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The Award database is continually updated throughout the year. As a result, data for FY24 is not expected to be complete until March, 2025.

Download all SBIR.gov award data either with award abstracts (290MB) or without award abstracts (65MB). A data dictionary and additional information is located on the Data Resource Page. Files are refreshed monthly.

The SBIR.gov award data files now contain the required fields to calculate award timeliness for individual awards or for an agency or branch. Additional information on calculating award timeliness is available on the Data Resource Page.

  1. Hardened Encryption Routing to Mitigate External Susceptibility

    SBC: Physical Optics Corporation            Topic: DHS201001

    To address the DHS's need for security of multimedia messages from the public to the Next Generation 9-1-1 (NG9-1-1) Public Safety Answering Point (PSAP) Emergency Communications Cybersecurity Center (EC3) within NG9-1-1 Emergency Service Internet Protocol Networks (ESINets), Physical Optics Corporation (POC) proposes to develop a new Hardened Encryption Routing to Mitigate External Susceptibility ...

    SBIR Phase I 2020 Department of Homeland Security
  2. Remote Sensor Data Protection and Anti-Spoofing

    SBC: BLUERISC INC            Topic: DHS201002

    Phase I project will be the investigation and specification of the necessary algorithms and platform for detection and mitigation of spoofing attacksand compromised sensing in sensor networks. The solution addresses the three main areas of sensing security: (a) detection and mitigation with corresponding customization; (b) support for collaborative, distributed detection across Ndes; and (c) hardw ...

    SBIR Phase I 2020 Department of Homeland Security
  3. Blockchain-based Anti-Spoofing and Integrity Protection

    SBC: INTELLISENSE SYSTEMS INC            Topic: DHS201002

    To address the DHS need for new remote sensor data protection and anti-spoofing techniques, Intellisense Systems, Inc. proposes to develop a new Blockchain-based Anti-Spoofing and Integrity Protection (BASIP) system. This proposed BASIP is based on redactable blockchain-based data protection and challenge-response-based spoof detection. The BASIP will offer high resilience to sensor spoofing and m ...

    SBIR Phase I 2020 Department of Homeland Security
  4. Emergency Digital Paging over Public Television (eDPPT)

    SBC: DEVICE SOLUTIONS INC            Topic: DHS201003

    Device Solutions (DS) and the Wireless Research Center (WRC) are teaming to create a development plan for inNvative digital paging for emergency responders using public television ATSC 3.0.Leveraging open standards, broadcast and public safety infrastructure, modern network devices, and new wireless electronics, our approach will provide responders and incident commanders with improved pager cover ...

    SBIR Phase I 2020 Department of Homeland Security
  5. Soft Targets and Crowded Places Security

    SBC: KARAGOZIAN & CASE, INC.            Topic: DHS201004

    To address the Department of Homeland Security (DHS) Cybersecurity and Infrastructure Security Agency (CISA) requirements and strategic intent, Karagozian and Case, Inc. (K&C) proposes to develop a SECURITY MITIGATION ASSESMENT OF RISKS AND THREATS (SMART) software application for SOFT TARGETS AND CROWDED PLACES (ST-CP) which leverages advanced Geographical Information Systems (GIS) mapping softwa ...

    SBIR Phase I 2020 Department of Homeland Security
  6. Handheld ANmaly Recognition Tool (HART)

    SBC: SPECTRAL LABS INCORPORATED            Topic: DHS201006

    Check point screening is key to mitigating threats in aviation transport as well as in missions protecting critical infrastructure, high-value cultural institutions, and persons, in a variety of missions from civilian security to law enforcement and corrections to military.These missions are made more challenging by the range of threats presents, from metallic weapons to liquid-based explosives.It ...

    SBIR Phase I 2020 Department of Homeland Security
  7. Handheld Advanced Detection/Imaging TechNlogy System

    SBC: LUNA INNOVATIONS INCORPORATED            Topic: DHS201006

    TeraMetrix is a wholly owned subsidiary of Luna InNvations Incorporated.Both TeraMetrix and Luna InNvations meet the SBIR eligibility requirements in size and Phase II conversion.We have attached Luna InNvations' registration SBC_000671230 because it includes ALL Luna employees and eliminates the question of does TeraMetrix as a subsidiary of Luna meet the size requirements. Luna as a whole, inclu ...

    SBIR Phase I 2020 Department of Homeland Security
  8. Targeted Surface Interrogation Scanning System

    SBC: INTELLISENSE SYSTEMS INC            Topic: DHS201007

    To address the DHS's need for a quick and efficient targeted surface interrogation technique to locate and detect trace residues of interest, including explosives and illicit drugs, on carry-on baggage and items, Intellisense Systems, Inc. proposes to develop a new rapid Targeted Surface Interrogation Scanning (TASIS) system, based on ultraviolet Raman spectroscopy and fast data processing/renderi ...

    SBIR Phase I 2020 Department of Homeland Security
  9. One dimensional convolutional neural networks for improved training time and standardization in spectral classification

    SBC: PHYSICAL SCIENCES INC.            Topic: DHS201009

    Physical Sciences Inc. (PSI) proposes to develop a deep learning based spectral target detection algorithm for identification and classification of opioids and explosives that will be executed on a portable hardware solution. The proposed algorithm is designed to be spectrometer agNstic and allows for rapid training on previously untrained spectrometer platforms. The proposed hardware solution is ...

    SBIR Phase I 2020 Department of Homeland Security
  10. Hybrid Machine Learning Approaches for Radiation Signature Identification

    SBC: RADIATION MONITORING DEVICES, INC.            Topic: NGA192002

    To improve the identification and detection of radio-logical materials, we propose a hybrid supervised learning and unsupervised machine learning approach to reduce the false positive rate, increase the accuracy and throughput, and augment the capabilities of the human operators. At the end of the Phase I, we will have a machine learning algorithm that is trained to recognize a variety of nuclear ...

    SBIR Phase I 2020 Department of DefenseNational Geospatial-Intelligence Agency
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