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Abstracts of HSHQDC-16-R-00012 Phase I Awards
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H-SB016.1-001

Company

BALFOUR Technologies LLC
510 Grumman Road West
Suite 212
Bethpage, NY 11714-3631

Proposal Information HSHQDC-16-R-00012-H-SB016.1-001-0007-I - A Secure, Mobile Machine-to-Machine (M2M) Internet-of-Things (IoT) Video/Audio Interoperability Device (VAID)
Topic Information H-SB016.1-001 - Security Systems Video/Audio Interoperability Device
Award/Contract Number HSHQDC-16-C-00049
Abstract

In an emergency or special event, First Responders need to leverage existing/available video and audio feeds from surveillance systems already deployed at the site. This audio/video connectivity must be achieved rapidly and easily as first responders arrive, and should also include access to valuable mobile/wireless audio/video feeds that become available during the emergency/event. Balfour Technologies proposes to develop a video/audio interoperable device (VAID) that first responders can deploy on-site that will: (A) strongly authenticate users and connect to commonly deployed/existing surveillance camera systems; (B) discover and stream live and archived audio/video from existing surveillance cameras; (C) securely broadcast this audio/video in realtime to first responders and emergency managers on-site or in remote/mobile command centers; (D) provide an easy-to-use user interface to configure, manage, control, record, and view these camera streams in a common operating environment (where additional features such as geo-location, automated video analytics, etc. could be applied); and (E) dynamically connect to and capture live mobile/wireless audio/video (i.e. from smartphones) that becomes available during the event. With Balfour's extensive past experience integrating many diverse surveillance systems over the past decade, this VAID innovation will be able to be rapidly implemented incrementally and initially deployed within months. Commercially, every federal/local/state first responder group (fire, police, security) should have a VAID system to quickly acquire interior surveillance video/audio feeds during fires, active shooters, etc. emergency situations. And security groups for every large/multi-campus organizations with a mix of surveillance systems at various locations/buildings can benefit from utilizing VAID systems.

Company

MCQ INC.
1551 Forbes St.
Fredericksburg, VA 22405-1603

Proposal Information HSHQDC-16-R-00012-H-SB016.1-001-0013-I - Security Systems Video/Audio Interoperability Device
Topic Information H-SB016.1-001 - Security Systems Video/Audio Interoperability Device
Award/Contract Number HSHQDC-16-C-00050
Abstract

Through this SBIR, a system will be developed to enable authorized users to access video and audio from existing surveillance systems, and rebroadcast the video/audio signals for use by authorized users such as first responders. McQ will leverage its extensive camera interface, video compression, cryptography, and product development experience to both perform the appropriate tradeoffs in designing the system and to successfully build and test a prototype system. Interoperability is a critical feature of the system to allow the system to operate on a variety of closed circuit and networked camera systems; each with different physical interfaces, communication standards, and architectures. McQ's plug-and-play camera interface experience developed through developing its vWatch product, and its extensive networking and communications experience based on over a decade of developing video streaming products, will be efficiently utilized. During Phase I, a detailed analysis will be performed to provide a camera interface standard which encompasses a large variety of existing surveillance camera products; and a complete system design will be developed. During Phase II, a prototype system will be assembled and tested.

Company

Systems Engineering, Inc.
21351 Gentry Drive
Suite 100
Dulles, VA 20166-6510

Proposal Information HSHQDC-16-R-00012-H-SB016.1-001-0015-I - Security Systems Video/Audio Interoperability Device
Topic Information H-SB016.1-001 - Security Systems Video/Audio Interoperability Device
Award/Contract Number HSHQDC-16-C-00051
Abstract

First responders are challenged by the lack of real-time information from surrounding video/audio sources when arriving at an incident and a forced to rely of information that is outdated or incorrect from secondary sources. In today's technological society, there is a plethora of video cameras; in homes, businesses, law enforcement and public areas that difficult to access. To gain access to this information requires level of technical expertise not readily available to first responders. The issues arise with disparate systems employing different standards, equipment types and quantities. The response details the research required in Phase I to design a self-contained device that will capture video and audio from closed-circuit television and networked video security systems commonly implemented by both public and private entities. The concept will address how to access the video and audio feeds with the approval of the system owners, and rebroadcast the data to first responders and incident command centers for improved situational awareness. and enhanced personnel safety. The concept will enable plug and play access, through hard-wired or wireless capabilities to the widest array of existing video security systems for use during an emergency or response operation. To optimize the ability for first responders to readily access on scene information, the concept will consider characteristics of typical video and audio security systems installed in public and private buildings or used to monitor large outdoor areas.

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H-SB016.1-002

Company

Digital Bazaar, Inc.
203 Roanoke St W.
Blacksburg, VA 24060-7419

Proposal Information HSHQDC-16-R-00012-H-SB016.1-002-0026-I - Credentials on Public/Private Linked Ledgers
Topic Information H-SB016.1-002 - Applicability of Blockchain Technology to Privacy Respecting Identity Management
Award/Contract Number HSHQDC-16-C-00058
Abstract

A wide variety of applications could benefit from combining identity management technology with decentralized ledgers (aka blockchains). However, not every application uses the same data or requires the same consensus or authorization models. While a single solution is unlikely, we assert each application could benefit from a standard, configurable, decentralized ledger with flexible semantics. We will study the feasibility of this concept by building a proof-of-concept Linked Data ledger format and architecture. We intend to configure this architecture to demonstrate how to publish credentials (aka verifiable attributes) to address specific DHS use cases and to commercialize the created technology. The proposed architecture would enable ledgers to provide independently, cryptographically verifiable credentials with flexible semantics. This approach decouples issuing and verification services, reducing infrastructure requirements and costs for issuers. It also increases a ledger's utility and number of participants, resulting in cost sharing and increased incentives to provide the high availability now only required by the verification process. For example, fire and rescue organizations could publish credentials about personnel to a highly available public ledger. First responders could then be authenticated to gain access to protected sites or resources by demonstrating ownership over these credentials via their mobile device. Even if the credential issuers had experienced complete system failure, the verification process would be unaffected. This approach encourages shared infrastructure costs, highly available verification systems, and new forms of authentication and authorization for numerous applications, including those that would benefit the DHS.

Company

Evernym Inc.
12233 Corliss Ave N.
Seattle, WA 98133-8538

Proposal Information HSHQDC-16-R-00012-H-SB016.1-002-0029-I - Applying Blockchain to Decentralized Identity
Topic Information H-SB016.1-002 - Applicability of Blockchain Technology to Privacy Respecting Identity Management
Award/Contract Number HSHQDC-16-C-00061
Abstract

The purpose of this SBIR Proposal is to conduct the basic research that will result in a specific method by which blockchain technology can provide a decentralized foundation for privacy-respecting identity management infrastructure. Respect Network will research and develop a decentralized registry and discovery service for Decentralized Identifiers (DIDs) to integrate with the public blockchain. DIDs will allow principals to directly control their own identities with cryptographic proofs and secure, addressable network endpoints. DIDs will enable a Decentralized Identity Management (DIDM) infrastructure that will empower people and organizations to securely and confidentially manage and assert their identities. Open standards and established industry protocols will permit principals to selectively disclose identity claims, and to manage their privacy and digital relationships. Respect Network's thesis is that the combination of DIDs and DIDM architecture, using public and/or private blockchains as "identity backbones", can meet traditional information security principles of confidentiality, integrity, availability, non-repudiation and provenance. Further, our approach applies privacy-by-design principles, including user control, selective disclosure of information and pseudonymity. This proposal presents the basic research challenges that need to be accomplished to harness the science and technology of DIDs, and to integrate DIDs into DIDM infrastructure that serves both individuals and enterprises. Our proposed effort and deliverables will present and answer critical questions related to security and privacy. Results of our research will enable the development and demonstration of prototypes in future R&D phases for Homeland Security Enterprise applications, and for commercial products.

Company

Narf Industries LLC
2425 Perry St NE
Washington, DC 20018-3130

Proposal Information HSHQDC-16-R-00012-H-SB016.1-002-0030-I - FEUDAL
Topic Information H-SB016.1-002 - Applicability of Blockchain Technology to Privacy Respecting Identity Management
Award/Contract Number HSHQDC-16-C-00053
Abstract

Existing blockchain implementations do not include features required for an effective, decentralized and scalable identity management solution. Although current public (permissionless) blockchains provide rigorous, self-incentivizing primitives to ensure the integrity, availability, and non-repudiation of events, they often intentionally eschew confidentiality features as anathema to the consensus goals of traditional proofs of work. Fortunately, we believe that distributed autonomous contracts or organizations (DAOs), as seen in the Ethereum ecosystem, provide opportunity to enable confidentiality and selective disclosure primitives without compromises to core blockchain protocol or incentive structures. Our research, FEUDAL, seeks to answer questions and overcome obstacles necessary to achieve everything required for tomorrows identity management solution built on a permissionless blockchain: confidentiality (with selective information disclosure), integrity, availability, non-repudiation, provenance and pseudo-anonymity. FEUDAL will define and implement Federated Identity 2.0: permissioned authentication and authorization built on a permissionless, public blockchain. Our Federated Identity 2.0 concept garners benefits of the blockchain infrastructure (availability, integrity), adds additional features (confidentiality,permissioned attribute authorship, administrative delegation) while remaining interoperable with industry-standard data exchange formats such as SAML and LDAP. FEUDAL will provide a clear path toward better identity management while remaining backwards compatible with traditional federated schemes. The applications for such a DAO-based technology are far-reaching in both Government and Industry. Commercial applications include, but are not limited to: scalable single sign on between federated entities, tracking credit worthiness via selective disclosure of attributes to approved creditors, and information escrow governed by autonomous contracts.

Company

Celerity Government Solutions, LLC
8405 Greensboro Drive, Suite 930
McLean, VA 22102-5110

Proposal Information HSHQDC-16-R-00012-H-SB016.1-002-0034-I - Xcelerate Solutions Response to H-SB016.1-002
Topic Information H-SB016.1-002 - Applicability of Blockchain Technology to Privacy Respecting Identity Management
Award/Contract Number HSHQDC-16-C-00059
Abstract

Xcelerate proposes a project team of identity, security, privacy, and blockchain subject matter experts (SME) to perform research that determines the feasibility of a blockchain solution enabling users to establish and maintain trusted identity transactions with public and private organizations. Our solution will enable users to develop an immutable identity transaction history, including verified identity information, to be used as inputs to determine trust confidence levels based on past transaction history. It will provide an authoritative source of participant consumer identity attributes that Service Providers could use for attribute verification. A solution that is easily integrated with other technologies and leverages the advantages of blockchain technology will be valuable to the identity ecosystem and address key problems for which there are currently no viable solutions. This phase will produce a set of requirements, informed by privacy and security assessments of existing public and private blockchains, to be used in the design and prototype of a blockchain solution to be developed in Phase II. Security and privacy-by-design will be key tenets throughout Phase I to ensure the solution meets the requirements for Federal Government identity services. This feasibility study will evaluate blockchain implementations that meet these requirements. New concepts and methods will be developed to assess and design the security and privacy of blockchain technologies. We will develop a technical prototype to demonstrate its privacy, security, and technical capabilities and will complete a commercialization strategy to operationalize the solution for DHS as a deliverable of Phase I.

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H-SB016.1-003

Company

BlueRISC, Inc.
28 Dana St
Amherst, MA 01002-0000

Proposal Information HSHQDC-16-R-00012-H-SB016.1-003-0004-I - Malware Prediction for Situational Understanding and Preemptive Cyber Defense
Topic Information H-SB016.1-003 - Malware Prediction for Situational Understanding and Preemptive Cyber Defense
Award/Contract Number HSHQDC-16-C-00065
Abstract

BlueRISC's proposed solution provides a fundamentally new approach to predicting the presence of malware in a network based on a novel graph-theoretical framework. Unlike traditional approaches that are reactive, it builds on a predictive capability that is flexible, adaptive, and is not relying on signatures or strict rule based malware definitions. The approach captures system motion as a predictive surrogate for malicious activity. This occurs based a concise graph-based forensics representation of a systems state and associated space-time correlations algorithms which use graph theory.

Company

GrammaTech, Inc.
531 Esty Street
Ithaca, NY 14850-4201

Proposal Information HSHQDC-16-R-00012-H-SB016.1-003-0006-I - Malware Prediction
Topic Information H-SB016.1-003 - Malware Prediction for Situational Understanding and Preemptive Cyber Defense
Award/Contract Number HSHQDC-16-C-00071
Abstract

GrammaTech will create the CodeSurfer/INSIGHT tool to address the problem of understanding the evolution of malware characteristics and anticipating future malware evolution. INSIGHT will build on these capabilities: (a) GrammaTech's binary analysis tools as enhanced during the DARPA RAPID project, extending it with more sophisticated component identification, type inference, representations of software structure, and improved similarity detection in malware and obfuscated code; (b) GrammaTech's ongoing contributions to the DARPA MUSE project, using its features, similarity and search algorithms, and high-capacity database for storing and retrieving information about malware, extended with new features based on INSIGHT's improvements in binary analysis; (c) GrammaTech's experience in MUSE with feature extraction and pattern recognition specifically applied to code structure of binaries; and (d) the open source repositories of malware and the data and insights produced in the DARPA CyberGenome project. The result will be a tool that automatically extracts characteristics and aggregate features of a collection of malware, identifying malware families, trends, cross-fertilization, and evolutionary directions. These will provide a human analyst insight into the evolution and relationships within a corpus of binary executables, malware in particular. Both government and commercial clients will use the tool to help anticipate threats to their organizations and infrastructure. Non-malware applications include identifying code borrowing for license tracking, detecting instances of insider threat, and determining differences among different versions of software.

Company

Red Balloon Security
336 West 37th Street Suite 1024
New York, NY 10018-4592

Proposal Information HSHQDC-16-R-00012-H-SB016.1-003-0020-I - Hybrid Prediction for Embedded Malware
Topic Information H-SB016.1-003 - Malware Prediction for Situational Understanding and Preemptive Cyber Defense
Award/Contract Number HSHQDC-16-C-00072
Abstract

Predicting malware trends and designing defenses to defeat the next generation of malware is difficult but necessary in order to significantly increase the cost to attackers of developing malware and executing successful attacks. Without such malware trend predictions, we will continually be defending against yesterday's attacks and will remain unprepared for new threats. Embedded devices are becoming the next target for attackers as traditional workstations and servers become more secure. We will create a hybrid approach toward embedded device malware trend prediction. Our approach targets both long-term malware trend prediction utilizing attack graphs and short-term approaches monitoring malware and capturing forensic data to provide real-time predictions. A hybrid of short-term and long-term approaches offers many benefits. Captured samples would confirm or better inform the long-term predictions of what evasions and attack paths malware uses. Long-term predictions would enable advanced defenses to be prepared to capture malware samples. Our hybridized predictive malware trending scheme will significantly increase situational awareness into both short-term and long-term attack trends. Furthermore, our output will enhance embedded attack incidence response capabilities at an enterprise level and predict future attack trends at both tactical and strategic time scales.

Company

ZeroPoint Dynamics, LLC
130 Hamilton Hedge Pl
Cary, NC 27519-9144

Proposal Information HSHQDC-16-R-00012-H-SB016.1-003-0021-I - InnerAwareness: Preemptive Cyber Defense and Situational Understanding Through MemoryOriented Cyber Genomics and Physiology
Topic Information H-SB016.1-003 - Malware Prediction for Situational Understanding and Preemptive Cyber Defense
Award/Contract Number HSHQDC-16-C-00073
Abstract

Motivated by a real operational need to tackle threats posed by the onslaught of constantly evolving exploits and malware, this proposal describes techniques for dynamically analyzing malicious documents and malware that addresses weaknesses in the status quo by (i) focusing on memory-oriented artifacts without the use of traditional sandbox hooks, while at the same time (ii) providing operators with enhanced situational understanding and preemptive malware and exploit defenses. Specifically, we will explore the design and implementation of novel memory-oriented techniques for conducting automated analysis of malware binaries, malicious documents and exploits (i.e. so called cyber-physiology techniques) to not only assist analysts in understanding the their function and intent, but also produce a novel set of outputs (i.e. artifacts, behaviors, code constructs) that, combined, concisely represent human understandable malware and exploit fingerprints. Second, we will design and implement so called cyber-genomics techniques for both individually using and collating a multitude of these malware and exploit fingerprints over time to not only aid in determining their identity, lineage, and provenance, but also identify trends in fingerprint components to pinpoint key distinguishing characteristics of malware and exploits in future waves of attack.

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H-SB016.1-004

Company

Robotic Research, LLC
555 Quince Orchard Road, Suite 300
Gaithersburg, MD 20878-1453

Proposal Information HSHQDC-16-R-00012-H-SB016.1-004-0002-I - ANTARES
Topic Information H-SB016.1-004 - Autonomous Indoor Navigation and Tracking of First Responders
Award/Contract Number HSHQDC-16-C-00068
Abstract

For the past 10 years, Robotic Research, LLC has worked with the Special Forces community to meet these requirements, and to deploy the resulting systems: WarLoc and Mole. The US government has invested in excess of $10 million to develop such capabilities. Over the years, Robotic Research has also leveraged this technology to match the different mission needs of the Army (e.g. the 2nd Infantry Division in South Korea), DHS Customs and Border Protection/Immigration and Customs Enforcement (Nogales group), and the Department of Energy. In this proposal, we will make the case that the core technology developed for these elite customers can be leveraged to provide similar levels of functionality in a package, form factor, and interface that is well-suited for the missions and op-tempo of the first responder community. It is our goal to maintain compatibility with WarLoc and Mole so that interoperability between first responder groups and DoD, DoE, and CBP/ICE can be maintained, and possibly enhanced. We call this technology ANTARES (Autonomous Navigation and Tracking of first RESponders).

Company

Oceanit Laboratories, Inc.
828 Fort Street Mall #600
Honolulu, HI 96813-4314

Proposal Information HSHQDC-16-R-00012-H-SB016.1-004-0018-I - FIND (First responder INdoor Determination)
Topic Information H-SB016.1-004 - Autonomous Indoor Navigation and Tracking of First Responders
Award/Contract Number HSHQDC-16-C-00067
Abstract

Oceanit proposes to develop a wearable capability for autonomous indoor navigation and tracking of first responders indoors in various types of building structures.

Company

Integrated Solutions For Systems
4970 Corporate Drive
Suite 100
Huntsville, AL 35805-6230

Proposal Information HSHQDC-16-R-00012-H-SB016.1-004-0022-I - Autonomous Indoor Navigation and Tracking of First Responders
Topic Information H-SB016.1-004 - Autonomous Indoor Navigation and Tracking of First Responders
Award/Contract Number HSHQDC-16-C-00055
Abstract

Integrated Solutions for Systems, Inc. (IS4S), a leader in advanced PNT technology, proposes to develop a personal First Responder navigation and tracking system for use in GPS-limited or denied environments. The system will Track First Responder motion with inertial-based pedometry combined with visual odometry Have a modular and scalable architecture to incorporate, but not rely on, other aiding sensors or information specific to the response environment (e.g. RF localization systems, maps, etc.) Incorporate standards to maximize operability with other connected systems and tools Send PNT solutions to the NGFR communication hub for transmission over available communication links, such as Land Mobile Radio (LMR) or Long-Term Evolution (LTE) networks Require minimal to no interaction from the First Responder to operate.

Company

Human Systems Integration, Inc.
153 Washington St
4th Floor
Walpole, MA 02032-1163

Proposal Information HSHQDC-16-R-00012-H-SB016.1-004-0024-I - An Indoor Navigation, Tracking and Situational Awareness Platform for the First Responder
Topic Information H-SB016.1-004 - Autonomous Indoor Navigation and Tracking of First Responders
Award/Contract Number HSHQDC-16-C-00056
Abstract

Human Systems Integration, Inc., a leading developer of Wearable Electronics products and solutions, will design and develop a Navigation and Situational Awareness system for the First Responder Environment (NavSAFE) that will enable persistent navigation and tracking of responders in indoor and GPS-denied environments. Our TacPAN system, provides the ideal platform for the integration of the multiple system components, including sensors, communication, and computing, which will be required to realize the desired indoor navigation and tracking capability. The system will be able to interface with multiple communications networks will implement a wearable electronics integration scheme in a form factor that maintains First Responder comfort and does not negatively impact his mission. NavSAFE will enable access for responders and commanders to both a priori and real-time situational awareness (SA) and will integrate all location and SA data into a single geo-referenced system. The system will securely network the responder to other responders, commanders and Incident Command Nodes. The system will provide location data for responders relative to each other and known and emerging threats and hazards.

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H-SB016.1-005

Company

Physical Optics Corporation
1845 West 205th Street
Torrance, CA 90501-1510

Proposal Information HSHQDC-16-R-00012-H-SB016.1-005-0018-I - Real-time Flood Forecasting and Reporting
Topic Information H-SB016.1-005 - Internet of Things (IoT) Low-Cost Flood Inundation Sensor
Award/Contract Number HSHQDC-16-C-00075
Abstract

To address the DHS need to rapidly predict, detect, and react to ever-changing flood conditions, Physical Optics Corporation (POC) proposes to develop a new Real-time Flood Forecasting and Reporting (RAFFAR) system based on a combination of commercial off-the-shelf (COTS) wireless networking technologies and existing proprietary POC sensors. The system will offer a means to deploy a scalable mesh network across a broad area that allows sensors to relay information through open data exchange standards to an operation center for monitoring of both flood conditions and heavy rain conditions that serve as predictors of floods. After collection, the information will be relayed to handheld devices through wireless emergency alerting. In Phase I POC will demonstrate the feasibility of RAFFAR by building and testing a preliminary prototype network and performing an analysis of a full-size network roll-out. Currently at Technology Readiness Level (TRL)-4, at the end of the resultant Phase I effort, the RAFFAR system will reach TRL-6. In Phase II, POC plans to manufacture sufficient sensors to deploy a 100+ unit network for outdoor testing. The successful completion of this project at the end of Phase III will benefit the nation in both government and commercial sectors by providing real-time disaster data so that first responders can react appropriately based on the best possible information. Commercial applications for this technology include applications in disaster prevention and recovery, manufacturing and equipment monitoring, and irrigation management.

Company

Progeny Systems Corporation
9500 Innovation Drive
Manassas, VA 20110-2210

Proposal Information HSHQDC-16-R-00012-H-SB016.1-005-0030-I - Internet of Things (IoT) Low-Cost Flood Inundation Sensor
Topic Information H-SB016.1-005 - Internet of Things (IoT) Low-Cost Flood Inundation Sensor
Award/Contract Number HSHQDC-16-C-00076
Abstract

Progeny Systems proposes to develop a deployable, low-cost flood inundation sensor for alerts, warnings and notifications to responders and citizens using IoT Wireless Emergency Alerts. The sensor will be ruggedized, modular, deployable, GPS-enabled, and submersible. The sensor will be part of a scalable wireless mesh sensor network. The sensor network will consist of an array of wireless sensor nodes that can measure ever-changing flood conditions and report them back to an operations center through a gateway node. The data from all the nodes in the network will be collected and analyzed at the operations center so as to rapidly predict, detect and react to inundation of low-lying areas, underpasses, and critical transportation corridors. This critical data will allow for federal, state and local governments to make real-time decisions pertaining to flood response.

Company

Evigia Systems, Inc.
3810 Varsity Drive
ANN ARBOR, MI 48108-2224

Proposal Information HSHQDC-16-R-00012-H-SB016.1-005-0038-I - Wide-Area Flood Alert Sensor Network
Topic Information H-SB016.1-005 - Internet of Things (IoT) Low-Cost Flood Inundation Sensor
Award/Contract Number HSHQDC-16-C-00074
Abstract

The proposed SBIR Phase I effort initiates the development of a highly-reliable, modular, and cost-effective wide-area flood sensor network system. Evigia leverages the EVX-1000 family of wireless mesh networked sensor system developed for remote rugged arctic oil-spill recovery operation to develop the proposed flood alert IoT system. The senor nodes operate on IEEE802.15.4 wireless physical layer, and an enhanced energy-efficient 6LoWPAN (IPv6 over Low power Wireless Personal Area Networks) open-standard mesh protocol. The proposed system addresses the present gap in cost-effectively monitoring and projecting water-levels and flooding, and generating early warnings in all terrains including urban and remote rugged areas.

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H-SB016.1-006

Company

ElanTech
9250 Bendix Road
Suite 1030
Columbia, MD 21045-1832

Proposal Information HSHQDC-16-R-00012-H-SB016.1-006-0009-I - EMS Data Analytics in Real-time (EMS DART)
Topic Information H-SB016.1-006 - Low-Cost, Real-Time Data Analytics for Underserved EMS Agencies
Award/Contract Number HSHQDC-16-C-00078
Abstract

The purpose of this research is to demonstrate the feasibility of developing an architecture design for a real-time monitoring, analysis, and notification solution for underserved EMS organizations at an affordable cost. Two efforts will be completed as part of the proposed research: 1) High performance EMS organizations of different sizes and constraints will be researched to identify a common set of key performance indicators (KPIs). 2) Database technologies and methods will be researched to determine the optimal approach to extracting information from a database with minimum knowledge of its structure and contents. The proposed research efforts will produce a common set of KPIs against which EMS organizations of different sizes and constraints can measure performance, and which can be used by DHS to develop guidance and best practices for operations management. The database research will produce a foundation for developing an automated database query method necessary to develop an analytics solution available to underserved EMS organizations at an affordable cost. Ambulance companies, community based and regional EMS organizations, 9-1-1 dispatch centers, and hospital based dispatch centers are all public safety organizations which would benefit from the proposed research. This market represents tens of thousands of organizations that would benefit from the proposed research. By identifying common high performing EMS KPIs and providing an affordable solution for underserved EMS organizations, the level of patient care will be elevated.

Company

Azavea Inc.
340 N 12th Street, Suite 402
Philadelphia, PA 19107-1102

Proposal Information HSHQDC-16-R-00012-H-SB016.1-006-0014-I - HunchLab for EMS: A Low-Cost, Multi-Screen Performance Management Solution for Underserved Agencies
Topic Information H-SB016.1-006 - Low-Cost, Real-Time Data Analytics for Underserved EMS Agencies
Award/Contract Number HSHQDC-16-C-00077
Abstract

The goal of this research is to explore the feasibility of providing a low-cost Software-as-a-Service (SaaS) solution to assist underserved Emergency Medical Services (EMS) agencies of all sizes to better analyze and improve operations through real-time data analysis. Delivering a data analysis suite tuned to key performance indicators of EMS agencies as an online, cloud subscription will result in a dramatically less expensive solution while remaining fiscally sustainable. The vision for this research is to provide several interface designs within one application to support differing use cases and accommodate a range of off-the-shelf hardware. In particular, it will support use on multiple devices with varying screen sizes to enable utility both in the office and in the field.

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H-SB016.1-007

Company

InferLink Corporation
2361 Rosecrans Ave., Suite 348
El Segundo, CA 90245-2901

Proposal Information HSHQDC-16-R-00012-H-SB016.1-007-0008-I - OpenWatch: An Architecture for Scalable Resiliency Assessment
Topic Information H-SB016.1-007 - Real-Time Assessment of Resilience and Preparedness
Award/Contract Number HSHQDC-16-C-00070
Abstract

In this project, we propose to develop software that employs open source information to assess a community's resilience and preparedness. The goal is challenging because current technology does not scale well due to the heterogeneity of the problem. Specifically, the heterogeneity of the data, as well as the heterogeneity of the assessment process makes it time-consuming to develop extractors for harvesting relevant data, as well as to develop decision methods for performing resiliency/preparedness assessments. Our work in phase I will include identifying detailed use cases and sample data, along with an ontology for the application. We will also develop an end-to-design for a system, OpenWatch, that we will prototype in Phase II. Finally, we will develop machine learning technology to deal with the heterogeneity problem, including algorithms for semi-automatically developing extractors and semi-automatically developing design surfaces for resiliency assessment. The results of the project will include an open-source software architecture for resiliency assessment, upon which a commercial resiliency-assessment service can be built. In addition, aggregated resilience-related data can be repurposed for multiple commercial verticals, including in particular the insurance industry. The technology developed will also contribute to developing a cloud-based service for Web aggregation that can be rapidly customized for new verticals.

Company

Datanova Scientific LLC
3000 Chestnut Ave, Suite 109A
Baltimore, MD 21211-2796

Proposal Information HSHQDC-16-R-00012-H-SB016.1-007-0021-I - RIDER on the Storm: A Cogntive Cloud for Resilience Assessment
Topic Information H-SB016.1-007 - Real-Time Assessment of Resilience and Preparedness
Award/Contract Number HSHQDC-16-C-00069
Abstract

We propose Real-time Intelligent Determination of Resilience (RIDER), a cognitive cloud product that consumes real-time data to generate a predictive and proactive risk and resilience posture with site-specific granularity. RIDER utilizes existing FEMA resources in a novel and innovative way for site-specific predictive and proactive risk generation. This statistical risk will be combined with prioritized open data sources (like Twitter) to generate an accurate and current resilience assessment. RIDER will utilize cognitive computing to exploit the open data sources and the FEMA data. The various datasets will be fused together using a deductive semantic model. The RIDER product will produce various visualizations such as heat maps to assess overall resilience of a community. It will also be able to zoom into a specific site or infrastructural component, and be able to provide a detailed logical proof of what affected that site's resilience; this feature is important for the end user to obtain insight from the system. RIDER will also be able to ascertain the conditions under which the risk is acceptable or unacceptable for a given site. The proposed solution addresses the urgent need for resilience assessment in various markets like local governments, the DoD, and commercial insurance companies. Local governments can use RIDER to assess their community's resilience. The DoD is interested in protecting its mission critical infrastructure in various global force deployments. Flood insurance in coastal communities can be optimized greatly using the site-specific, granular, and real time operation of RIDER.

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H-SB016.1-008

Company

Physical Optics Corporation
Electro-Optics Systems Division
1845 West 205th Street
Torrance, CA 90501-1510

Proposal Information HSHQDC-16-R-00012-H-SB016.1-008-0010-I - Real-time Information Contextual Correlation and Analysis
Topic Information H-SB016.1-008 - Using Social Media to Support Timely and Targeted Emergency Response Actions
Award/Contract Number HSHQDC-16-C-00060
Abstract

To address the DHS need for a new data analytics engine to correlate social media comments and activity with incident command data, Physical Optics Corporation (POC) proposes to develop a new Real-time Information Contextual Correlation and Analysis (RICCA) software system based on Bayesian analytics, multiresolution event context hypercube (MECH) representation, and multi-source data analysis and fusion using social media ontologies and emergency management ontologies. RICCA offers automatic and real-time extraction of multiple external factors relevant to an event of interest from social media outlets, to improve incident command's situational awareness and understanding. In Phase I, POC will demonstrate the feasibility of RICCA by developing a set of operational scenarios, identifying the external factors in social media and operational incident data, developing core analytics modules, and implementing algorithms to measure performance and improvements. In Phase II, POC plans to mature the RICCA prototype and correlation and analysis algorithms to support a pilot protocol by which a social media feed is correlated with operational incident data. The successful completion of this project at the end of Phase III will benefit the nation in both government and commercial sectors by improving the situational awareness and decision-making capabilities of incident commands and significantly improving the effectiveness of response decisions and actions. Commercial applications for this technology range from personal use to business intelligence, news gathering, trend analysis, and data gathering applications.

Company

ElanTech
9250 Bendix Road
Suite 1030
Columbia, MD 21045-1832

Proposal Information HSHQDC-16-R-00012-H-SB016.1-008-0014-I - Social Media and CAD Correlation (SMaCC)
Topic Information H-SB016.1-008 - Using Social Media to Support Timely and Targeted Emergency Response Actions
Award/Contract Number HSHQDC-16-C-00057
Abstract

The purpose of the research is to demonstrate the feasibility of using social media to improve situational awareness and support decision making, pre-emptive response, and predicted outcomes for operational response by first responders. Through customer discovery and literature research, a selected set of Meaningful Events will be identified that, if supported by corroborated data, would provide improved operational responses. Specific social media and computer aided dispatch (CAD) feeds will be identified. The broader factors/triggers supporting and validating Meaningful Events will be discovered. Research the availability of tools and technologies that may support correlated data analytics. Research and document the ways in which correlated data may support operational response(s). Results of this research will include Meaningful Events, validated and supported by potential customer interviews. Once the Meaningful Events are defined, the broader factors and triggers enabling correlation between CAD data and social media data would be identified. The correlated results that support operational response capabilities will be determined. Potential use of correlated data by command and control for operational response, situational awareness and decision making will be documented. First responder, public safety and other organizations would have a tool that could quantify, validate, correlate and present supportive, action-oriented decision support tools around Meaningful Events. This process could enable first responders to modify and enhance the way they respond to mass casualty incidents, and other emergency situations using social media to expand their visibility into events as they occur, in real-time.

Company

DECISIVE ANALYTICS Corporation
1400 Crystal Drive
Suite 1400
Arlington, VA 22202-4361

Proposal Information HSHQDC-16-R-00012-H-SB016.1-008-0025-I - Social media Triggers for Alerting and Response (STAR)
Topic Information H-SB016.1-008 - Using Social Media to Support Timely and Targeted Emergency Response Actions
Award/Contract Number HSHQDC-16-C-00062
Abstract

Information present in social media is valuable to emergency response organizations which have a need to maintain situational awareness about the events and activities in a region of interest. Approaches to using social media to inform emergency personnel in rare and large-scale events such as earthquakes and hurricanes have been studied. However, the emergency response community has little experience with use of social media to improve the information available to first responders in more routine emergencies. The research proposed here applies Natural Language Processing and Machine Learning algorithms to the problem of extracting the signal of emergency incidents from social media data. In Phase I, the DAC team will identify a set of emergency incident types whose social media profile allows for incident detection, alignment with CAD incident data, and extraction of response-relevant information. At the conclusion of Phase I we will understand the tradeoffs between automated processing and manual analysis of social media and will be able to quantify the benefits social-media-sourced information can bring to the first responder. We will develop a prototype system that will demonstrate the feasibility of our approach, and define the requirements and touchpoints for integrating social-media algorithms into CAD systems. The technology developed under this effort can be transitioned into commercial emergency dispatch systems, and easily repurposed to address a variety of law enforcement and intelligence analysis scenarios. This work will be developed in partnership with the FDNY.

Company

UtopiaCompression Corporation
11150 W. Olympic Blvd.
Suite 820
Los Angeles, CA 90064-1818

Proposal Information HSHQDC-16-R-00012-H-SB016.1-008-0028-I - Joint Modeling of Social Media and CAD Data for Crisis Management Decision Support
Topic Information H-SB016.1-008 - Using Social Media to Support Timely and Targeted Emergency Response Actions
Award/Contract Number HSHQDC-16-C-00066
Abstract

Archived computer-aided dispatch (CAD) data has been beneficial for post-event analysis and continual improvement processes. First responder CAD data represents a potential data set that can be exploited by recently-emergent big data techniques. The criticality of first responder missions increases the importance of such efforts: the impact of CAD data analytics could be directly related to lives saved. Emergency management organizations are well aware of the power of social media (SM) to assist and improve response efforts. However, most are ill-equipped to ingest, process, and utilize in an intelligent, quantitative, and effective way, the enormous amount of SM data available. UtopiaCompression Corporation (UC) proposes to develop and deliver a comprehensive solution that can jointly analyze CAD and social media data in real time. This tool is intended to provide situational awareness, advanced analytics, visualization and decision support for crisis management, by detecting and classifying emergency events, and providing first responders with suggested courses of action. In Phase I, UC will (a) identify at least three emergency management scenarios for which the proposed tools may be applied; (b) develop its novel event detection, localization and tracking algorithm; (c) evaluate the developed system on candidate CAD/SM data sets to demonstrate proof-of-concept. The developed tool is expected to have significant commercial applications in a diverse range of tasks including automated threat assessment, disaster/crisis management and emergency response.

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H-SB016.1-009

Company

BlockCypher
652 Sea Anchor Dr #2202
Redwood City, CA 94063-2894

Proposal Information HSHQDC-16-R-00012-H-SB016.1-009-0009-I - Blockchain Platform for Multiple Blockchains, Applications, and Analytics
Topic Information H-SB016.1-009 - Blockchain Applications for Homeland Security Analytics
Award/Contract Number HSHQDC-16-C-00080
Abstract

The purpose of this proposal is to provide a platform for multiple blockchains, applications, and the analysis of blockchain transactional data. BlockCypher has already built a blockchain infrastructure that supports a multitude of applications, e.g., identify management, internet-of-things (IoT), notary, embeddable assets, predictive analytics, etc. - and runs both closed and open blockchains on the same infrastructure. BlockCypher's platform currently supports the ability to embed encrypted data on any blockchain, predict which transactions will be accepted, and hosts a multitude of security measures that can provide a significant value proposition for homeland security applications. BlockCypher also stores and handles massive amounts of public blockchain transaction data (multiple terabytes) in distributed and redundant data stores. BlockCypher currently uses the data to do real-time predictive risk assessment and analysis. BlockCypher's proposal for Phase I is to design and prototype an analytical framework that allows DHS to utilize the data which is already being captured by BlockCypher and to make it actionable.

Company

RAM Laboratories, Inc.
591 Camino de la Reina
Suite 610
San Diego, CA 92108-3108

Proposal Information HSHQDC-16-R-00012-H-SB016.1-009-0014-I - Enhanced Blockchain Trust Services
Topic Information H-SB016.1-009 - Blockchain Applications for Homeland Security Analytics
Award/Contract Number HSHQDC-16-C-00079
Abstract

Several security shortfalls associated with the Internet of Things (IoTs) are related to key management and distributions, which are used to encrypt, sign and authenticate messages and remotely manage participating applications. These challenges are especially difficult to address in disadvantaged, intermittent and low latency (DIL) environments, such as those faced by first responders, where the ability to exchange keys to authenticate users, devices, and messages may be thwarted by the lack of connectivity. Blockchain technologies can address they shortfalls through the used of secure decentralized computing ledgers that update distributed nodes with ongoing consensus truth states. RAM Laboratories is proposing, within the context of a prototype ecosystem, to build on Blockchain concepts and develop an innovative set of Enhanced Blockchain Trust Services (EBTS) for use by first responders on attestation, signature generation, and authentication. EBTS services are pioneering in that they both establish a unique fingerprint for the target device by utilizing device fingerprint information extracted from hardware sensors, the device software configuration, and the network configuration parameters, and trust attestations computed by neighboring nodes and transaction partners in the distributed network. Attestations and keys generation from hardware, software, trust scores and network parameters alleviate the need for protected identity key storage and device re-keying. The proposed EBTS solution will also be integrated with network defense environments to provide enhanced capabilities for handling security polices, information security, network security, and user privacy.

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H-SB016.1-010

Company

CardSmart Technologies
17 Normandy
Basking Ridge, NJ 07920-1905

Proposal Information HSHQDC-16-R-00012-H-SB016.1-010-0006-I - Composite Identity Model for Optimizing Next Generation Remote Identity Proofing Methods
Topic Information H-SB016.1-010 - Remote Identity Proofing Alternatives to Knowledge Based Authentication/Verification
Award/Contract Number HSHQDC-16-C-00063
Abstract

Losses due to identity misuse/fraud are staggering. The most commonly implemented identity proofing technique is Knowledge Based Verification (KBV), where applicants are challenged with questions for which only they know the answer. However KBV has a number of shortcomings, most notably that with widespread spillage of PII there isn't much that is "known only to the applicant". The proposed Phase I research will investigate the effectiveness of eight KBV-alternative approaches, ranging from online reputation to voice forensics. Some of these approaches have been previously attempted in a limited manner, others are more theoretical. Metrics will be developed around which these approaches can be categorized/evaluated including: complexity, implementation cost, ease of use, and other measures of effectiveness. The most promising of these methods will then populate a model for identity enrichment. This "Composite Identity" model will demonstrate how multiple identity proofing methods can be combined in order to exponentially strengthen the overall level of identity assurance. The composite identity model can even map-reduce all that is known about an identity to a single Composite Identity Score for each applicant, similar to the FICO number that credit agencies use as a measure of one's credit worthiness. Future commercial potential includes; the high-scoring identification verification methods or technologies could be further developed for widespread use; the composite identity model could be packaged as a plug-in for website builders requiring turn-key identity proofing; currency-style block chain technology could be the means by which Composite Identities are distributed and mutually trusted.

Company

PreID Inc.
37 Park Dr
Atherton, CA 94027-4011

Proposal Information HSHQDC-16-R-00012-H-SB016.1-010-0007-I - Remote Identity Proofing Methods and Analysis
Topic Information H-SB016.1-010 - Remote Identity Proofing Alternatives to Knowledge Based Authentication/Verification
Award/Contract Number HSHQDC-16-C-00064
Abstract

The Internet and mobile technologies has brought on a rapid transition from doing business "in-person" to remote. Knowing the identity of the individual at this other end of the wire is at the very foundation of trust and security of this new world. Traditional methods to prove identity, such as driver's licenses, were designed for "in-person" use, not the digital economy. Instead, the Internet has turned to use Knowledge-Based Methods for remote identity-proofing, but the explosion of data breaches and the underground market selling Personally Identifiable Information (PII) has rendered that approach risky and weak. New methods and technologies are needed. Notably, there are new tools such as biometrics and sensor-laden smartphones just now gaining mass consumer deployment and acceptance, and also a critical-mass in membership of social networks such as Facebook and LinkedIn which could form the basis of an answer to this problem. The goal from this Phase I research is to rigorously review five or more such new approaches to identity-proofing, specifically to determine for each the technical strengths and weaknesses (security, privacy, accuracy), and commercial feasibility (cost, time to market, consumer acceptance). The immediate benefit to the Department of Homeland Security will be as technical guidance document for any program which requires remote identity-proofing, but longer term the commercial potential for a commercial/government partnership is to redefine strong digital identity is mission critical in the future of the Internet.

Company

Pomian & Corella, LLC
5120 Marconi Ave Apt 26
Carmichael, CA 95608-4281

Proposal Information HSHQDC-16-R-00012-H-SB016.1-010-0012-I - Practical Alternatives for Population-Scale Remote Identity Proofing
Topic Information H-SB016.1-010 - Remote Identity Proofing Alternatives to Knowledge Based Authentication/Verification
Award/Contract Number HSHQDC-16-C-00052
Abstract

The purpose of this multiphase SBIR project is to identify, define and demonstrate a range of alternatives to knowledge-based verification for remote identity proofing. Knowledge-based verification is becoming less and less secure due to the increased availability to fraudsters of personally identifiable information. The project will expand the multidimensional space of remote identity proofing solutions by considering innovations including the use of EMV chip cards as identity tokens, the use of federated identity protocols for directly conveying validated attributes from identity providers to relying parties, and the use of persistent web storage available in modern browsers to store cryptographic credentials carrying validated attributes. Five or more solutions will be selected from the expanded multidimensional space, analyzed, and ranked according to the identity assurance, privacy and user experience they provide. The most promising ones will be demonstrated by building prototypes. It is anticipated that the project will ultimately result in commercial products implementing remote identity proofing solutions usable by Federal Agencies to verify the identity and eligibility of citizens seeking government services, as well as by state, local and tribal governments for similar purposes. The same commercial products will also be usable in the private sector for applications such as remote loan issuance or remote application for credit cards. Eliminating the use knowledge-based verification will make identity theft much more difficult and will increase privacy by reducing the incentives to collect personally identifiable information by legal or illegal means.

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