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Computing on Masked Data to improve the security of big data

Published in:
HST 2015, IEEE Int. Conf. on Technologies for Homeland Security, 14-16 April 2015.

Summary

Organizations that make use of large quantities of information require the ability to store and process data from central locations so that the product can be shared or distributed across a heterogeneous group of users. However, recent events underscore the need for improving the security of data stored in such untrusted servers or databases. Advances in cryptographic techniques and database technologies provide the necessary security functionality but rely on a computational model in which the cloud is used solely for storage and retrieval. Much of big data computation and analytics make use of signal processing fundamentals for computation. As the trend of moving data storage and computation to the cloud increases, homeland security missions should understand the impact of security on key signal processing kernels such as correlation or thresholding. In this article, we propose a tool called Computing on Masked Data (CMD), which combines advances in database technologies and cryptographic tools to provide a low overhead mechanism to offload certain mathematical operations securely to the cloud. This article describes the design and development of the CMD tool.
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Summary

Organizations that make use of large quantities of information require the ability to store and process data from central locations so that the product can be shared or distributed across a heterogeneous group of users. However, recent events underscore the need for improving the security of data stored in such...

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Rapid sequence identification of potential pathogens using techniques from sparse linear algebra

Summary

The decreasing costs and increasing speed and accuracy of DNA sample collection, preparation, and sequencing has rapidly produced an enormous volume of genetic data. However, fast and accurate analysis of the samples remains a bottleneck. Here we present D4RAGenS, a genetic sequence identification algorithm that exhibits the Big Data handling and computational power of the Dynamic Distributed Dimensional Data Model (D4M). The method leverages linear algebra and statistical properties to increase computational performance while retaining accuracy by subsampling the data. Two run modes, Fast and Wise, yield speed and precision tradeoffs, with applications in biodefense and medical diagnostics. The D4RAGenS analysis algorithm is tested over several datasets, including three utilized for the Defense Threat Reduction Agency (DTRA) metagenomic algorithm contest.
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Summary

The decreasing costs and increasing speed and accuracy of DNA sample collection, preparation, and sequencing has rapidly produced an enormous volume of genetic data. However, fast and accurate analysis of the samples remains a bottleneck. Here we present D4RAGenS, a genetic sequence identification algorithm that exhibits the Big Data handling...

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Agent-based simulation for assessing network security risk due to unauthorized hardware

Published in:
SpringSim 2015: Spring Simulation Multiconference, 12-15 April 2015.

Summary

Computer networks are present throughout all sectors of our critical infrastructure and these networks are under a constant threat of cyber attack. One prevalent computer network threat takes advantage of unauthorized, and thus insecure, hardware on a network. This paper presents a prototype simulation system for network risk assessment that is intended for use by administrators to simulate and evaluate varying network environments and attacker/defender scenarios with respect to authorized and unauthorized hardware. The system is built on the agent-based modeling paradigm and captures emergent system dynamics that result from the interactions of multiple network agents including regular and administrator users, attackers, and defenders in a network environment. The agent-based system produces both metrics and visualizations that provide insights into network security risk and serve to guide the search for efficient policies and controls to protect a network from attacks related to unauthorized hardware. The simulation model is unique in the current literature both for its network threat model and its visualized agent-based approach. We demonstrate the model via a case study that evaluates risk for several candidate security policies on a representative computer network.
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Summary

Computer networks are present throughout all sectors of our critical infrastructure and these networks are under a constant threat of cyber attack. One prevalent computer network threat takes advantage of unauthorized, and thus insecure, hardware on a network. This paper presents a prototype simulation system for network risk assessment that...

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Broadband magnetometry and temperature sensing with a light-trapping diamond waveguide

Published in:
Nature Phys. Lett., Vol. 11, May 2015, pp. 393-7.

Summary

Solid-state quantum sensors are attracting wide interest because of their sensitivity at room temperature. In particular, the spin properties of individual nitrogen-vacancy (NV) colour centres in diamond make them outstanding nanoscale sensors of magnetic fields, electric fields and temperature under ambient conditions. Recent work on NV ensemble-based magnetometers, inertial sensors, and clocks has employed unentangled colour centres to realize significant improvements in sensitivity. However, to achieve this potential sensitivity enhancement in practice, new techniques are required to excite efficiently and to collect the optical signal from large NV ensembles. Here, we introduce a light-trapping diamond waveguide geometry with an excitation efficiency and signal collection that enables in excess of 5% conversion efficiency of pump photons into optically detected magnetic resonance (ODMR) fluorescence--an improvement over previous single-pass geometries of more than three orders of magnitude. This marked enhancement of the ODMR signal enables precision broadband measurements of magnetic field and temperature in the low-frequency range, otherwise inaccessible by dynamical decoupling techniques.
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Summary

Solid-state quantum sensors are attracting wide interest because of their sensitivity at room temperature. In particular, the spin properties of individual nitrogen-vacancy (NV) colour centres in diamond make them outstanding nanoscale sensors of magnetic fields, electric fields and temperature under ambient conditions. Recent work on NV ensemble-based magnetometers, inertial sensors...

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A study of crosstalk in a 256 x 256 photon counting imager based on silicon Geiger-mode avalanche photodiodes

Published in:
IEEE Sens. J., Vol. 15, No. 4, April 2015, pp. 2123-32.

Summary

We demonstrate a 256 x 256 passive photon counting imager based on hybridization of back-illuminated silicon Geiger-mode avalanche photodiodes to an all-digital CMOS counting chip. Photon detection efficiencies in the 10%-20% are observed at visible wavelengths. The detection efficiency is currently limited by optical crosstalk that leads to elevation of dark count rates as the bias voltage on the photodiodes is increased. Both the time dependence of dark count activity during a gate time and the spatial structure of dark images were successfully explained using crosstalk-based models.
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Summary

We demonstrate a 256 x 256 passive photon counting imager based on hybridization of back-illuminated silicon Geiger-mode avalanche photodiodes to an all-digital CMOS counting chip. Photon detection efficiencies in the 10%-20% are observed at visible wavelengths. The detection efficiency is currently limited by optical crosstalk that leads to elevation of...

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Detection statistics in Geiger-mode avalanche photodiode quad-cell arrays with crosstalk and dead time

Published in:
IEEE Sens. J., Vol. 15, No. 4, April 2015, pp. 2133-43.

Summary

The detection statistics of Geiger-mode photodetector subarrays with a combination of reset-time blocking loss and optical crosstalk are investigated. Closed-form expressions are obtained for the means and covariances of the numbers of counts in 2 x 2 subarrays (quad cells) used in Shack-Hartmann wavefront sensors. The predicted wavefront sensing precision is compared with that obtained with a charge-coupled device-based wavefront sensor with readout noise. The results of the theory are also used to predict photon transfer curves for the Geiger-mode device and these are compared with experiment.
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Summary

The detection statistics of Geiger-mode photodetector subarrays with a combination of reset-time blocking loss and optical crosstalk are investigated. Closed-form expressions are obtained for the means and covariances of the numbers of counts in 2 x 2 subarrays (quad cells) used in Shack-Hartmann wavefront sensors. The predicted wavefront sensing precision...

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Development and application of spherically curved charge-coupled device imagers

Summary

Operation of a CCD imager on a curved focal surface offers advantages to flat focal planes, especially for lightweight, relatively simple optical systems. The first advantage is that the modulation transfer function can approach diffraction-limited performance for a spherical focal surface employed in large field-of-view or large-format imagers. The second advantage is that a curved focal surface maintains more uniform illumination as a function of radius from the field center. Examples of applications of curved imagers, described here, include a small compact imager and the large curved array used in the Space Surveillance Telescope. The operational characteristics and mechanical limits of an imager deformed to a 15 mm radius are also described.
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Summary

Operation of a CCD imager on a curved focal surface offers advantages to flat focal planes, especially for lightweight, relatively simple optical systems. The first advantage is that the modulation transfer function can approach diffraction-limited performance for a spherical focal surface employed in large field-of-view or large-format imagers. The second...

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Measurement of ion motional heating rates over a range of trap frequencies and temperatures

Published in:
Phys. Rev. A, At. Mol. Opt. Phys., Vol. 91, No. 4, April 2015, 041402.

Summary

We present measurements of the motional heating rate of a trapped ion at different trap frequencies and temperatures between ~0.6 and 1.5 MHz and ~4 and 295 K. Additionally, we examine the possible effect of adsorbed surface contaminants with boiling points below ~105 degrees C by measuring the ion heating rate before and after locally baking our ion trap chip under ultrahigh vacuum conditions. We compare the heating rates presented here to those calculated from available electric-field noise models. We can tightly constrain a subset of these models based on their expected frequency and temperature scaling interdependence. Discrepancies between the measured results and predicted values point to the need for refinement of theoretical noise models in order to more fully understand the mechanisms behind motional trapped-ion heating.
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Summary

We present measurements of the motional heating rate of a trapped ion at different trap frequencies and temperatures between ~0.6 and 1.5 MHz and ~4 and 295 K. Additionally, we examine the possible effect of adsorbed surface contaminants with boiling points below ~105 degrees C by measuring the ion heating...

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Cryptographically secure computation

Published in:
Computer, Vol. 48, No. 4, April 2015, pp. 78-81.

Summary

Researchers are making secure multiparty computation--a cryptographic technique that enables information sharing and analysis while keeping sensitive inputs secret--faster and easier to use for application software developers.
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Summary

Researchers are making secure multiparty computation--a cryptographic technique that enables information sharing and analysis while keeping sensitive inputs secret--faster and easier to use for application software developers.

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Permittivity evaluation of multilayered hyperbolic metamaterials: ellipsometry vs. reflectometry

Published in:
J. Appl. Phys., Vol. 117, No. 10, 14 March 2015, 103104.

Summary

Metal-dielectric nanolaminates represent a class of hyperbolic metamaterials with uniaxial permittivity tensor. In this study, we critically compare permittivity extraction of nanolaminate samples using two techniques: polarized reflectrometry vs. spectroscopic anisotropic ellipsometry. Both Au/MgF2 and Ag/MgF2 metal-dielectric stacks are examined. We demonstrate the applicability of the treatment of the multilayered material as a uniaxial medium and compare the derived optical parameters to those expected from the effective medium approximation. We also experimentally compare the effect of varying the material outer layer on the homogenization of the composite. Additionally, we introduce a simple empirical method of extracting the epsilon-near-zero point of the nanolaminates from normal incidence reflectance. The results of this study are useful in accurate determination of the hyperbolic material permittivity and in the ability to tune its optical properties.
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Summary

Metal-dielectric nanolaminates represent a class of hyperbolic metamaterials with uniaxial permittivity tensor. In this study, we critically compare permittivity extraction of nanolaminate samples using two techniques: polarized reflectrometry vs. spectroscopic anisotropic ellipsometry. Both Au/MgF2 and Ag/MgF2 metal-dielectric stacks are examined. We demonstrate the applicability of the treatment of the multilayered...

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