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Awards

Topic Information Award/Contract Number Proposal Information Company Performance
Period
Award/Contract
Value
Abstract

H-SB016.1-005
Internet of Things (IoT) Low-Cost Flood Inundation Sensor

HSHQDC-16-C-00075 HSHQDC-16-R-00012-H-SB016.1-005-0018-I
(HSHQDC-16-R-00012 Phase I)
Real-time Flood Forecasting and Reporting

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

05/03/2016
to
11/02/2016
$99,997.47

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.

H-SB016.1-005
Internet of Things (IoT) Low-Cost Flood Inundation Sensor

HSHQDC-17-C-00020 HSHQDC-16-R-00012-H-SB016.1-005-0018-II
(HSHQDC-16-R-00012 Phase II)
Real-time Flood Forecasting and Reporting

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

03/20/2017
to
07/01/2019
$1,575,176.64

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 demonstrated the feasibility of RAFFAR by building and testing a preliminary prototype network and performing an analysis of a full-size network roll-out. At the end of the Phase I effort, the RAFFAR system reached TRL-6. In Phase II, POC plans to manufacture sufficient sensors to deploy a 100+ unit network for extensive 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.

H-SB016.1-007
Real-Time Assessment of Resilience and Preparedness

HSHQDC-16-C-00070 HSHQDC-16-R-00012-H-SB016.1-007-0008-I
(HSHQDC-16-R-00012 Phase I)
OpenWatch: An Architecture for Scalable Resiliency Assessment

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

05/02/2016
to
11/01/2016
$100,000.00

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.

H-SB016.1-007
Real-Time Assessment of Resilience and Preparedness

HSHQDC-17-C-00015 HSHQDC-16-R-00012-H-SB016.1-007-0008-II
(HSHQDC-16-R-00012 Phase II)
OpenWatch: An Architecture for Scalable Resiliency Assessment

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

04/10/2017
to
04/09/2019
$749,999.99

In this project, we propose to develop software that employs open source information to assess factors related to resilience. 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 II will produce an end-to-end working system, called OpenWatch, that can use real-time, open-source data to assess resilience, and provide the results to end users. The system will make it simple and fast to aggregate data from multiple Web sources, and also assist in the development of sophisticated risk assessment models. The results of the project will include an open-source software system for risk assessment. In addition, we will use the system to develop applications that address important resiliency issues. This will include an application to a produce a neighborhood-level heat vulnerability index for cities throughout the United States, and an application for predicting CVSS scores based on cyber vulnerability announcements, which can be employed commercially.

H-SB016.1-008
Using Social Media to Support Timely and Targeted Emergency Response Actions

HSHQDC-16-C-00060 HSHQDC-16-R-00012-H-SB016.1-008-0010-I
(HSHQDC-16-R-00012 Phase I)
Real-time Information Contextual Correlation and Analysis

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

05/02/2016
to
11/01/2016
$99,993.99

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.

H-SB016.1-008
Using Social Media to Support Timely and Targeted Emergency Response Actions

HSHQDC17C00016 HSHQDC-16-R-00012-H-SB016.1-008-0010-II
(HSHQDC-16-R-00012 Phase II)
Real-time Information Contextual Correlation and Analysis Software System

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

03/31/2017
to
03/30/2019
$749,346.42

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, in Phase II, to advance a new Real-time Information Contextual Correlation and Analysis (RICCA) software system proven feasible in Phase I. RICCA is based on unstructured data analysis and integration and event context modeling. Its advanced contextual analytics engine enables automated processing flow to retrieve social media data from multiple outlets (Facebook, Twitter, YouTube), extract environmental, social, meteorological, political, economic, and other factors relevant to an event of interest, correlate them in geo-space and time with data stored in a computer-aided-dispatch (CAD) system, and generate alerts for first responders and emergency/incident/crisis management. The innovation in unstructured data processing and integration and multi-resolution event context modeling can improve incident command's situational awareness and understanding. In Phase I, POC demonstrated 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 its correlation and analysis algorithms for the target scenario established in Phase I and support a pilot protocol by which a social media feed is correlated with operational incident data. Validation and trust algorithms will also be developed to support more timely and targeted response actions and allow for escalation preparedness.

H-SB016.1-008
Using Social Media to Support Timely and Targeted Emergency Response Actions

HSHQDC-16-C-00066 HSHQDC-16-R-00012-H-SB016.1-008-0028-I
(HSHQDC-16-R-00012 Phase I)
Joint Modeling of Social Media and CAD Data for Crisis Management Decision Support

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

05/02/2016
to
11/01/2016
$99,988.18

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.

H-SB016.1-009
Blockchain Applications for Homeland Security Analytics

HSHQDC-16-C-00080 HSHQDC-16-R-00012-H-SB016.1-009-0009-I
(HSHQDC-16-R-00012 Phase I)
Blockchain Platform for Multiple Blockchains, Applications, and Analytics

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

05/02/2016
to
11/01/2016
$99,946.82

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.

H-SB016.1-009
Blockchain Applications for Homeland Security Analytics

HSHQDC-17-C-00011 HSHQDC-16-R-00012-H-SB016.1-009-0009-II
(HSHQDC-16-R-00012 Phase II)
Blockchain Platform for Multiple Blockchains, Applications, and Analytics Phase II

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

03/20/2017
to
05/31/2018
$749,835.71

The purpose of this proposal is to continue work done in Phase I on a platform for multiple blockchains, applications, and the analysis of blockchain transactional data. BlockCypher has 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 larges amounts of public blockchain transaction data (multiple terabytes) in distributed and redundant data stores. In Phase I, we built a blockchain analytical framework and an Analytics API on top of our data store so we would see if any useful information and patterns could be extracted. Phase II will build upon the framework of Phase I and will dive deeper into broader-scale use cases for analytics (e.g. identity, law enforcement, compliance).

H-SB016.1-009
Blockchain Applications for Homeland Security Analytics

HSHQDC-16-C-00079 HSHQDC-16-R-00012-H-SB016.1-009-0014-I
(HSHQDC-16-R-00012 Phase I)
Enhanced Blockchain Trust Services

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

05/02/2016
to
11/01/2016
$100,000.00

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.

H-SB016.1-010
Remote Identity Proofing Alternatives to Knowledge Based Authentication/Verification

HSHQDC-16-C-00064 HSHQDC-16-R-00012-H-SB016.1-010-0007-I
(HSHQDC-16-R-00012 Phase I)
Remote Identity Proofing Methods and Analysis

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

05/02/2016
to
11/01/2016
$99,476.22

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.

H-SB016.1-010
Remote Identity Proofing Alternatives to Knowledge Based Authentication/Verification

HSHQDC-16-C-00052 HSHQDC-16-R-00012-H-SB016.1-010-0012-I
(HSHQDC-16-R-00012 Phase I)
Practical Alternatives for Population-Scale Remote Identity Proofing

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

05/02/2016
to
11/01/2016
$99,674.82

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.