White-Hat Worm Launcher Based on Deep Learning in Botnet Defense System
| Title | White-Hat Worm Launcher Based on Deep Learning in Botnet Defense System |
| Publication Type | Conference Paper |
| Year of Publication | 2020 |
| Authors | Kamilin, M. H. B., Yamaguchi, S. |
| Conference Name | 2020 IEEE International Conference on Consumer Electronics - Asia (ICCE-Asia) |
| Date Published | Nov. 2020 |
| Publisher | IEEE |
| ISBN Number | 978-1-7281-6164-8 |
| Keywords | BDS, Botnet, botnet defense system, botnets, composability, computer network performance evaluation, computer network security, Data models, Deep Learning, Grippers, Internet of Things, invasive software, IoT, IoT system, learning (artificial intelligence), malicious botnets, Malware, Mathematical model, Metrics, pubcrawl, resilience, Resiliency, Training data, white-hat botnets, white-hat worm launcher, worms placement |
| Abstract | This paper proposes a deep learning-based white-hat worm launcher in Botnet Defense System (BDS). BDS uses white-hat botnets to defend an IoT system against malicious botnets. White-hat worm launcher literally launches white-hat worms to create white-hat botnets according to the strategy decided by BDS. The proposed launcher learns with deep learning where is the white-hat worms' right place to successfully drive out malicious botnets. Given a system situation invaded by malicious botnets, it predicts a worms' placement by the learning result and launches them. We confirmed the effect of the proposed launcher through simulating evaluation. |
| URL | https://ieeexplore.ieee.org/document/9277358 |
| DOI | 10.1109/ICCE-Asia49877.2020.9277358 |
| Citation Key | kamilin_white-hat_2020 |
- IoT system
- worms placement
- white-hat worm launcher
- white-hat botnets
- Training data
- Resiliency
- resilience
- pubcrawl
- Metrics
- Mathematical model
- malware
- malicious botnets
- learning (artificial intelligence)
- BDS
- IoT
- invasive software
- Internet of Things
- Grippers
- deep learning
- Data models
- computer network security
- computer network performance evaluation
- composability
- botnets
- botnet defense system
- botnet