Network anomaly detection: a survey and comparative analysis of stochastic and deterministic methods

7 pages. 1 more figure than final CDC 2013 versionWe present five methods to the problem of network anomaly detection. These methods cover most of the common techniques in the anomaly detection field, including Statistical Hypothesis Tests (SHT), Support Vector Machines (SVM) and clustering analysis. We evaluate all methods in a simulated network that consists of nominal data, three flow-level anomalies and one packet-level attack. Through analyzing the results, we point out the advantages and disadvantages of each method and conclude that combining the results of the individual methods can yield improved anomaly detection results

Linear response theory and optimal control for a molecular system under nonequilibrium conditions

In this paper, we propose a straightforward generalization of linear response theory to systems in nonequilibrium that are subject to nonequilibrium driving. We briefly revisit the standard linear response result for equilibrium systems, where we consider Langevin dynamics as a special case, and then give an alternative derivation using a change-of-measure argument that does not rely on any stationarity or reversibility assumption. This procedure moreover easily enables us to calculate the second order correction to the linear response formula (which may or may not be useful in practice). Furthermore, we outline how the novel nonequilibirum linear response formula can be used to compute optimal controls of molecular systems for cases in which one wants to steer the system to maximize a certain target expectation value. We illustrate our approach with simple numerical examples

Behavior of a movable electrode in piezo-response mode of an atomic force microscope

Author name used in this publication: C. H. XuAuthor name used in this publication: C. H. WooAuthor name used in this publication: S. Q. ShiAuthor name used in this publication: Y. Wang2003-2004 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Dependence of the optical conductivity on the uniaxial and biaxial strains in black phosphorene

© 2018 American Physical Society. By using the Kubo formula, the optical conductivity of strained black phosphorene was studied. The anisotropic band dispersion gives rise to an orientation dependent optical conductivity. The energy gap can be tuned by the uniaxial and biaxial strains which can be observed from the interband optical conductivity polarized along the armchair (x) direction. The preferential conducting direction is along the x direction. The dependence of the intraband optical conductivity along the zigzag (y) direction on the Fermi energy and strain exhibits increasing or decreasing monotonously. However, along the x direction this dependence is complicated which originates from the carriers' inverse-direction movements obtained by two types of the nearest phosphorus atom interactions. The modification of the biaxial strain on the energy structure and optical-absorption property is more effective. The imaginary part of the total optical conductivity (Imσ) can be negative around the threshold of the interband optical transition by modifying the chemical potential. Away from this frequency region, Imσ exhibits positive value. It can be used in the application of the surface plasmon propagations in multilayer dielectric structures

The tuned absorptance in multilayer graphene-dielectric structures by intraband transition

© 2017 Author(s). In this work, using the transfer-matrix method, the optical transport process is investigated, with graphene inserted into multilayer dielectric structures, theoretically and numerically in the THz regime. When the incident frequency is lower than the graphene Fermi energy, the optical intra-band transitions provide the main contribution to the graphene surface current. The absorptance can be enhanced to about 50% with only one graphene/dielectric layer in air. When increasing the number of dielectric layers coated with graphene, the absorption increases. Periodic absorption peaks are observed in multilayer structures. The positions of the absorption peaks as a function of the frequency and the incident angle are in accordance with the positions of the abrupt change in the reflection coefficient phase and of the imaginary solution of the Bloch wavevector in expanding periodic structures using Bloch theorem

Grand-canonical-like molecular-dynamics simulations by using an adaptive-resolution technique

n this work, we provide a detailed theoretical analysis, supported by numerical tests, of the reliability of the adaptive resolution simulation (AdResS) technique in sampling the Grand Canonical ensemble. We demonstrate that the correct density and radial distribution functions in the hybrid region, where molecules change resolution, are two necessary conditions for considering the atomistic and coarse-grained regions in AdResS equivalent to subsystems of a full atomistic system with an accuracy up to the second order with respect to the probability distribution of the system. Moreover, we show that the work done by the thermostat and a thermodynamic force in the transition region is formally equivalent to balance the chemical potential difference between the different resolutions. From these results follows the main conclusion that the atomistic region exchanges molecules with the coarse-grained region in a Grand Canonical fashion with an accuracy up to (at least) second order. Numerical tests, for the relevant case of liquid water at ambient conditions, are carried out to strengthen the conclusions of the theoretical analysis. Finally, in order to show the computational convenience of AdResS as a Grand Canonical set up, we compare our method to the Insertion Particle Method (IMP) in its most efficient computational implementation. This fruitful combination of theoretical principles and numerical evidence candidates the adaptive resolution technique as a natural, general and efficient protocol for Grand Canonical Molecular Dynamics for the case of large systems

Properties of Si-SiO2 interface traps due to low-energy Ar+ backsurface bombardment in n-channel nitrided MOSFETs

Flicker noise in backsurface gettered, nitrided n-channel MOSFETs is characterized over a wide range of temperatures and biases. The gettering time ranged from 10 to 40 minutes. The noise power spectra for devices with different gettering times are compared to the ungettered devices which serve as the control. It is found that flicker noise is reduced by backsurface gettering for short gettering times. A rebound in the noise magnitude is observed for long gettering times. Investigations of the temperature dependencies of the noise power spectra indicates that the low-frequency noise arises from thermal activation of carriers to traps at the Si-SiO2 interface. Backsurface gettering results in the modification of the energy distribution of the interface traps, probably due to stress relaxation at the Si-SiO2 interface.published_or_final_versio

Macroscopic phase segregation in superconducting K0.73Fe1.67Se2 as seen by muon spin rotation and infrared spectroscopy

Using muon spin rotation (\muSR) and infrared spectroscopy we investigated the recently discovered superconductor K0.73Fe1.67Se2 with Tc = 32 K. We show that the combined data can be consistently described in terms of a macroscopically phase segregated state with a matrix of ~88% volume fraction that is insulating and strongly magnetic and inclusions with a ~12% volume fraction which are metallic, superconducting and non-magnetic. The electronic properties of the latter, in terms of the normal state plasma frequency and the superconducting condensate density, appear to be similar as in other iron selenide or arsenide superconductors.Comment: 22 pages, 8 figures. (citation list correction.

Applications of the cross-entropy method to importance sampling and optimal control of diffusions

Abstract. We study the cross-entropy method for diffusions. One of the results is a versatile cross-entropy algorithm that can be used to design efficient importance sampling strategies for rare events or to solve optimal control problems. The approach is based on the minimization of a suitable cross-entropy functional, with a parametric family of exponentially tilted probability distributions. We illustrate the new algorithm with several numerical examples and discuss algorithmic issues and possible extensions of the method. Key words. importance sampling, optimal control, cross-entropy method, rare events, change of measure. AMS subject classifications. 1 Introduction This article deals with the application of the cross-entropy method to diffusion processes, specifically, with the application to importance sampling for rare events and optimal control. Generally, the cross-entropy method is a Monte-Carlo method that was originally developed for the efficient simulation of rare events in queuing models and that has been extended to, e.g., combinatorial optimization or analysis of networks in the meantim

Coupled clustering ensemble by exploring data interdependence

© 2018 ACM. Clustering ensembles combine multiple partitions of data into a single clustering solution. It is an effective technique for improving the quality of clustering results. Current clustering ensemble algorithms are usually built on the pairwise agreements between clusterings that focus on the similarity via consensus functions, between data objects that induce similarity measures from partitions and re-cluster objects, and between clusters that collapse groups of clusters into meta-clusters. In most of those models, there is a strong assumption on IIDness (i.e., independent and identical distribution), which states that base clusterings perform independently of one another and all objects are also independent. In the real world, however, objects are generally likely related to each other through features that are either explicit or even implicit. There is also latent but definite relationship among intermediate base clusterings because they are derived from the same set of data. All these demand a further investigation of clustering ensembles that explores the interdependence characteristics of data. To solve this problem, a new coupled clustering ensemble (CCE) framework that works on the interdependence nature of objects and intermediate base clusterings is proposed in this article. The main idea is to model the coupling relationship between objects by aggregating the similarity of base clusterings, and the interactive relationship among objects by addressing their neighborhood domains. Once these interdependence relationships are discovered, they will act as critical supplements to clustering ensembles. We verified our proposed framework by using three types of consensus function: clustering-based, object-based, and cluster-based. Substantial experiments on multiple synthetic and real-life benchmark datasets indicate that CCE can effectively capture the implicit interdependence relationships among base clusterings and among objects with higher clustering accuracy, stability, and robustness compared to 14 state-of-the-art techniques, supported by statistical analysis. In addition, we show that the final clustering quality is dependent on the data characteristics (e.g., quality and consistency) of base clusterings in terms of sensitivity analysis. Finally, the applications in document clustering, as well as on the datasets with much larger size and dimensionality, further demonstrate the effectiveness, efficiency, and scalability of our proposed models