Visible to the public Toward a Network Intrusion Detection System for Geographic Data

TitleToward a Network Intrusion Detection System for Geographic Data
Publication TypeConference Paper
Year of Publication2020
AuthorsOuiazzane, S., Addou, M., Barramou, F.
Conference Name2020 IEEE International conference of Moroccan Geomatics (Morgeo)
Date PublishedMay 2020
PublisherIEEE
ISBN Number978-1-7281-5806-8
Keywordsanomaly detection, autonomous agents, autonomy, Big Data, Big networks, DIDS, distributed file system, distributed intrusion detection system, distributed processing, Distribution, expert systems, geographic data security, geographic information systems, Geographical System, GIS., Human Behavior, IDS, Intrusion detection, knowledge based systems, knowledge bases, known computer attack detection, MAS, Multi Agent System, multi-agent systems, multiagent paradigm, multiagent systems, network intrusion detection system, pubcrawl, resilience, Resiliency, Scalability, security, security of data, time detection, unknown computer attack detection
Abstract

The objective of this paper is to propose a model of a distributed intrusion detection system based on the multi-agent paradigm and the distributed file system (HDFS). Multi-agent systems (MAS) are very suitable to intrusion detection systems as they can address the issue of geographic data security in terms of autonomy, distribution and performance. The proposed system is based on a set of autonomous agents that cooperate and collaborate with each other to effectively detect intrusions and suspicious activities that may impact geographic information systems. Our system allows the detection of known and unknown computer attacks without any human intervention (Security Experts) unlike traditional intrusion detection systems that rely on knowledge bases as a mechanism to detect known attacks. The proposed model allows a real time detection of known and unknown attacks within large networks hosting geographic data.

URLhttps://ieeexplore.ieee.org/document/9121878
DOI10.1109/Morgeo49228.2020.9121878
Citation Keyouiazzane_toward_2020