Dataset for Botnet group activity with adaptive generator

Author:

Hostiadi Dandy Pramana,Ahmad TohariORCID

Publisher

Elsevier BV

Subject

Multidisciplinary

Reference9 articles.

1. An empirical comparison of botnet detection methods;Garc;Comput. Secur.,2014

2. A new approach to detecting bot attack activity scenario;Hostiadi,2021

3. Towards the development of realistic botnet dataset in the Internet of Things for network forensic analytics: bot-IoT dataset;Koroniotis;Futur. Gener. Comput. Syst.,2019

4. Botnet detection based on traffic behavior analysis and flow intervals;Zhao;Comput. Secur.,2013

5. The IDMEF : RFC 4765;Debar;Mycol. Res.,2007

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1. B-CAT: a model for detecting botnet attacks using deep attack behavior analysis on network traffic flows;Journal of Big Data;2024-04-10

2. Traffic Classification For Botnet Detection Using Deep Learning;2023 3rd International Conference on Smart Cities, Automation & Intelligent Computing Systems (ICON-SONICS);2023-12-06

3. Analyzing and detecting Botnet Attacks using Anomaly Detection with Machine Learning;2023 5th International Conference on Inventive Research in Computing Applications (ICIRCA);2023-08-03

4. Botnet Dataset Overview Using Statistical Approach Based on Time Gap Activity Analysis;2023 11th International Symposium on Digital Forensics and Security (ISDFS);2023-05-11

5. Dimensional Feature Reduction for Detecting Botnet Activities;2023 25th International Conference on Advanced Communication Technology (ICACT);2023-02-19

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