using Machine Learning Approaches
af: Fauzi Dwi Setiawan Sumadi, et al.
Udgivet: (2022-03-01)

Hybrid DDoS Detection Framework Using Matching Pursuit Algorithm
af: Derya Erhan, et al.
Udgivet: (2020-01-01)

Mitigation of Application Layer DDoS Flood Attack Against Web Servers
af: Ahamed Aljuhani, et al.
Udgivet: (2019-03-01)

A DoS/DDoS Attack Detection System Using Chi-Square Statistic Approach
af: Fang-Yie Leu, et al.
Udgivet: (2010-04-01)

Komparasi Mod Evasive dan DDoS Deflate Untuk Mitigasi Serangan Slow Post
af: Jupriyadi Jupriyadi, et al.
Udgivet: (2021-02-01)

DDoS attacks and machine‐learning‐based detection methods: A survey and taxonomy
af: Mohammad Najafimehr, et al.
Udgivet: (2023-12-01)

Scalable DDoS Mitigation System for Data Centers
af: Zdenek Martinasek
Udgivet: (2015-01-01)

Blockchain-Assisted Hybrid Harris Hawks Optimization Based Deep DDoS Attack Detection in the IoT Environment
af: Iyad Katib, et al.
Udgivet: (2023-04-01)

Protocol-Based Deep Intrusion Detection for DoS and DDoS Attacks Using UNSW-NB15 and Bot-IoT Data-Sets
af: Muhammad Zeeshan, et al.
Udgivet: (2022-01-01)

Federated Learning for Decentralized DDoS Attack Detection in IoT Networks
af: Yaser Alhasawi, et al.
Udgivet: (2024-01-01)

Intercept the Cloud Network From Brute Force and DDoS Attacks via Intrusion Detection and Prevention System
af: Muhammad Nadeem, et al.
Udgivet: (2021-01-01)

SDN Based Collaborative Scheme for Mitigation of DDoS Attacks
af: Sufian Hameed, et al.
Udgivet: (2018-02-01)

Seleksi Fitur Dengan Information Gain Untuk Meningkatkan Deteksi Serangan DDoS menggunakan Random Forest
af: Kurniabudi Kurniabudi, et al.
Udgivet: (2020-02-01)

An Enhanced LSTM Approach for Detecting IoT-Based DDoS Attacks Using Honeypot Data
af: Arjun Kumar Bose Arnob, et al.
Udgivet: (2025-02-01)

DoS and DDoS vulnerability of IoT: A review
af: Emina Džaferović, et al.
Udgivet: (2019-06-01)

Enhancing Cybersecurity: Machine Learning Approaches for Predicting DDoS Attack
af: Farhan Sadik Ferdous, et al.
Udgivet: (2024-07-01)

Understanding Internet DDoS Mitigation from Academic and Industrial Perspectives
af: Yuan Cao, et al.
Udgivet: (2018-01-01)

Visualization analysis and design of DDoS attack
af: Yi-fan ZHANG, et al.
Udgivet: (2017-02-01)

Visualization analysis and design of DDoS attack
af: Yi-fan ZHANG,Xiao-ju DONG
Udgivet: (2017-02-01)

DDoS Attack Detection Method Based on Improved KNN With the Degree of DDoS Attack in Software-Defined Networks
af: Shi Dong, et al.
Udgivet: (2020-01-01)

Security Performance Analysis of LEO Satellite Constellation Networks under DDoS Attack
af: Yan Zhang, et al.
Udgivet: (2022-09-01)

Detection of Application-Layer DDoS Attacks Produced by Various Freely Accessible Toolkits Using Machine Learning
af: Dyari Mohammed Sharif, et al.
Udgivet: (2023-01-01)

Detection of spoofed and non-spoofed DDoS attacks and discriminating them from flash crowds
af: Jaideep Gera, et al.
Udgivet: (2018-07-01)

Deep-Learning-Based Approach to Detect ICMPv6 Flooding DDoS Attacks on IPv6 Networks
af: Omar E. Elejla, et al.
Udgivet: (2022-06-01)

Survey of DDoS defense:challenges and directions
af: Fei CHEN, et al.
Udgivet: (2017-10-01)

Survey of DDoS defense:challenges and directions
af: Fei CHEN,Xiao-hong BI,Jing-jing WANG,Yuan LIU
Udgivet: (2017-10-01)

Enhancing IoT Network Security: Unveiling the Power of Self-Supervised Learning against DDoS Attacks
af: Josue Genaro Almaraz-Rivera, et al.
Udgivet: (2023-10-01)

ICMPv6-Based DoS and DDoS Attacks Detection Using Machine Learning Techniques, Open Challenges, and Blockchain Applicability: A Review
af: Mohammad Tayyab, et al.
Udgivet: (2020-01-01)

IoT-DH dataset for classification, identification, and detection DDoS attack in IoT
af: Syaifuddin Saif, et al.
Udgivet: (2024-06-01)

Developing information technology for evaluating and enhancing application-layer DDoS attack detection methods
af: Arkadii Kravchuk, et al.
Udgivet: (2024-08-01)