Data mining techniques play an increasing role in the intrusion detection by analyzing
network data and classifying it as' normal'or'intrusion'. In recent years, several data mining …

Many networking research activities are dependent on the availability of network captures.
Even outside academic research, there is a need for sharing network captures to cooperate …

Monitoring the Smart Grid (SG) is highly desired for critical applications such as power
quality assessment and transformer monitoring. Due to their low-cost, flexibility and …

From the identification of a drawback in the Isolation Forest (IF) algorithm that limits its use in
the scope of anomaly detection, we propose two extensions that allow to firstly overcome the …

With the increase of network components connected to the Internet, the need to ensure
secure connectivity is becoming increasingly vital. Intrusion Detection Systems (IDSs) are …

The publication and sharing of network trace data is a critical to the advancement of
collaborative research among various entities, both in government, private sector, and …

Network traffic processing is an automated method for arranging and optimizing network
traffic, based on the parameters. The traffic data is gathered to begin the study of the …

A large volume of network trace data are collected by the government and public and private
organizations and can be analyzed for various purposes such as resolving network …

Data mining techniques play an increasing role in the intrusion detection by analyzing
network data and classifying it as' normal'or'intrusion'. In recent years, several data mining …

The goal of the work is to present a preliminary result of research about trade-off between
privacy and utility in network traces. The study is considered in context of anomaly detection …