| Title | Development of an Intrusion Detection System Using a Botnet with the R Statistical Computing System |
| Publication Type | Conference Paper |
| Year of Publication | 2020 |
| Authors | Yamanoue, Takashi, Murakami, Junya |
| Conference Name | 2020 9th International Congress on Advanced Applied Informatics (IIAI-AAI) |
| Date Published | Sept. 2020 |
| Publisher | IEEE |
| ISBN Number | 978-1-7281-7397-9 |
| Keywords | Bot, Botnet, composability, DDoS Attack Prevention, detection, Electronic publishing, Human Behavior, Information services, intrusion, Intrusion detection, Logic gates, Malware, Metrics, Prevention, pubcrawl, r, resilience, Resiliency, wide area networks |
| Abstract | Development of an intrusion detection system, which tries to detect signs of technology of malware, is discussed. The system can detect signs of technology of malware such as peer to peer (P2P) communication, DDoS attack, Domain Generation Algorithm (DGA), and network scanning. The system consists of beneficial botnet and the R statistical computing system. The beneficial botnet is a group of Wiki servers, agent bots and analyzing bots. The script in a Wiki page of the Wiki server controls an agent bot or an analyzing bot. An agent bot is placed between a LAN and its gateway. It can capture every packet between hosts in the LAN and hosts behind the gateway from the LAN. An analyzing bot can be placed anywhere in the LAN or WAN if it can communicate with the Wiki server for controlling the analyzing bot. The analyzing bot has R statistical computing system and it can analyze data which is collected by agent bots. |
| URL | https://ieeexplore.ieee.org/document/9430408 |
| DOI | 10.1109/IIAI-AAI50415.2020.00022 |
| Citation Key | yamanoue_development_2020 |
Development of an Intrusion Detection System Using a Botnet with the R Statistical Computing System