It is important to increase the detection rate for known intrusions and detect unknown intrusions. It is also important to incrementally learn new unknown intrusions. Most current intrusion detection systems employ either misuse detection or anomaly detection. In order to employ these techniques, we propose incremental hybrid intrusion detection system. This framework combines incremental misus...

Today, e-commerce has occupied a large volume of economic exchanges. It is known as one of the most effective business practices. Predicted trust which means trusting an anonymous user is important in online communities. In this paper, the trust was predicted by combining two methods of multiplex network and community detection. In modeling the network in terms of a multiplex network, the relat...

Fast and accurate ridge detection in fingerprints is essential to each AFIS (Automatic Fingerprint Identification System). Smudged furrows and cut ridges in the image of a finger print are major problems in any AFIS. This paper investigates a new online ridge detection method that reduces the complexity and costs associated with the fingerprint identification procedure. The noise in fingerprint...

the arc costs are assumed to be online parameters of the network and decisions should be made while the costs of arcs are not known. the policies determine the permitted nodes and arcs to traverse and they are generally defined according to the departure nodes of the current policy nodes. in on-line created tours arc costs are not available for decision makers. the on-line traversed nodes are f...

Collusion is a major unsolved security problem in online bridge: by illicitly exchanging card information over the telephone, instant messenger or the like, cheaters can gain huge advantages over honest players. It is very hard if not impossible to prevent collusion from happening. Instead, we motivate an AI-based detection approach and discuss its challenges. We challenge the AI community to c...

This paper investigates the effect of various types of linguistic features (lexical, syntactic and semantic) for training classifiers to detect threats of violence in a corpus of YouTube comments. Our results show that combinations of lexical features outperform the use of more complex syntactic and semantic features for this task.