The main use of intrusion detection systems (IDS) is to detect attacks against information
systems and networks. Normal use of the network and its functioning can also be monitored …

In this paper we focus on the aggregation of IDS alerts, an important component of the alert
fusion process. We exploit fuzzy measures and fuzzy sets to design simple and robust alert …

During the last decade, intrusion detection systems (IDSs) have become a widely used
measure for security management. However, these systems often generate many false …

Debt detection is important for improving payment accuracy in social security. Since debt
detection from customer transactional data can be generally modelled as a fraud detection …

As security threats change and advance in a drastic way, most of the organizations
implement multiple Network Intrusion Detection Systems (NIDSs) to optimize detection and …

As the rapid growth of network attacking tools, patterns of network intrusion events change
gradually. Although many researches had been proposed to analyze network intrusion …

As security threats change and advance in a drastic way, most of the organizations
implement multiple Network Intrusion Detection Systems (NIDSs) to optimize detection and …

Intrusion detection systems (IDS) often provide a large number and poor quality alerts, which
are insufficient to support rapid identification of ongoing attacks or predict an intruderpsilas …

As security threats advance in a drastic way, most of the organizations implement multiple
network intrusion detection systems (NIDSs) to optimize detection and to provide …

Data mining is an emerging field gaining acceptance in research and industry. This is
evidenced by an increasing number of research publications, conferences, journals and …