Abstract. Systems supporting situation awareness typically integrate information about a large number of real-world objects anchored in time and space provided by multiple sources....
Norbert Baumgartner, Wolfgang Gottesheim, Stefan M...
—Accurate and timely detection of infectious disease outbreaks provides valuable information which can enable public health officials to respond to major public health threats in...
—Anomaly detection methods typically operate on pre-processed, i.e., sampled and aggregated, traffic traces. Most traffic capturing devices today employ random packet sampling,...
Despite the advances reached along the last 20 years, anomaly detection in network behavior is still an immature technology, and the shortage of commercial tools thus corroborates...
In this paper, we try to develop a machine learning-based virus email detection method. The key feature of this paper is employing Mail Header and Encoding Anomaly(MHEA) [1]. MHEA ...
Automated bot/botnet detection is a difficult problem given the high level of attacker power. We propose a systematic approach for evaluating the evadability of detection methods....
Anomaly detection methods can be very useful in identifying unusual or interesting patterns in data. A recently proposed conditional anomaly detection framework extends anomaly de...
The potentially catastrophic impact of a bioterrorist attack makes developing effective detection methods essential for public health. In the case of anthrax attack, a delay of ho...
Algorithms for detecting anomalous events can be divided into those that are designed to detect specific diseases and those that are non-specific in what they detect. Specific dete...
— This paper presents a novel human detection method based on a Bayesian fusion approach using laser range data and camera images. Laser range data analysis groups data points wi...