APPROVED_PUBLIC_RELEASE_RFI for PIN-Cyber_JUNE062024v2.docx

APPROVED FOR PUBLIC RELEASE

RFI for Predictive Cyber Analytics and Response Optimization

Request for Information (RFI) for Predictive Cyber Analytics and Response Optimization

DISCLAIMER:

THIS IS NOT A SOLICITATION: No award will be made as a result of this request. This RFI is for informational and planning purposes only; this is not an Invitation for Bid, a Request for Proposal, or a Request for Quotation. No solicitation document exists, and a formal solicitation will not be issued by the Government after receiving responses to this RFI. The Government will not be liable for payment of any costs incurred in response to this RFI and is under no obligation to act in any way on the information received. No costs incurred by interested companies in response to this announcement will be reimbursed. The information provided may be used by the Army in developing a future acquisition strategy, Performance Work Statement, Statement of Objectives and/or Performance Based Specification(s). Interested parties are responsible for adequately marking proprietary or competition sensitive information contained in their response.

PURPOSE:

The U.S. Army Combat Capabilities Development Command (DEVCOM), Command, Control, Communications, Computers, Cyber, Intelligence, Surveillance and Reconnaissance (C5ISR) Center is surveying the market to locate/identify interested Business Concerns. The US Army C5ISR Center, Engineering & Systems Integration (ESI) is interested in addressing the issue of the current reactive cybersecurity approach. This approach depends on security information and event management (SIEM) and security orchestration, automation, and response (SOAR) processes that only activate after potential issues are detected, resulting in network degradation or downtime. ESI is seeking information from companies offering solutions that leverage advancements in artificial intelligence (AI) to enable predictive cyber analytics with the goal to proactively enhance the cyber resilience of Army tactical networks.

BACKGROUND:

The Army is in the process of continuous modernization of its tactical communications networks. This effort is to understand how artificial intelligence (AI) capabilities can assist with network configuration and management, network defense, and network resiliency in the face of AI-enabled or other attempts by adversaries to degrade Army network operations. In exploring new AI-enabled network management and cybersecurity response, the Army is also exploring how network/application segmentation or other techniques might contribute to greater network resilience. The Army is evaluating available vendor options to determine marketplace evolution and technological advancement.

INFORMATION REQUESTED: Interested parties with the ability to design and demonstrate a predictive analytics and response optimization solution should submit a Whitepaper not to exceed 10 pages in length. At a minimum, the Whitepaper should address the following information:

1. Recent and Relevant performance contracts with Government customers, particularly within the DoD.

2. Delivery model, including hardware/software requirements, licensing cost model for approximately 3 million Army users, cost variations for different networks (e.g., NIPRNet vs. SIPRNet) and user types, and options for product expansion/customization.

3. Support for various SIEM and SOAR tools, including cyber monitoring and integration.

4. Approach to predictive cybersecurity, AI/ML models used, experience with these models, and the cybersecurity frameworks employed and interoperability with established cyber frameworks such as MITRE ATT&CK® and D3FEND™.

5. Approach to micro-segmentation, compliance with DoD Zero Trust Reference Architecture, experience with micro-segmentation, level of micro-segmentation supported, and changes to network required and access policy modifications for micro-segmentation.

6. Approach to mitigation and recommendations, including changing/restructuring micro-segmentation and modifying access policies, and any relevant project experience.

7. Other techniques to enhance network security and limit lateral movement in the network.

8. Objective measures of effectiveness to assess your solutions and capabilities.

9. Explainability approaches for predictions and responses.

10. Estimated technology readiness level (TRL) at the start and end of the effort, and applicability to Army tactical networks under constrained conditions.

Interested parties are encouraged to submit their information electronically by 1700 EST on 06 JUL 2024 to the ESI BAA inbox; usarmy.apg.devcom-c5isr.mbx.esi-bus-ops-acq-baa@army.mil. The subject line for the email submission should read: “RFI: PIN CYBER – YOUR COMPANY”.

Any company proprietary information, performance capabilities and/or future modification plans should be clearly identified and MUST be marked accordingly and will be protected by the Government. All information marked as proprietary information will be safeguarded to prevent disclosures to non-government personnel and entities. Please do not submit classified information in responses to this RFI; if necessary, classified discussions with the Government can occur later via secure means.

Please include a Cover Page (excluded from page count) that includes:

1. Point of contact information to include: company name, contact name, company address, company website

2. Commercial and Government Entity (CAGE) Code and Data Universal Numbering System (DUNS) Number

REFERENCES:

Department of Defense Office of Publications and Security Review, “Department of Defense (DoD) Zero Trust Reference Architecture”, Version 2.0, July 2022 (https://dodcio.defense.gov/Portals/0/Documents/Library/(U)ZT_RA_v2.0(U)_Sep22.pdf)

Department of Defense Office of Publications and Security Review, “DOD Zero Trust Strategy”, November 2022 (https://dodcio.defense.gov/Portals/0/Documents/Library/DoD-ZTStrategy.pdf)

Strom B.E., Applebaum A., Miller D.P., Nickels K.C., Pennington A.G., Thomas C.B., MITRE ATT&CK®: Design and Philosophy. Revised March 2020, The MITRE Corporation; Bedford, MA, USA: 2020. (https://attack.mitre.org/docs/ATTACK_Design_and_Philosophy_March_2020.pdf)

Kaloroumakis, P., Smith, M., Toward a Knowledge Graph of Cybersecurity Countermeasures, (https://d3fend.mitre.org/resources/D3FEND.pdf)