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Cloudbreak: answering the challenges of cyber command and control

Published in:
Lincoln Laboratory Journal, Vol. 22, No. 1, 2016, pp. 60-73.

Summary

Lincoln Laboratory's flexible, user-centered framework for the development of command-and-control systems allows the rapid prototyping of new system capabilities. This methodology, Cloudbreak, effectively supports the insertion of new capabilities into existing systems and fosters user acceptance of new tools.
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Summary

Lincoln Laboratory's flexible, user-centered framework for the development of command-and-control systems allows the rapid prototyping of new system capabilities. This methodology, Cloudbreak, effectively supports the insertion of new capabilities into existing systems and fosters user acceptance of new tools.

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Threat-based risk assessment for enterprise networks

Published in:
Lincoln Laboratory Journal, Vol. 22, No. 1, 2016, pp. 33-45.

Summary

Protecting enterprise networks requires continuous risk assessment that automatically identifies and prioritizes cyber security risks, enables efficient allocation of cyber security resources, and enhances protection against modern cyber threats. Lincoln Laboratory created a network security model to guide the development of such risk assessments and, for the most important cyber threats, designed practical risk metrics that can be computed automatically and continuously from security-relevant network data.
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Summary

Protecting enterprise networks requires continuous risk assessment that automatically identifies and prioritizes cyber security risks, enables efficient allocation of cyber security resources, and enhances protection against modern cyber threats. Lincoln Laboratory created a network security model to guide the development of such risk assessments and, for the most important cyber...

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Finding malicious cyber discussions in social media

Summary

Today's analysts manually examine social media networks to find discussions concerning planned cyber attacks, attacker techniques and tools, and potential victims. Applying modern machine learning approaches, Lincoln Laboratory has demonstrated the ability to automatically discover such discussions from Stack Exchange, Reddit, and Twitter posts written in English.
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Summary

Today's analysts manually examine social media networks to find discussions concerning planned cyber attacks, attacker techniques and tools, and potential victims. Applying modern machine learning approaches, Lincoln Laboratory has demonstrated the ability to automatically discover such discussions from Stack Exchange, Reddit, and Twitter posts written in English.

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Scalability of VM provisioning systems

Summary

Virtual machines and virtualized hardware have been around for over half a century. The commoditization of the x86 platform and its rapidly growing hardware capabilities have led to recent exponential growth in the use of virtualization both in the enterprise and high performance computing (HPC). The startup time of a virtualized environment is a key performance metric for high performance computing in which the runtime of any individual task is typically much shorter than the lifetime of a virtualized service in an enterprise context. In this paper, a methodology for accurately measuring the startup performance on an HPC system is described. The startup performance overhead of three of the most mature, widely deployed cloud management frameworks (OpenStack, OpenNebula, and Eucalyptus) is measured to determine their suitability for workloads typically seen in an HPC environment. A 10x performance difference is observed between the fastest (Eucalyptus) and the slowest (OpenNebula) framework. This time difference is primarily due to delays in waiting on networking in the cloud-init portion of the startup. The methodology and measurements presented should facilitate the optimization of startup across a variety of virtualization environments.
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Summary

Virtual machines and virtualized hardware have been around for over half a century. The commoditization of the x86 platform and its rapidly growing hardware capabilities have led to recent exponential growth in the use of virtualization both in the enterprise and high performance computing (HPC). The startup time of a...

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Building Resource Adaptive Software Systems (BRASS): objectives and system evaluation

Summary

As modern software systems continue inexorably to increase in complexity and capability, users have become accustomed to periodic cycles of updating and upgrading to avoid obsolescence—if at some cost in terms of frustration. In the case of the U.S. military, having access to well-functioning software systems and underlying content is critical to national security, but updates are no less problematic than among civilian users and often demand considerable time and expense. To address these challenges, DARPA has announced a new four-year research project to investigate the fundamental computational and algorithmic requirements necessary for software systems and data to remain robust and functional in excess of 100 years. The Building Resource Adaptive Software Systems, or BRASS, program seeks to realize foundational advances in the design and implementation of long-lived software systems that can dynamically adapt to changes in the resources they depend upon and environments in which they operate. MIT Lincoln Laboratory will provide the test framework and evaluation of proposed software tools in support of this revolutionary vision.
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Summary

As modern software systems continue inexorably to increase in complexity and capability, users have become accustomed to periodic cycles of updating and upgrading to avoid obsolescence—if at some cost in terms of frustration. In the case of the U.S. military, having access to well-functioning software systems and underlying content is...

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Airspace flow rate forecast algorithms, validation, and implementation

Summary

This report summarizes work performed by MIT Lincoln Laboratory during the period 1 February 2015 - 30 November 2015 focused on developing and improving algorithms to estimate the impact of convective weather on air traffic flows. The core motivation for the work is the need to improve strategic traffic flow management decision-making in the National Airspace System. The algorithms developed as part of this work translate multiple weather forecast products into a discrete airspace impact metric called permeability.
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Summary

This report summarizes work performed by MIT Lincoln Laboratory during the period 1 February 2015 - 30 November 2015 focused on developing and improving algorithms to estimate the impact of convective weather on air traffic flows. The core motivation for the work is the need to improve strategic traffic flow...

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Photothermal speckle modulation for noncontact materials characterization

Summary

We have developed a noncontact, photothermal materials characterization method based on visible-light speckle imaging. This technique is applied to remotely measure the infrared absorption spectra of materials and to discriminate materials based on their thermal conductivities. A wavelength-tunable (7.5-8.7 um), intensity-modulated, quantum cascade pump laser and a continuous-wave 532 nm probe laser illuminate a sample surface such that the two laser spots overlap. Surface absorption of the intensity-modulated pump laser induces a time-varying thermoelastic surface deformation, resulting in a time-varying 532 nm scattering speckle field from the surface. The speckle modulation amplitude, derived from a series of visible camera images, is found to correlate with the amplitude of the surface motion. By tuning the pump laser's wavelength over a molecular absorption feature, the amplitude spectrum of the speckle modulation is found to correlate to the IR absorption spectrum. As an example, we demonstrate this technique for spectroscopic identification of thin polymeric films. Furthermore, by adjusting the rate of modulation of the pump beam and measuring the associated modulation transfer to the visible speckle pattern, information about the thermal time constants of surface and sub-surface features can be revealed. Using this approach, we demonstrate the ability to distinguish between different materials (including metals, semiconductors, and insulators) based on differences in their thermal conductivities.
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Summary

We have developed a noncontact, photothermal materials characterization method based on visible-light speckle imaging. This technique is applied to remotely measure the infrared absorption spectra of materials and to discriminate materials based on their thermal conductivities. A wavelength-tunable (7.5-8.7 um), intensity-modulated, quantum cascade pump laser and a continuous-wave 532 nm...

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Analysis of factors affecting system performance in the ASpIRE challenge

Published in:
2015 IEEE Automatic Speech Recognition and Understanding Workshop, ASRU 2015, 13-17 December 2015.

Summary

This paper presents an analysis of factors affecting system performance in the ASpIRE (Automatic Speech recognition In Reverberant Environments) challenge. In particular, overall word error rate (WER) of the solver systems is analyzed as a function of room, distance between talker and microphone, and microphone type. We also analyze speech activity detection performance of the solver systems and investigate its relationship to WER. The primary goal of the paper is to provide insight into the factors affecting system performance in the ASpIRE evaluation set across many systems given annotations and metadata that are not available to the solvers. This analysis will inform the design of future challenges and provide insight into the efficacy of current solutions addressing noisy reverberant speech in mismatched conditions.
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Summary

This paper presents an analysis of factors affecting system performance in the ASpIRE (Automatic Speech recognition In Reverberant Environments) challenge. In particular, overall word error rate (WER) of the solver systems is analyzed as a function of room, distance between talker and microphone, and microphone type. We also analyze speech...

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NetProf iOS pronunciation feedback demonstration

Published in:
IEEE Automatic Speech Recognition and Understanding Workshop, ASRU, 13 December 2015.

Summary

One of the greatest challenges for an adult learning a new language is gaining the ability to distinguish and produce foreign sounds. The US Government trains 3,600 enlisted soldiers a year at the Defense Language Institute Foreign Language Center (DLIFLC) in languages critical to national security, most of which are not widely studied in the U.S. Many students struggle to attain speaking fluency and proper pronunciation. Teaching pronunciation is a time-intensive task for teachers that requires them to give individual feedback to students during classroom hours. This limits the time teachers can spend imparting other information, and students may feel embarrassed or inhibited when they practice with their classmates. Given the demand for students educated in foreign languages and the limited number of qualified teachers in languages of interest, there is a growing need for computer-based tools students can use to practice and receive feedback at their own pace and schedule. Most existing tools are limited to listening to pre-recorded audio with limited or nonexistent support for pronunciation feedback. MIT Lincoln Laboratory has developed a new tool, Net Pronunciation Feedback (NetProF), to address these challenges and improve student pronunciation and general language fluency.
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Summary

One of the greatest challenges for an adult learning a new language is gaining the ability to distinguish and produce foreign sounds. The US Government trains 3,600 enlisted soldiers a year at the Defense Language Institute Foreign Language Center (DLIFLC) in languages critical to national security, most of which are...

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Assessing functional neural connectivity as an indicator of cognitive performance

Published in:
5th NIPS Workshop on Machine Learning and Interpretation in Neuroimaging, MLINI 2015, 11-12 December 2015.

Summary

Studies in recent years have demonstrated that neural organization and structure impact an individual's ability to perform a given task. Specifically, individuals with greater neural efficiency have been shown to outperform those with less organized functional structure. In this work, we compare the predictive ability of properties of neural connectivity on a working memory task. We provide two novel approaches for characterizing functional network connectivity from electroencephalography (EEG), and compare these features to the average power across frequency bands in EEG channels. Our first novel approach represents functional connectivity structure through the distribution of eigenvalues making up channel coherence matrices in multiple frequency bands. Our second approach creates a connectivity network at each frequency band, and assesses variability in average path lengths of connected components and degree across the network. Failures in digit and sentence recall on single trials are detected using a Gaussian classifier for each feature set, at each frequency band. The classifier results are then fused across frequency bands, with the resulting detection performance summarized using the area under the receiver operating characteristic curve (AUC) statistic. Fused AUC results of 0.63/0.58/0.61 for digit recall failure and 0.58/0.59/0.54 for sentence recall failure are obtained from the connectivity structure, graph variability, and channel power features respectively.
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Summary

Studies in recent years have demonstrated that neural organization and structure impact an individual's ability to perform a given task. Specifically, individuals with greater neural efficiency have been shown to outperform those with less organized functional structure. In this work, we compare the predictive ability of properties of neural connectivity...

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