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This work falls in the area of collaborative malware detection systems which rely on expertise and knowledge from multiple different antivirus software for malware detection. A critical component of such systems is the collaborative malware detection decision process. In this paper, we propose a novel decision model, RevMatch, where collaborative malware decisions are made based on labeled malware...
Software Defined Networking promises to simplify network management tasks by separating the control plane (a central controller) from the data plane (switches). OpenFlow has emerged as the de facto standard for communication between the controller and switches. Apart from providing flow control and communication interfaces, OpenFlow provides a flow level statistics collection mechanism from the data...
In managing multimedia services, it is important to understand how network performance affects user experience. The model presented in this paper aims to estimate user perception of video quality based on defect events, which are automatically classified by machine learning techniques. The underlying principle of our model is that human experience is event-based and there is a strong correlation between...
An effective Collaborative Intrusion Detection Network (CIDN) allows distributed Intrusion Detection Systems (IDSes) to collaborate and share their knowledge and opinions about intrusions, to enhance the overall accuracy of intrusion assessment as well as the ability of detecting new classes of intrusions. Toward this goal, we propose a distributed Host-based IDS (HIDS) collaboration system, particularly...
Protection and performance are the major requirements for any Intrusion Detection and/or Prevention System (IDPS). Existing IDPSs do not seem to provide a satisfactory method of achieving these two conflicting goals. Intrusion Detection Systems (IDSs) fulfill the network performance requirement but exhibit poor protection under successive attacks. On the other hand, Intrusion Prevention Systems (IPSs)...
In this paper, we propose a novel recommender framework for P2P file sharing systems. The proposed recommender system is based on user-based collaborative filtering technique. We take advantage from the partial search process used in partially decentralized systems to explore the relationships between peers. The proposed recommender system does not require any additional effort from the users since...
Cooperation between intrusion detection systems (IDSs) allow collective information and experience from a network of IDSs to be shared for improving the accuracy of detection. A critical component of a collaborative network is the mechanism of feedback aggregation in which each IDS makes an overall security evaluation based on peer opinions and assessments. In this paper, we propose a collaboration...
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