Laser-assisted bumping for flip chip assembly

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Botnet Detection using Social Graph Analysis

Signature-based botnet detection methods identify botnets by recognizing Command and Control (C\&C) traffic and can be ineffective for botnets that use new and sophisticate mechanisms for such communications. To address these limitations, we propose a novel botnet detection method that analyzes the social relationships among nodes. The method consists of two stages: (i) anomaly detection in an "interaction" graph among nodes using large deviations results on the degree distribution, and (ii) community detection in a social "correlation" graph whose edges connect nodes with highly correlated communications. The latter stage uses a refined modularity measure and formulates the problem as a non-convex optimization problem for which appropriate relaxation strategies are developed. We apply our method to real-world botnet traffic and compare its performance with other community detection methods. The results show that our approach works effectively and the refined modularity measure improves the detection accuracy.Comment: 7 pages. Allerton Conferenc

Robust Anomaly Detection in Dynamic Networks

We propose two robust methods for anomaly detection in dynamic networks in which the properties of normal traffic are time-varying. We formulate the robust anomaly detection problem as a binary composite hypothesis testing problem and propose two methods: a model-free and a model-based one, leveraging techniques from the theory of large deviations. Both methods require a family of Probability Laws (PLs) that represent normal properties of traffic. We devise a two-step procedure to estimate this family of PLs. We compare the performance of our robust methods and their vanilla counterparts, which assume that normal traffic is stationary, on a network with a diurnal normal pattern and a common anomaly related to data exfiltration. Simulation results show that our robust methods perform better than their vanilla counterparts in dynamic networks.Comment: 6 pages. MED conferenc

Scalable solid-state quantum computation in decoherence-free subspaces with trapped ions

We propose a decoherence-free subspaces (DFS) scheme to realize scalable quantum computation with trapped ions. The spin-dependent Coulomb interaction is exploited, and the universal set of unconventional geometric quantum gates is achieved in encoded subspaces that are immune from decoherence by collective dephasing. The scalability of the scheme for the ion array system is demonstrated, either by an adiabatic way of switching on and off the interactions, or by a fast gate scheme with comprehensive DFS encoding and noise decoupling techniques.Comment: 4 pages, 1 figur

A metal–organic framework/α-alumina composite with a novel geometry for enhanced adsorptive separation

The development of a metal–organic framework/α-alumina composite leads to a novel concept: efficient adsorption occurs within a plurality of radial micro-channels with no loss of the active adsorbents during the process. This composite can effectively remediate arsenic contaminated water producing potable water recovery, whereas the conventional fixed bed requires eight times the amount of active adsorbents to achieve a similar performance

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

Efficient method for calculating the transmission coefficient of two-dimensional quantum wire structures

We present a very simple and efficient method for calculating the transmission coefficient of two-dimensional quantum wire structures based on the time-dependent solution of the Schrödinger equation. We apply the new method to a specific two-dimensional quantum wire structure. The new method is much faster than the finite element method and can be used to study electron transport in the presence of electron–phonon interaction and nonlinear interactions in the Schrödinger equation. ©1996 American Institute of Physics.published_or_final_versio

Curie temperature and critical thickness of ferroelectric thin films

Author name used in this publication: C. H. Woo2004-2005 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe