Publications

Refine Results

(Filters Applied) Clear All

A compact end cryptographic unit for tactical unmanned systems

July 11, 2019
  |
Conference Paper
Author:
Hoa G. Nguyen
…
Published in:
Proc. SPIE 11021, Unmanned Systems Technology XXI, 11 July 2019, 1102101.
Topic:
cyber security
R&D area:
R&D group:

Summary

Under the Navy's Flexible Cyber-Secure Radio (FlexCSR) program, the Naval Information Warfare Center Pacific and the Massachusetts Institute of Technology's Lincoln Laboratory are jointly developing a unique cybersecurity solution for tactical unmanned systems (UxS): the FlexCSR Security/Cyber Module (SCM) End Cryptographic Unit (ECU). To deal with possible loss of unmanned systems that contain the device, the SCM ECU uses only publicly available Commercial National Security Algorithms and a Tactical Key Management system to generate and distribute onboard mission keys that are destroyed at mission completion or upon compromise. This also significantly reduces the logistic complexity traditionally involved with protection and loading of classified cryptographic keys. The SCM ECU is on track to be certified by the National Security Agency for protecting tactical data-in-transit up to Secret level. The FlexCSR SCM ECU is the first stand-alone cryptographic module that conforms to the United States Department of Defense (DoD) Joint Communications Architecture for Unmanned Systems, an initiative by the Office of the Secretary of Defense supporting the interoperability pillar of the DoD Unmanned Systems Integrated Roadmap. It is a credit card-sized enclosed unit that provides USB interfaces for plaintext and ciphertext, support for radio controls and management, and a software Application Programming Interface that together allow easy integration into tactical UxS communication systems. This paper gives an overview of the architecture, interfaces, usage, and development and approval schedule of the device.
READ LESS

Summary

Under the Navy's Flexible Cyber-Secure Radio (FlexCSR) program, the Naval Information Warfare Center Pacific and the Massachusetts Institute of Technology's Lincoln Laboratory are jointly developing a unique cybersecurity solution for tactical unmanned systems (UxS): the FlexCSR Security/Cyber Module (SCM) End Cryptographic Unit (ECU). To deal with possible loss of unmanned...

READ MORE
A compact end cryptographic unit for tactical unmanned systems

Supporting security sensitive tenants in a bare-metal cloud

July 10, 2019
  |
Conference Paper
Author:
Amin Mosayyebzadeh
…
Published in:
2019 USENIX Annual Technical Conf., 10-12 July 2019.
Topic:
cyber security
R&D area:
R&D group:

Summary

Bolted is a new architecture for bare-metal clouds that enables tenants to control tradeoffs between security, price, and performance. Security-sensitive tenants can minimize their trust in the public cloud provider and achieve similar levels of security and control that they can obtain in their own private data centers. At the same time, Bolted neither imposes overhead on tenants that are security insensitive nor compromises the flexibility or operational efficiency of the provider. Our prototype exploits a novel provisioning system and specialized firmware to enable elasticity similar to virtualized clouds. Experimentally we quantify the cost of different levels of security for a variety of workloads and demonstrate the value of giving control to the tenant.
READ LESS

Summary

Bolted is a new architecture for bare-metal clouds that enables tenants to control tradeoffs between security, price, and performance. Security-sensitive tenants can minimize their trust in the public cloud provider and achieve similar levels of security and control that they can obtain in their own private data centers. At the...

READ MORE
Supporting security sensitive tenants in a bare-metal cloud

Control-flow integrity for real-time embedded systems

July 9, 2019
  |
Conference Paper
Author:
Robert J. Walls
…
Published in:
31st Euromicro Conf. on Real-Time Systems, ECRTS, 9-12 July 2019.
Topic:
embedded computing
R&D area:
R&D group:

Summary

Attacks on real-time embedded systems can endanger lives and critical infrastructure. Despite this, techniques for securing embedded systems software have not been widely studied. Many existing security techniques for general-purpose computers rely on assumptions that do not hold in the embedded case. This paper focuses on one such technique, control-flow integrity (CFI), that has been vetted as an effective countermeasure against control-flow hijacking attacks on general-purpose computing systems. Without the process isolation and fine-grained memory protections provided by a general-purpose computer with a rich operating system, CFI cannot provide any security guarantees. This work proposes RECFISH, a system for providing CFI guarantees on ARM Cortex-R devices running minimal real-time operating systems. We provide techniques for protecting runtime structures, isolating processes, and instrumenting compiled ARM binaries with CFI protection. We empirically evaluate RECFISH and its performance implications for real-time systems. Our results suggest RECFISH can be directly applied to binaries without compromising real-time performance; in a test of over six million realistic task systems running FreeRTOS, 85% were still schedulable after adding RECFISH.
READ LESS

Summary

Attacks on real-time embedded systems can endanger lives and critical infrastructure. Despite this, techniques for securing embedded systems software have not been widely studied. Many existing security techniques for general-purpose computers rely on assumptions that do not hold in the embedded case. This paper focuses on one such technique, control-flow...

READ MORE
Control-flow integrity for real-time embedded systems

New software helps users build resilient, cost-effective energy architectures

July 2, 2019
  |
Journal Article
Author:
Madelaine H. Millar
Published in:
Lincoln Laboratory News
Topic:
energy
R&D area:
R&D group:

Summary

The Energy Resilience Analysis tool lets mission owners and energy managers balance the needs of critical missions on military installations with affordability when they design energy resilience solutions.
READ LESS

Summary

The Energy Resilience Analysis tool lets mission owners and energy managers balance the needs of critical missions on military installations with affordability when they design energy resilience solutions.

READ MORE
New software helps users build resilient, cost-effective energy architectures

A Framework for Evaluating Electric Power Grid Improvements in Puerto Rico(2.58 MB)

July 1, 2019
  |
Project Report
Author:
Marija Ilic
…
Topic:
humanitarian assistance
R&D area:
R&D group:

Summary

This report is motivated by the recognition that serving highly distributed electric power load in Puerto Rico during extreme events requires innovative methods. To do this, we must determine the type and locations of the most critical equipment, innovative methods, and software for operating the electrical system most effectively. It is well recognized that the existing system needs to be both hardened and further enhanced by deploying Distributed Energy Resources (DERs), solar photovoltaics (PV) in particular, and local reconfigurable microgrids to manage these newly deployed DERs. While deployment of microgrids and DERs has been advocated by many, there is little fundamental understanding how to operate Puerto Rico’s electrical system in a way that effectively uses DERs during both normal operations and grid failures. Utility companies’ traditional reliability requirements and operational risk management practices rely on excessive amounts of centralized reserve generation to anticipate failures, which increases the cost of normal operations and nullifies the potential of DERs to meet loads during grid failures. At present, no electric power utility has a ready-to-use framework that overcomes these limitations. This report seeks to fill this void.
READ LESS

Summary

This report is motivated by the recognition that serving highly distributed electric power load in Puerto Rico during extreme events requires innovative methods. To do this, we must determine the type and locations of the most critical equipment, innovative methods, and software for operating the electrical system most effectively. It...

READ MORE
A Framework for Evaluating Electric Power Grid Improvements in Puerto Rico

A framework for evaluating electric power grid improvements in Puerto Rico

July 1, 2019
  |
Project Report
Author:
Marija Ilic
…
Published in:
MIT Lincoln Laboratory Report 127164
Topic:
energy
R&D area:
R&D group:

Summary

This report is motivated by the recognition that serving highly distributed electric power load in Puerto Rico during extreme events requires innovative methods. To do this, we must determine the type and locations of the most critical equipment, innovative methods, and software for operating the electrical system most effectively. It is well recognized that the existing system needs to be both hardened and further enhanced by deploying Distributed Energy Resources (DERs), solar photovoltaics (PV) in particular, and local reconfigurable microgrids to manage these newly deployed DERs. While deployment of microgrids and DERs has been advocated by many, there is little fundamental understanding how to operate Puerto Rico's electrical system in a way that effectively uses DERs during both normal operations and grid failures. Utility companies' traditional reliability requirements and operational risk management practices rely on excessive amounts of centralized reserve generation to anticipate failures, which increases the cost of normal operations and nullifies the potential of DERs to meet loads during grid failures. At present, no electric power utility has a ready-to-use framework that overcomes these limitations. This report seeks to fill this void.
READ LESS

Summary

This report is motivated by the recognition that serving highly distributed electric power load in Puerto Rico during extreme events requires innovative methods. To do this, we must determine the type and locations of the most critical equipment, innovative methods, and software for operating the electrical system most effectively. It...

READ MORE
A framework for evaluating electric power grid improvements in Puerto Rico

Feature forwarding for efficient single image dehazing

June 17, 2019
  |
Conference Paper
Author:
Peter M. Morales
…
Published in:
IEEE/CVF Conf. on Computer Vision and Pattern Recognition Workshops, CVPRW, 16-17 June 2019.
Topic:
image processing
R&D area:
R&D group:

Summary

Haze degrades content and obscures information of images, which can negatively impact vision-based decision-making in real-time systems. In this paper, we propose an efficient fully convolutional neural network (CNN) image dehazing method designed to run on edge graphical processing units (GPUs). We utilize three variants of our architecture to explore the dependency of dehazed image quality on parameter count and model design. The first two variants presented, a small and big version, make use of a single efficient encoder–decoder convolutional feature extractor. The final variant utilizes a pair of encoder-decoders for atmospheric light and transmission map estimation. Each variant ends with an image refinement pyramid pooling network to form the final dehazed image. For the big variant of the single-encoder network, we demonstrate state-of-the-art performance on the NYU Depth dataset. For the small variant, we maintain competitive performance on the superresolution O/I-HAZE datasets without the need for image cropping. Finally, we examine some challenges presented by the Dense-Haze dataset when leveraging CNN architectures for dehazing of dense haze imagery and examine the impact of loss function selection on image quality. Benchmarks are included to show the feasibility of introducing this approach into real-time systems.
READ LESS

Summary

Haze degrades content and obscures information of images, which can negatively impact vision-based decision-making in real-time systems. In this paper, we propose an efficient fully convolutional neural network (CNN) image dehazing method designed to run on edge graphical processing units (GPUs). We utilize three variants of our architecture to explore...

READ MORE
Feature forwarding for efficient single image dehazing

Collaborative and passive channel gain estimation in fading environments

June 12, 2019
  |
Journal Article
Author:
Binoy G. Kurien
Published in:
IEEE Trans. Cognitive Commun. and Netw., Vol. 5, No. 4, December 2019, pp. 863-72.
Topic:
communications
R&D area:
R&D group:

Summary

Dynamic spectrum access techniques are typically aided by knowledge of the wireless channel gains among participating radios, as this knowledge allows the potential interference impact of any radio's transmissions on its neighbors to be quantified. We present a technique for collaborative inference of the channel gains which relies solely on the radios monitoring their aggregate transmitted and received energies as they transmit their data packets. We demonstrate that through low data-rate exchange of these energy metrics among bursty networks, the gains can be jointly estimated within a dB and with low latency on the order of seconds. In particular, we derive the best linear unbiased estimator (BLUE) for the gains. While this estimator relies on knowledge of fading parameters not known in practice, we propose a practical variant which achieves performance comparable to the BLUE in the realistic fading setting used in our simulations.
READ LESS

Summary

Dynamic spectrum access techniques are typically aided by knowledge of the wireless channel gains among participating radios, as this knowledge allows the potential interference impact of any radio's transmissions on its neighbors to be quantified. We present a technique for collaborative inference of the channel gains which relies solely on...

READ MORE
Collaborative and passive channel gain estimation in fading environments

Discriminative PLDA for speaker verification with X-vectors

May 12, 2019
  |
Conference Paper
Author:
Bengt J. Borgstrom
Published in:
International Conference on Acoustics, Speech, and Signal Processing, May 2019 [submitted]
Topic:
speaker recognition
R&D area:
R&D group:

Summary

This paper proposes a novel approach to discriminative training ofprobabilistic linear discriminant analysis (PLDA) for speaker veri-fication with x-vectors. The Newton Method is used to discrimi-natively train the PLDA model by minimizing the log loss of ver-ification trials. By diagonalizing the across-class and within-classcovariance matrices as a pre-processing step, the PLDA model canbe trained without relying on approximations, and while maintain-ing important properties of the underlying covariance matrices. Thetraining procedure is extended to allow for efficient domain adapta-tion. When applied to the Speakers in the Wild and SRE16 tasks, theproposed approach provides significant performance improvementsrelative to conventional PLDA.
READ LESS

Summary

This paper proposes a novel approach to discriminative training ofprobabilistic linear discriminant analysis (PLDA) for speaker veri-fication with x-vectors. The Newton Method is used to discrimi-natively train the PLDA model by minimizing the log loss of ver-ification trials. By diagonalizing the across-class and within-classcovariance matrices as a pre-processing step, the...

READ MORE
Discriminative PLDA for speaker verification with X-vectors

AI enabling technologies: a survey

May 8, 2019
  |
Journal Article
Author:
Vijay N. Gadepally
…
Published in:
https://arxiv.org/abs/1905.03592
Topic:
artificial intelligence
R&D area:
R&D group:

Summary

Artificial Intelligence (AI) has the opportunity to revolutionize the way the United States Department of Defense (DoD) and Intelligence Community (IC) address the challenges of evolving threats, data deluge, and rapid courses of action. Developing an end-to-end artificial intelligence system involves parallel development of different pieces that must work together in order to provide capabilities that can be used by decision makers, warfighters and analysts. These pieces include data collection, data conditioning, algorithms, computing, robust artificial intelligence, and human-machine teaming. While much of the popular press today surrounds advances in algorithms and computing, most modern AI systems leverage advances across numerous different fields. Further, while certain components may not be as visible to end-users as others, our experience has shown that each of these interrelated components play a major role in the success or failure of an AI system. This article is meant to highlight many of these technologies that are involved in an end-to-end AI system. The goal of this article is to provide readers with an overview of terminology, technical details and recent highlights from academia, industry and government. Where possible, we indicate relevant resources that can be used for further reading and understanding.
READ LESS

Summary

Artificial Intelligence (AI) has the opportunity to revolutionize the way the United States Department of Defense (DoD) and Intelligence Community (IC) address the challenges of evolving threats, data deluge, and rapid courses of action. Developing an end-to-end artificial intelligence system involves parallel development of different pieces that must work together...

READ MORE
AI enabling technologies: a survey
241-250 of 2301