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Alerts correlation techniques have been widely used to provide intelligent and stateful detection methodologies. This is to understand attack steps and predict the expected sequence of events. However, most of the proposed systems are based on rule - based mechanisms which are tedious and error prone. Other methods are based on statistical modeling, these are unable to identify causal relationships...
We address the problem of combining information from diversified sources in a coherent fashion. A generalized evidence processing theory and an architecture for data fusion that accommodates diversified sources of information are presented. Different levels at which data fusion may take place such as the level of dynamics, the level of attributes, and the level of evidence are discussed. A multi-level...
Network Intrusion Detection Systems (NIDS) are considered as essential mechanisms to ensure reliable security. Intrusive model is used in signature-based NIDS by defining attack patterns and applying signature-matching on incoming traffic packets. Thousands of signatures and rules are created to specify different attacks and variations of a single attack. As a result, enormous data with less efficiency...
Due to customers' demands, network intrusion detection systems (NIDS) are required more real time. Since traditional intelligent NIDS are constructed on the basis of historical network data and system logs, they are expensive and not real time in a network stream environment. This paper presents an improved real time model that based on sequence mining to accelerate the accuracy and efficiency. In...
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