Abstract. Anomaly detection is based on profiles that represent normal behaviour of users, hosts or networks and detects attacks as significant deviations from these profiles. In t...
We present a novel approach for adaptively grouping and subdividing hair using discrete level-of-detail (LOD) representations. The set of discrete LODs include hair strands, clust...
This paper investigates a novel approach to unsupervised morphology induction relying on community detection in networks. In a first step, morphological transformation rules are a...
We present the architecture of an automatic early warning system (EWS) that aims at providing predictions and advice regarding security threats in information and communication tec...
Martin Apel, Joachim Biskup, Ulrich Flegel, Michae...
In this paper we show how to reduce downtime of J2EE applications by rapidly and automatically recovering from transient and intermittent software failures, without requiring appl...
George Candea, Emre Kiciman, Shinichi Kawamoto, Ar...