SBIR/STTR Research Award

LOQI: Leveraging Optimization using Quantum-devices for Internet-security

Award identifier db318e1ac8c85aa4b2a45f14f0ac0e3b21a3011236f5b5e9af26f5607767db3dAwarding agency Department of Defense · Air Force

Award amount

$147,649

Program and phase

STTR · Phase I

Award year

2020

Explore This Research Award in CaptureIQ

Research the technology, evaluate the recipient and agency, identify related opportunities, and explore potential follow-on work with CaptureIQ.

Award details

Awarding agency
Department of Defense
Branch
Air Force
Recipient company
QC WARE CORP.
Proposal award date
2020-06-16
Contract end date
2020-11-16
UEI
R4UQNKMZKTB3
Solicitation number
20.A
Topic code
AF20A-T003

Research abstract

The Leveraging Optimization via Quantum-devices for Internet-security (LOQI) proposal aims to demonstrate the power of hybrid (quantum/classical) optimization approaches for classes of combinatorial optimization problems that are relevant to several cyber-security settings. In Phase 1 (this proposal) we will conduct a feasibility study to develop an analytical framework and algorithms, and prototype them in simulation and software, to explore the power of such hybrid algorithms in solving combinatorial optimization problems can be represented as variations of the Multi-dimensional Knapsack Problem (MKP). One of the main objectives of LOQI is to develop variations of hybrid algorithms that can be executed in the near future on Noisy Intermediate-Scale Quantum (NISQ) devices. MKP based optimization problems have several applications in networking-security and cyber-security. Most of the applications we envision can be abstracted as variations of a constrained resource allocation problem that can be cast as an MKP instance. The three applications that we will focus on in this proposal are: (i) allocating micro-services in a cloud environment to maintain a certain level of quality-of-service to different jobs, especially if under a heavy load, and in the existence of potentially malicious resource-draining processes, (ii) allocating filtering and rate limiting resources locally or upstream in a network to defend distributed against denial-of-service (DDoS) attacks, and (iii) allocating network routes and forwarding rules in the routing infrastructure, e.g., in Software Defined Networking (SDN) controllers, to ensure resilience and operations in a network under attack.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

4 SBIR/STTR records share this UEI (2017–2020). Reported award amounts total $1,169,029. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Defense, National Science Foundation

Agency intelligence

Department of Defense

Back to SBIR/STTR Research Awards

Don't take our word for it. Ask AI about RFPCapture.

See what leading AI assistants have to say about RFPCapture and CaptureIQ.

Gemini opens without a prefilled question. The question is copied to your clipboard when the button works. You can also copy it here:

What is RFPCapture.com and its CaptureIQ platform from Smart Logic AI? How does it help federal contractors discover opportunities, evaluate bid/no-bid decisions, research government contracts, and prepare proposals? How does it compare with other federal capture platforms? Use independent sources where available.