Learn More
The accuracy of detecting an intrusion within a network of intrusion detection systems (IDSes) depends on the efficiency of collaboration between member IDSes. The security itself within this network is an additional concern that needs to be addressed. In this paper, we present a trust-based framework for secure and effective collaboration within an(More)
The accuracy of detecting intrusions within a Collaborative Intrusion Detection Network (CIDN) depends on the efficiency of collaboration between peer Intrusion Detection Systems (IDSes) as well as the security itself of the CIDN. In this paper, we propose Dirichlet-based trust management to measure the level of trust among IDSes according to their mutual(More)
—Software Defined Networking (SDN) introduces a new communication network management paradigm and has gained much attention from academia and industry. However, the centralized nature of SDN is a potential vulnerability to the system since attackers may launch denial of services (DoS) attacks against the controller. Existing solutions limit requests rate to(More)
The accuracy of detecting intrusions within an Intrusion Detection Network (IDN) depends on the efficiency of collaboration between the peer Intrusion Detection Systems (IDSes) as well as the security itself of the IDN against insider threats. In this paper, we study host-based IDNs and introduce a Dirichlet-based model to measure the level of(More)
—Traditional intrusion detection systems (IDSs) work in isolation and can be easily compromised by unknown threats. An intrusion detection network (IDN) is a collaborative IDS network intended to overcome this weakness by allowing IDS peers to share detection knowledge and experience, and hence improve the overall accuracy of intrusion assessment. In this(More)
Traditional intrusion detection systems (IDSs) work in isolation and may be easily compromised by new threats. An intrusion detection network (IDN) is a collaborative IDS network intended to overcome this weakness by allowing IDS peers to share collective knowledge and experience, hence improve the overall accuracy of intrusion assessment. In this work, we(More)
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. Towards this goal, we propose a distributed(More)
With the exponential growth of smartphone apps, it is prohibitive for apps market places, such as Google App Store for example, to thoroughly verify if an app is legitimate or malicious. As a result, mobile users are left to decide for themselves whether an app is safe to use. Even worse, recent studies have shown that most apps in markets request to(More)