| Title | A Multi-Agent Model for Network Intrusion Detection |
| Publication Type | Conference Paper |
| Year of Publication | 2019 |
| Authors | OUIAZZANE, Said, ADDOU, Malika, BARRAMOU, Fatimazahra |
| Conference Name | 2019 1st International Conference on Smart Systems and Data Science (ICSSD) |
| Keywords | anomaly detection, autonomy, big computer infrastructure, Big Data, Big networks, composability, computer network security, computer security, Databases, DIDS, distributed intrusion detection model, Distribution, Hadoop distributed file system, IDS, Intrusion detection, MAS, MAS agents, Metrics, Multi Agent System, multi-agent systems, multiagent system, network intrusion detection, network intrusions, network requirements, pubcrawl, Resiliency, security |
| Abstract | The objective of this paper is to propose a distributed intrusion detection model based on a multi agent system. Mutli Agent Systems (MAS) are very suitable for intrusion detection systems as they meet the characteristics required by the networks and Big Data issues. The MAS agents cooperate and communicate with each other to ensure the effective detection of network intrusions without the intervention of an expert as used to be in the classical intrusion detection systems relying on signature matching to detect known attacks. The proposed model helped to detect known and unknown attacks within big computer infrastructure by responding to the network requirements in terms of distribution, autonomy, responsiveness and communication. The proposed model is capable of achieving a good and a real time intrusion detection using multi-agents paradigm and Hadoop Distributed File System (HDFS). |
| DOI | 10.1109/ICSSD47982.2019.9003119 |
| Citation Key | ouiazzane_multi-agent_2019 |
A Multi-Agent Model for Network Intrusion Detection