Laboratory for Telecommunication Sciences at College Park

College Park, MD, United States

Laboratory for Telecommunication Sciences at College Park

College Park, MD, United States

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Dykstra J.A.B.S.,Laboratory for Telecommunication Sciences at College Park | Orr S.R.,U.S. Naval Academy
2016 IEEE International Conference on Cyber Conflict, CyCon U.S. 2016 | Year: 2016

Researchers have shown that human decision making in complex environments like cyber is a significant risk factor. Unfortunately, much work on cyber situational awareness has been technology-focused, despite the ultimate importance of human decisions, especially in crisis situations like real-time cyber-attacks and data breaches. Cybersecurity practitioners and leaders require an appropriate framework to help decision makers at all levels guide and act while managing risk in unexpected and dynamic situations. Without such a framework, failure to enlighten the unknown leads to heightened risk, uncertainty, and insecurity. The ability to establish context, adapt, and apply the most appropriate decision-making style to unique situations increases the likelihood of security. We offer an application of the Cynefin Framework, a sensemaking solution, to cybersecurity which allows practitioners and leaders to identify the context and appropriate response type in complex situations using the cause-and-effect relationship. We also illustrate how orienting oneself in the five Cynefin domains - disorder, obvious, complicated, complex, and chaotic - can help manage risk. By comparing Cynefin to other decision-making frameworks, we show how this framework is uniquely appropriate for acting through complexity and risk in cyber. © 2016 IEEE.


Georgakopoulos A.,WINGS Inc | Margaris A.,WINGS Inc | Tsagkaris K.,WINGS Inc | Demestichas P.,University of Piraeus | Demestichas P.,Laboratory for Telecommunication Sciences at College Park
IEEE Vehicular Technology Magazine | Year: 2016

Wireless networks have made huge progress over the past three decades. Nevertheless, emerging fifth-generation (5G) networks are under pressure to continue in this direction at an even more rapid pace, at least for the next ten to 20 years. This pressure is exercised by rigid requirements as well as emerging technology trends that are aimed at introducing improvements to the 5G wireless world. © 2016 IEEE.


Punnoose R.,Proteus Technologies | Crainiceanu A.,U.S. Naval Academy | Rapp D.,Laboratory for Telecommunication Sciences at College Park
ACM International Conference Proceeding Series | Year: 2012

Resource Description Framework (RDF) was designed with the initial goal of developing metadata for the Internet. While the Internet is a conglomeration of many interconnected networks and computers, most of today's best RDF storage solutions are confined to a single node. Working on a single node has significant scalability issues, especially considering the magnitude of modern day data. In this paper we introduce a scalable RDF data management system that uses Accumulo, a Google Bigtable variant. We introduce storage methods, indexing schemes, and query processing techniques that scale to billions of triples across multiple nodes, while providing fast and easy access to the data through conventional query mechanisms such as SPARQL. Our performance evaluation shows that in most cases, our system outperforms existing distributed RDF solutions, even systems much more complex than ours. Copyright 2012 ACM.


Uher J.,Johns Hopkins University | Harper J.,Johns Hopkins University | Mennecke R.G.,Johns Hopkins University | Patton P.,Johns Hopkins University | Farroha B.,Laboratory for Telecommunication Sciences at College Park
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2016

The emerging 5th generation wireless network will be architected and specified to meet the vision of allowing the billions of devices and millions of human users to share spectrum to communicate and deliver services. The expansion of wireless networks from its current role to serve these diverse communities of interest introduces new paradigms that require multi-tiered approaches. The introduction of inherently low security components, like IoT devices, necessitates that critical data be better secured to protect the networks and users. Moreover high-speed communications that are meant to enable the autonomous vehicles require ultra reliable and low latency paths. This research explores security within the proposed new architectures and the cross interconnection of the highly protected assets with low cost/low security components forming the overarching 5th generation wireless infrastructure. © 2016 SPIE.


Chimiak W.J.,Laboratory for Telecommunication Sciences at College Park | Patton S.T.,Laboratory for Telecommunication Sciences at College Park | Janansky S.,University of Delaware
Computer | Year: 2014

Enhanced IP (EnIP) offers a solution to the problem of IPv4 address depletion without replacing IPv4, as IPv6 does, but by building on top of IPv4, maximizing backward compatibility. An experimental EnIP deployment between nodes at the University of Maryland and the University of Delaware, requiring neither software modification nor modification of in-path routers, demonstrates EnIP's potential. © 2014 IEEE.


Chang N.B.,Applied Communication science | Liberti J.C.,Applied Communication science | Gross M.,Laboratory for Telecommunication Sciences at College Park
Conference Record - Asilomar Conference on Signals, Systems and Computers | Year: 2015

Distributed source coding techniques enable distributed receivers to independently compress samples to a rate above the Slepian-Wolf bound, by leveraging statistical correlations between different receivers observations. The wireless channel can impose many compression challenges, such as unknown or dynamic compression bounds due to time-varying fading and mobility. This work derives a novel rate adaptive non-binary distributed source coding scheme which is motivated by these challenges. Applications are derived for distributed detection and distributed multiple-input multiple-output (MIMO) reception. Results demonstrate strong performance with these applications along with near-bound compression at various SNR levels and channel realizations. © 2015 IEEE.


Ferguson M.P.,Cray | Buettner D.,Laboratory for Telecommunication Sciences at College Park
Proceedings - 2015 9th International Conference on Partitioned Global Address Space Programming Models, PGAS 2015 | Year: 2015

We investigated a software cache for PGAS PUT and GET operations. The cache is implemented as a software write-back cache with dirty bits, local memory consistency operations, and programmer-guided prefetch. This cache supports programmer productivity while enabling communication aggregation and overlap. We evaluated an implementation of this cache for remote data within the Chapel programming language. The cache provides a 2x speedup for several distributed memory application benchmarks written in Chapel across a variety of network configurations. In addition, we observed that improvements to compiler optimization did not remove the benefit of the cache. © 2015 IEEE.


Keller C.M.,Lincoln Laboratory | Whipple G.H.,Laboratory for Telecommunication Sciences at College Park
Conference Record - Asilomar Conference on Signals, Systems and Computers | Year: 2015

Information theoretic upper bounds on the number of distinguishable classes enable assessments of feasibility when applying classification techniques [1][2]. A goal of this paper is to examine the behavior of these upper bounds as the items being classified become more complex in the sense that the number of degrees of freedom increases. We synthesize filters with different numbers of stages to represent items with various levels of complexity. Using a typical distribution for component tolerances, we study whether different instantiations of filters with greater numbers of components (stages) are more distinguishable than filters with fewer components. We examine the behavior of the Fano upper bound for the number of distinguishable classes as a function of signal-to-noise ratio (SNR), to make the comparisons. © 2014 IEEE.


Mailloux L.O.,U.S. Air force | Grimaila M.R.,U.S. Air force | Colombi J.M.,U.S. Air force | Hodson D.D.,U.S. Air force | And 3 more authors.
IEEE Communications Magazine | Year: 2015

Quantum key distribution (QKD) is an innovative technology that exploits the laws of quantum mechanics to generate and distribute a shared cryptographic key for secure communications. The unique nature of QKD ensures that eavesdropping on quantum communications necessarily introduces detectable errors which is desirable for high-security environments. QKD systems have been demonstrated in both freespace and optical fiber configurations, gaining global interest from national laboratories, commercial entities, and the U.S. Department of Defense. However, QKD is a nascent technology where realized systems are constructed from non-ideal components, which can significantly impact system performance and security. In this article, we describe QKD technology as part of a secure communications solution and identify vulnerabilities associated with practical network architectures. In particular, we examine the performance of decoy state enabled QKD systems against a modeled photon number splitting attack and suggest an improvement to the decoy state protocol security condition that does not assume a priori knowledge of the QKD channel efficiency. © 2015 IEEE.


Crainiceanu A.,U.S. Naval Academy | Rapp D.,Laboratory for Telecommunication Sciences at College Park
Information Systems | Year: 2015

SPARQL is the standard query language for Resource Description Framework (RDF) data. RDF was designed with the initial goal of developing metadata for the Internet. While the number and the size of the generated RDF datasets are continually increasing, most of today's best RDF storage solutions are confined to a single node. Working on a single node has significant scalability issues, especially considering the magnitude of modern day data. In this paper we introduce Rya, a scalable RDF data management system that efficiently supports SPARQL queries. We introduce storage methods, indexing schemes, and query processing techniques that scale to billions of triples across multiple nodes, while providing fast and easy access to the data through conventional query mechanisms such as SPARQL. Our performance evaluation shows that in most cases, our system outperforms existing distributed RDF solutions, even systems much more complex than ours. © 2015, Elsevier Ltd. All rights reserved.

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