@article {Bendriss2013307,
	title = {Automatic selection of filtering devices in a distributed intrusion prevension system},
	journal = {Journal of Theoretical and Applied Information Technology},
	volume = {53},
	number = {2},
	year = {2013},
	note = {cited By 0},
	pages = {307-311},
	abstract = {We presented in a previous article [1] a distributed intrusion prevention system based on honeypots for collecting malicious data. Among important questions to handle there is the choice of filtering device on which a filtering rule has to be applied. In this paper we propose a solution which will allow automatic selection of filtering device in the distributed IPMS platform. These devices will be configured to block unauthorized traffic. This solution must ensure full integration with the IPMS architecture. {\textcopyright} 2005 - 2013 JATIT \& LLS. All rights reserved.},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84880649114\&partnerID=40\&md5=65a999baae635cb70cfb3cfd71d7a506},
	author = {Bendriss, E. and Regragui, B.}
}
@article {Bendriss2013792,
	title = {Honeypot based intrusion management system: From a passive architecture to an ips system},
	journal = {Journal of Theoretical and Applied Information Technology},
	volume = {47},
	number = {2},
	year = {2013},
	note = {cited By 1},
	pages = {792-797},
	abstract = {In this paper, we are presenting an Intrusion Prevention System (IPS) based on multiple sensors in the network. These sensors are in fact honeypots built using honeyd. Honeyd is a high level honeypot which is very light and which is offering a lot of possibilities to get the most of information gathered about attackers in general. In fact, we are presenting a solution to go from passive and isolated sensors to a collaborative platform to help prevent intrusions by analyzing all collected data. To be able to do this, honeyd2db module was developed to enable honeyd to log its data into a database instead of a local file to the sensor. This aggregation of data from all sensors give us the possibility to analyze all collected logs as a hole and come out with a decision (deny network traffic on a firewall for example) using any of the known methods of data analysis. {\textcopyright} 2005 - 2013 JATIT \& LLS.},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84872851179\&partnerID=40\&md5=64123c156efa34310464200f371b9f29},
	author = {Bendriss, E. and Regragui, B.}
}
