Titlebook: Intelligent Mechanisms for Network Configuration and Security; 9th IFIP WG 6.6 Inte Steven Latré,Marinos Charalambides,Burkhard Stille Conf

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Learning to Detect Network Intrusion from a Few Labeled Events and Background Trafficning within this domain is a lack of relevant ground truth data, i.e. real attacks, capturing malicious behaviors in their full variety. Most of existing solutions thus, up to a certain level, rely on rules designed by network domain experts. Although there are advantages to the use of rules, they l

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Using Application-Aware Flow Monitoring for SIP Fraud Detection the flow data for analysis of a Voice over IP (VoIP) traffic and a threat detection. A traditionally used flow record is insufficient for this purpose and therefore it was extended by application-layer information. In particular, we focus on the Session Initiation Protocol (SIP) and the type of a t

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Towards an Adaptive and Effective IDS Using OpenFlowe continuously. Therefore, new approaches need to be investigated to detect and handle attacks already in high-speed environments. In this PhD research, we will develop a new approach for detecting network attacks by processing data from core network components taking advantage of properties of Open

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