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Dynamic Intrusion alerts generation and Aggregation using Intelligent IDS

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Author(s): Mrs.Sudha Singaraju*1, G.Srikanth

Journal: International Journal of Computer Trends and Technology
ISSN 2231-2803

Volume: 4;
Issue: 7;
Start page: 2131;
Date: 2013;
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Keywords: Intrusion Detection System | Alert Aggregation | different layers | Meta alerts.

ABSTRACT
The essential subtask of intrusion detection is Alert aggregation. Protecting our data in the internet is a great risk. Intruders and hackers are always ready grab our data. To identify unauthorized users and to cluster different alerts produced by lowlevel intrusion detection systems firewalls, Intrusion detection system has been introduced. The relevant information whereas the amount of data can be reduced substantially by Meta-alters which will be generated for the clusters. At a certain point in time which has been initiated by an attacker is belonging to a specific hacking. For communication within a distributed intrusion detection system the meta-alerts may be the basis for reporting to security experts. In this paper, for online alert aggregation we propose a novel technique which is based on a dynamic and probabilistic model of current attack situation. For the estimation of the model parameters, it can be regarded as a data stream version of a maximum likelihood approach. The first alerts, which are belonging to a new attack instance, are generated with meta-alerts with a delay of typically only a few seconds. To achieveReduction rates while the number of missing metaalerts is extremely low can be possible with the three benchmark data sets are demonstrated.
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