This paper proposes an effective anomaly detection algorithm for a forward-looking ground-penetrating radar (FLGPR). One challenge for threat detection using FLGPR is its high dynamic range in response to different kinds of targets and clutter objects. The application of a fixed threshold for detection often yields a large number of false alarms. We propose a locally-adaptive detection method t...

Plagiarism detection has been considered as a classification problem which can be approximated with intrinsic strategies, considering self-based information from a given document, and external strategies, considering comparison techniques between a suspicious document and different sources. In this work, both intrinsic and external approaches for plagiarism detection are presented. First, the m...

Algorithms for anomaly detection in IP networks have been developed and a real-time distributed platform for anomaly detection has been implemented. These algorithms automatically and adaptively detect “soft” network faults (performance degradations) in IP networks. These algorithms are implemented as a reliable and fully distributed real-time software platform called NSAD (Network/Service Anom...

Anomaly detection in networks is detection of deviations from what is considered to be normal. Performing anomaly detection is a learning approach to detect failures and intrusions in a network, intended to capture novel attacks. Anomaly Detection With fast Incremental Clustering (ADWICE) is an efficient algorithm to detect anomaly. But, since it uses distance based clustering mechanism it suff...

Techniques for video object motion analysis, behaviour recognition and event detection are becoming increasingly important with the rapid increase in demand for and deployment of video surveillance systems. Motion trajectories provide rich spatiotemporal information about an object’s activity. This paper presents a novel technique for classification of motion activity and anomaly detection usin...

We show how the coupling of gravitinos and gauginos to fluxes modifies anomaly cancellation in M-theory on a manifold with boundary. Anomaly cancellation continues to hold, after a shift of the definition of the gauge currents by a local gauge invariant expression in the curvatures and E 8 fieldstrengths. We compute the first nontrivial correction of

We deal with the problem of diffeomorphism anomaly in theories with branes. In particular we thoroughly analyze the problem of the residual chiral anomaly of a five–brane immersed in M–theory, paying attention to its global formulation in the five–brane world–volume. We conclude that the anomaly can be canceled by a local counterterm in the five–brane world–volume.

We show that inflation which is dominated by the D-term density avoids the 'slow-roll' problem of inflation in supergravity. Such an inflationary scenario can naturally emerge in theories with non-anomalous or anomalous U(1) gauge symmetry. In the latter case the scale of inflation is fixed by the Green–Schwarz mechanism of anomaly cancellation. The crucial point is that the (super)gravity-medi...

Anomaly detection approaches build models of normal data and detect deviations from the normal model in observed data. Anomaly detection applied to intrusion detection and computer security has been an active area of research. The major benefit of anomaly detection algorithms is their ability to potentially detect unforeseen attacks. In this paper, a novel weighted support vector clustering alg...

Most current network intrusion detection systems employ signature-based methods or data mining-based methods which rely on labeled training data. This training data is 90 typically expensive to produce. Moreover, these methods have difficulty in detecting new types of attack. In this paper, we have discussed anomaly based instruction detection, pros and cons of anomaly detection, supervised and...