An intrusion detection system (IDS) usually has to analyse Giga-bytes of audit information. In the case of anomaly IDS, the information is used to build a user profile characteris...
Abstract. The work presented in this paper shows the capability of a connectionist model, based on a statistical technique called Exploratory Projection Pursuit (EPP), to identify ...
The DARPA/MIT Lincoln Laboratory off-line intrusion detection evaluation data set is the most widely used public benchmark for testing intrusion detection systems. But the presence...
Chuanhuan Yin, Shengfeng Tian, Houkuan Huang, Jun ...
In order to complement the incomplete training audit trails, model generalization is always utilized to infer more unknown knowledge for intrusion detection. Thus, it is important ...
In this paper, we propose a distributed hierarchical intrusion detection system, for ad hoc wireless networks, based on a power level metric for potential ad hoc hosts, which is us...
T. Srinivasan, Jayesh Seshadri, J. B. Siddharth Jo...
This research employs unsupervised pattern recognition to approach the thorny issue of detecting anomalous network behavior. It applies a connectionist model to identify user behav...
Genetic Programming (GP) based Intrusion Detection Systems (IDS) use connection state network data during their training phase. These connection states are recorded as a set of fe...
Software-based Network Intrusion Detection Systems (NIDS) often fail to keep up with high-speed network links. In this paper an FPGA-based pre-filter is presented that reduces th...
Haoyu Song, Todd S. Sproull, Michael Attig, John W...
Building on the concepts and the formal definitions of self, nonself, antigen, and detector introduced in the research of network intrusion detection, the dynamic evolution models...
In this paper we present a storage based intrusion detection system (IDS) which uses time and space efficient point-intime copy and performs file system integrity checks to detec...