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Analytical models and methods for anomaly detection in dynamic, attributed graphs

Published in:
Chapter 2, Computational Network Analysis with R: Applications in Biology, Medicine, and Chemistry, 2017, pp. 35-61.

Summary

This chapter is devoted to anomaly detection in dynamic, attributed graphs. There has been a great deal of research on anomaly detection in graphs over the last decade, with a variety of methods proposed. This chapter discusses recent methods for anomaly detection in graphs,with a specific focus on detection within backgrounds based on random graph models. This sort of analysis can be applied for a variety of background models, which can incorporate topological dynamics and attributes of vertices and edges. The authors have developed a framework for anomalous subgraph detection in random background models, based on linear algebraic features of a graph. This includes an implementation in R that exploits structure in the random graph model for computationally tractable analysis of residuals. This chapter outlines this framework within the context of analyzing dynamic, attributed graphs. The remainder of this chapter is organized as follows. Section 2.2 defines the notation used within the chapter. Section 2.3 briefly describes a variety of perspectives and techniques for anomaly detection in graph-based data. Section 2.4 provides an overview of models for graph behavior that can be used as backgrounds for anomaly detection. Section 2.5 describes our framework for anomalous subgraph detection via spectral analysis of residuals, after the data are integrated over time. Section 2.6 discusses how the method described in Section 2.5 can be efficiently implemented in R using open source packages. Section 2.7 demonstrates the power of this technique in controlled simulation, considering the effects of both dynamics and attributes on detection performance. Section 2.8 gives a data analysis example within this context, using an evolving citation graph based on a commercially available document database of public scientific literature. Section 2.9 summarizes the chapter and discusses ongoing research in this area.
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Summary

This chapter is devoted to anomaly detection in dynamic, attributed graphs. There has been a great deal of research on anomaly detection in graphs over the last decade, with a variety of methods proposed. This chapter discusses recent methods for anomaly detection in graphs,with a specific focus on detection within...

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The TESS camera: modeling and measurements with deep depletion devices

Summary

The Transiting Exoplanet Survey Satellite, a NASA Explorer-class mission in development, will discover planets around nearby stars, most notably Earth-like planets with potential for follow up characterization. The all-sky survey requires a suite of four wide field-of-view cameras with sensitivity across a broad spectrum. Deep depletion CCDs with a silicon layer of 100 um thickness serve as the camera detectors, providing enhanced performance in the red wavelengths for sensitivity to cooler stars. The performance of the camera is critical for the mission objectives, with both the optical system and the CCD detectors contributing to the realized image quality. Expectations for image quality are studied using a combination of optical ray tracing in Zemax and simulations in Matlab to account for the interaction of the incoming photons with the 100 um silicon layer. The simulations include a probabilistic model to determine the depth of travel in the silicon before the photons are converted to photo-electrons, and a Monte Carlo approach to charge diffusion. The charge diffusion model varies with the remaining depth for the photo-electron to traverse and the strength of the intermediate electric field. The simulations are compared with laboratory measurements acquired by an engineering unit camera with the TESS optical design and deep depletion CCDs. In this paper we describe the performance simulations and the corresponding measurements taken with the engineering unit camera, and discuss where the models agree well in predicted trends and where there are differences compared to observations.
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Summary

The Transiting Exoplanet Survey Satellite, a NASA Explorer-class mission in development, will discover planets around nearby stars, most notably Earth-like planets with potential for follow up characterization. The all-sky survey requires a suite of four wide field-of-view cameras with sensitivity across a broad spectrum. Deep depletion CCDs with a silicon...

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Cross-domain entity resolution in social media

Published in:
4th Int. Workshop on Natural Language Processing for Social Media, SocialNLP with IJCAI, 11 July 2016.

Summary

The challenge of associating entities across multiple domains is a key problem in social media understanding. Successful cross-domain entity resolution provides integration of information from multiple sites to create a complete picture of user and community activities, characteristics, and trends. In this work, we examine the problem of entity resolution across Twitter and Instagram using general techniques. Our methods fall into three categories: profile, content, and graph based. For the profile-based methods, we consider techniques based on approximate string matching. For content-based methods, we perform author identification. Finally, for graph-based methods, we apply novel cross-domain community detection methods and generate neighborhood-based features. The three categories of methods are applied to a large graph of users in Twitter and Instagram to understand challenges, determine performance, and understand fusion of multiple methods. Final results demonstrate an equal error rate less than 1%.
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Summary

The challenge of associating entities across multiple domains is a key problem in social media understanding. Successful cross-domain entity resolution provides integration of information from multiple sites to create a complete picture of user and community activities, characteristics, and trends. In this work, we examine the problem of entity resolution...

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Apprenticeship scheduling: learning to schedule from human experts

Published in:
Proc. of the Int. Joint Conf. Artificial Intelligence (IJCAI), 9-15 July 2016.

Summary

Coordinating agents to complete a set of tasks with intercoupled temporal and resource constraints is computationally challenging, yet human domain experts can solve these difficult scheduling problems using paradigms learned through years of apprenticeship. A process for manually codifying this domain knowledge within a computational framework is necessary to scale beyond the "single expert, single-trainee" apprenticeship model. However, human domain experts often have difficulty describing their decision-making processes, causing the codification of this knowledge to become laborious. We propose a new approach for capturing domain-expert heuristics through a pairwise ranking formulation. Our approach is model-free and does not require enumerating or iterating through a large state-space. We empirically demonstrate that this approach accurately learns multifaceted heuristics on both a synthetic data set incorporating job-shop scheduling and vehicle routing problems and a real-world data set consisting of demonstrations of experts solving a weapon-to-target assignment problem.
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Summary

Coordinating agents to complete a set of tasks with intercoupled temporal and resource constraints is computationally challenging, yet human domain experts can solve these difficult scheduling problems using paradigms learned through years of apprenticeship. A process for manually codifying this domain knowledge within a computational framework is necessary to scale...

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Charting a security landscape in the clouds: data protection and collaboration in cloud storage

Summary

This report surveys different approaches to securely storing and sharing data in the cloud based on traditional notions of security: confidentiality, integrity, and availability, with the main focus on confidentiality. An appendix discusses the related notion of how users can securely authenticate to cloud providers. We propose a metric for comparing secure storage approaches based on their residual vulnerabilities: attack surfaces against which an approach cannot protect. Our categorization therefore ranks approaches from the weakest (the most residual vulnerabilities) to the strongest (the fewest residual vulnerabilities). In addition to the security provided by each approach, we also consider their inherent costs and limitations. This report can therefore help an organization select a cloud data protection approach that satisfies their enterprise infrastructure, security specifications, and functionality requirements.
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Summary

This report surveys different approaches to securely storing and sharing data in the cloud based on traditional notions of security: confidentiality, integrity, and availability, with the main focus on confidentiality. An appendix discusses the related notion of how users can securely authenticate to cloud providers. We propose a metric for...

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Directly-deposited blocking filters for high-performance silicon x-ray detectors

Published in:
SPIE, Vol. 9905, Space Telescopes and Instrumentation 2016: Ultraviolet to Gamma Ray, July 2016, 99054C.

Summary

Silicon X-ray detectors often require blocking filters to mitigate noise and out-of-band signal from UV and visible backgrounds. Such filters must be thin to minimize X-ray absorption, so direct deposition of filter material on the detector entrance surface is an attractive approach to fabrication of robust filters. On the other hand, the soft (E < 1 keV) X-ray spectral resolution of the detector is sensitive to the charge collection efficiency in the immediate vicinity of its entrance surface, so it is important that any filter layer is deposited without disturbing the electric field distribution there. We have successfully deposited aluminum blocking filters, ranging in thickness from 70 to 220nm, on back-illuminated CCD X-ray detectors passivated by means of molecular beam epitaxy. Here we report measurements showing that directly deposited filters have little or no effect on soft X-ray spectral resolution. We also find that in applications requiring very large optical density (> OD 6) care must be taken to prevent light from entering the sides and mounting surfaces of the detector. Our methods have been used to deposit filters on the detectors of the REXIS instrument scheduled to fly on OSIRIS-ReX later this year.
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Summary

Silicon X-ray detectors often require blocking filters to mitigate noise and out-of-band signal from UV and visible backgrounds. Such filters must be thin to minimize X-ray absorption, so direct deposition of filter material on the detector entrance surface is an attractive approach to fabrication of robust filters. On the other...

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Resonance fluorescence from an artificial atom in squeezed vacuum

Published in:
Phys. Rev. X, Vol. 6, No. 3, July-September 2016, 031004.

Summary

We present an experimental realization of resonance fluorescence in squeezed vacuum. We strongly couple microwave-frequency squeezed light to a superconducting artificial atom and detect the resulting fluorescence with high resolution enabled by a broadband traveling-wave parametric amplifier. We investigate the fluorescence spectra in the weak and strong driving regimes, observing up to 3.1 dB of reduction of the fluorescence linewidth below the ordinary vacuum level and a dramatic dependence of the Mollow triplet spectrum on the relative phase of the driving and squeezed vacuum fields. Our results are in excellent agreement with predictions for spectra produced by a two-level atom in squeezed vacuum [Phys. Rev. Lett. 58, 2539 (1987)], demonstrating that resonance fluorescence offers a resource-efficient means to characterize squeezing in cryogenic environments.
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Summary

We present an experimental realization of resonance fluorescence in squeezed vacuum. We strongly couple microwave-frequency squeezed light to a superconducting artificial atom and detect the resulting fluorescence with high resolution enabled by a broadband traveling-wave parametric amplifier. We investigate the fluorescence spectra in the weak and strong driving regimes, observing...

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The threat to weather radars by wireless technology

Published in:
Amer. Meteor. Soc., Vol. 97, No. 7, 1 July 2016, pp. 1159-67, doi: 10.1175/BAMS-D-15-00048.1.

Summary

Wireless technology, such as local area telecommunication networks and surveillance cameras, causes severe interference for weather radars, because they use the same operational radio frequencies. One or two disturbances can be removed from the radar image, but the number and power of the interfering wireless devices are growing all over the world, threatening that one day the radars could not be used at all. Some agencies have already changed or are considering changing frequency bands, but now even other bands are under threat. Use of equipment at radio frequencies is regulated by laws and international agreements. Technologies have been developed for peaceful co-existence. If wireless devices use these technologies to protect weather radars, their data transmission capabilities become limited, so it is tempting to violate the regulations. Hence, it is an important task for the worldwide weather community to involve themselves in the radio-frequency management process and work in close contact with their National Radio Authorities to ensure that meteorological interests be duly taken into account in any decision making process toward the future usage of wireless devices.
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Summary

Wireless technology, such as local area telecommunication networks and surveillance cameras, causes severe interference for weather radars, because they use the same operational radio frequencies. One or two disturbances can be removed from the radar image, but the number and power of the interfering wireless devices are growing all over...

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Balancing security and performance for agility in dynamic threat environments

Published in:
46th IEEE/IFIP Int. Conf. on Dependable Systems and Networks, DSN 2016, 28 June - 1 July 2016.

Summary

In cyber security, achieving the desired balance between system security and system performance in dynamic threat environments is a long-standing open challenge for cyber defenders. Typically an increase in system security comes at the price of decreased system performance, and vice versa, easily resulting in systems that are misaligned to operator specified requirements for system security and performance as the threat environment evolves. We develop an online, reinforcement learning based methodology to automatically discover and maintain desired operating postures in security-performance space even as the threat environment changes. We demonstrate the utility of our approach and discover parameters enabling an agile response to a dynamic adversary in a simulated security game involving prototype cyber moving target defenses.
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Summary

In cyber security, achieving the desired balance between system security and system performance in dynamic threat environments is a long-standing open challenge for cyber defenders. Typically an increase in system security comes at the price of decreased system performance, and vice versa, easily resulting in systems that are misaligned to...

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Multi-channel agile comb generator for antenna radiation pattern measurements

Published in:
IEEE Int. Symp. Antennas and Propagation (APSURSI), 26 June - 1 July 2016.

Summary

Antenna radiation patterns are typically measured using network analyzers, which are both expensive and physically large in size. These drawbacks can limit this test equipment's usage in universities that cannot afford to make such a purchase, as well as within applications that require mobile antenna measurements. An alternative approach is to combine a low-cost receiver with a flexible signal source. This paper presents the design of a tunable comb generator prototype that is capable of outputting frequencies up to 4 GHz. The compact nature of this source along with its potential to be dynamically reconfigured yields a device that can be used to measure antenna patterns for many different applications.
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Summary

Antenna radiation patterns are typically measured using network analyzers, which are both expensive and physically large in size. These drawbacks can limit this test equipment's usage in universities that cannot afford to make such a purchase, as well as within applications that require mobile antenna measurements. An alternative approach is...

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