Potomac Research LLC — Department of Defense STTR Phase I: A18B-T001
Potomac Research LLC — STTR Phase I award from Department of Defense.
Phase I STTR feasibility signal
- Phase I awards fund proof-of-concept work. For capture teams, they mark early interest from Department of Defense in a technical approach.
- Watch for Phase II follow-ons from the same firm/topic family — that conversion path is where budgets and transition pressure rise.
- Obligated amount $149,942. Cross-check similar awards in the same agency and technology tags for going-rate context.
- Topic code A18B-T001 links this award to a solicitation family — search the same topic stem for incumbents and recompete timing.
- Amount
- $149,942
- Agency
- Department of Defense · Army
- Program / Phase
- STTR · Phase I
- Topic
- A18B-T001
- Solicitation
- 2018.0
- NAICS
- —
- Place of performance
- VA
- Period
- 2018-11-15 → 2019-02-15
Description
Physically UnclonableFunctions (PUFs) have been proposed as central building blocks in cryptographic protocols and security architectures. PUFs are physical devices that exhibit a challenge/responsebehavior: when presented with a challenge, the device produces a response that is a random function of both the challenge and the physical properties of the device.In contrast to most digital designs, it isdesired that a PUF device be highly sensitive to small variations so that even the manufacturer cannotproduce two PUFs that give identical challenge/response behavior. This unclonability or uniquenessproperty enables PUFs to be used for applications such as device identification and authentication, binding software to hardware platforms and secure storage of cryptographic secrets. Despite their promise,existing PUF-based security solutions typically rely on assumptions that have not been confirmed for all PUF types.For instance, many PUF scan be simulated with software, which contradicts theunpredictability and unclonability properties. This project proposes to evaluate three novel designs of PUFs that may defeat current modeling attacks.