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Bootstrapping and Maintaining Trust in the Cloud(469.63 KB)

Date:
December 5, 2016
Published in:
Proceedings of the 32nd Annual Computer Security Applications Conference, ACSAC 2016
Type:
Conference Paper

Summary

Today's infrastructure as a service (IaaS) cloud environments rely upon full trust in the provider to secure applications and data. In this paper we introduce keylime, a scalable trusted cloud key management system. Keylime provides an end-to-end solution for both bootstrapping hardware rooted cryptographic identities for IaaS nodes and for system integrity monitoring of those nodes via periodic attestation.

Biomimetic Sniffing Improves the Detection Performance of a 3D Printed Nose of a Dog and a Commercial Trace Vapor Detector(677.58 KB)

Date:
December 1, 2016
Published in:
Nature Scientific Reports, vol. 6
Type:
Journal Article

Summary

Unlike current chemical trace detection technology, dogs actively sniff to acquire an odor sample. Flow visualization experiments with an anatomically-similar 3D printed dog’s nose revealed the external aerodynamics during canine sniffing, where ventral-laterally expired air jets entrain odorant-laden air toward the nose, thereby extending the “aerodynamic reach” for inspiration of otherwise inaccessible odors. Chemical sampling and detection experiments quantified two modes of operation with the artificial nose-active sniffing and continuous inspiration-and demonstrated an increase in odorant detection by a factor of up to 18 for active sniffing. A 16-fold improvement in detection was demonstrated with a commercially-available explosives detector by applying this bio-inspired design principle and making the device “sniff” like a dog. These lessons learned from the dog may benefit the next-generation of vapor samplers for explosives, narcotics, pathogens, or even cancer, and could inform future bio-inspired designs for optimized sampling of odor plumes.

Large Enhancement of Third-Order Nonlinear Effects with a Resonant All-Dielectric Metasurface

Date:
December 1, 2016
Published in:
AIP Advances, vol. 6
Type:
Journal Article
Topic:

Summary

A novel low-profile nonlinear metasurface, consisting of a single-layer of all-dielectric material, is proposed and numerically investigated by a nonlinear full-wave finite-difference time-domain (FDTD) method. The proposed metasurface is transparent for low, and opaque for high values of incident light intensity. The metasurface design is broadly applicable to enhancement of intrinsic nonlinearities of any material with a sufficiently high refractive index contrast. We illustrate the ability of this design to enhance intrinsic nonlinear absorption of a transition metal oxide, vanadium pentoxide (V2O5), with resonant metasurface elements. The complex third-order nonlinear susceptibility (χ(3)) for V2O5, representing both nonlinear refraction and absorption is considered in FDTD simulations. Our design achieves high initial transparency (>90%) for low incident light intensity. An order of magnitude decrease in the required input light intensity threshold for nonlinear response of the metasurface is observed in comparison with an unpatterend film. The proposed all-dielectric metasurface in this work is ultrathin and easy to fabricate. We envision a number of applications of this design for thin film coatings that offer protection against high-power laser radiation.

Terminal Flight Data Manager (TFDM) Environmental Benefits Assessment(2.35 MB)

Date:
November 10, 2016
Published in:
Project Report ATC-420, MIT Lincoln Laboratory
Type:
Project Report

Summary

This work monetizes the environmental benefits of Terminal Flight Data Manager (TFDM) capabilities which reduce fuel burn and gaseous emissions, and in turn reduce climate change and air quality effects.

Leveraging Data Provenance to Enhance Cyber Resilience(273.48 KB)

Date:
November 3, 2016
Published in:
Proceedings of 1st IEEE Cybersecurity Development Conference (SecDev'16), Boston, Mass.
Type:
Conference Paper

Summary

Creating bigger and better walls to keep adversaries out of our systems has been a failing strategy. The recent attacks against Target and Sony Pictures, to name a few, further emphasize this. Data provenance is a critical technology in building resilient systems that will allow systems to recover from attackers that manage to overcome the “hard-shell” defenses. In this paper, we provide background information on data provenance, details on provenance collection, analysis, and storage techniques and challenges.

Electrically Switchable Diffractive Waveplates with Metasurface Aligned Liquid Crystals(2.02 MB)

Date:
October 17, 2016
Published in:
Optics Express, vol. 24, no. 21
Type:
Journal Article
Topic:

Summary

Diffractive waveplates and equivalent metasurfaces provide a promising path for applications in thin film beam steering, tunable lenses, and polarization filters. However, fixed metasurfaces alone are unable to be tuned electronically. By combining metasurfaces with tunable liquid crystals, we experimentally demonstrate a single layer device capable of electrically switching a diffractive waveplate design at a measured peak diffraction efficiency of 35%, and a minimum switching voltage of 10V. Furthermore, the nano-scale metasurface aligned liquid crystals are largely independent of variations in wavelength and temperature. We also present a computational analysis of the efficiency limits of liquid crystal based diffractive waveplates, and compare this analysis to experimental measurements.

POPE: Partial Order Preserving Encoding(589.23 KB)

Date:
October 16, 2016
Published in:
Proceedings of the ACM Conference on Computer and Communications Security (CCS)
Type:
Conference Paper
Topic:

Summary

Recently there has been much interest in performing search queries over encrypted data to enable functionality while protecting sensitive data. One particularly efficient mechanism for executing such queries is order-preserving encryption/encoding (OPE). In this paper, we propose an alternative approach to range queries over encrypted data that is optimized to support insert-heavy workloads as are common in “big data” applications while still maintaining search functionality and achieving stronger security.

Detecting Depression using Vocal, Facial and Semantic Communication Cues(308.97 KB)

Date:
October 15, 2016
Published in:
Proceedings of the Audio Visual Emotion Challenge and Workshop, Amsterdam, The Netherlands
Type:
Conference Paper
Topic:

Summary

Major depressive disorder (MDD) is known to result in neurophysiological and neurocognitive changes that affect control of motor, linguistic, and cognitive functions. These changes are associated with a decline in dynamics and coordination of speech and facial motor control, while neurocognitive changes influence dialogue semantics. In this paper, biomarkers are derived from all of these modalities.

Multi-Modal Audio, Video, and Physiological Sensor Learning for Continuous Emotion Prediction(451.61 KB)

Date:
October 15, 2016
Published in:
Proceedings of 2016 AVEC Workshop, ACM Multimedia
Type:
Conference Paper
Topic:

Summary

The automatic determination of emotional state from multimedia content is an inherently challenging problem with a broad range of applications including biomedical diagnostics, multimedia retrieval, and human computer interfaces. This paper provides an overview of our AVEC Emotion Challenge system, which uses multi-feature learning and fusion across all available modalities.

Use of Photoacoustic Excitation and Laser Vibrometry to Remotely Detect Trace Explosives

Date:
October 6, 2016
Published in:
Applied Optics, vol. 55, no. 32
Type:
Journal Article

Summary

In this paper, we examine a laser-based approach to remotely initiate, measure, and differentiate acoustic and vibrational emissions from trace quantities of explosive materials against their environment. Using a pulsed ultraviolet laser (266 nm), we induce a significant (>100  Pa) photoacoustic response from small quantities of military-grade explosives. The photoacoustic signal, with frequencies predominantly between 100 and 500 kHz, is detected remotely via a wideband laser Doppler vibrometer. This two-laser system can be used to rapidly detect and discriminate explosives from ordinary background materials, which have significantly weaker photoacoustic response. A 100  ng/cm2 limit of detection is estimated. Photoablation is proposed as the dominant mechanism for the large photoacoustic signals generated by explosives.