The National Institute of Science and Technology is soliciting feedback on its draft guidance on using key-encapsulation mechanisms, or KEMs, for protection against cyberattacks using quantum computers. The guide follows up on the August release of NIST’s updated cryptographic standards with an algorithm for quantum attack protection, the institute said Tuesday. 

NIST added that the public input on the guidance, titled Recommendations for Key Encapsulation Mechanisms, will help it select one or two additional KEMs for standardization. Through KEMs and their set of algorithms, two parties can share a secret key for performing tasks, such as encryption and authentication, over a public channel.

Multi-Algorithm Protection Key

Approaches to establishing a multi-algorithm key in creating and combining shared secrets are among the recommendations in the 52-page guidance. It also provides KEMs’ definitions, properties and applications.

The deadline for submitting comments—which can be e-mailed to sp800-227-comments@nist.gov—is March 7.

In November, NIST solicited public comments on the first draft of its report describing how the agency will manage and guide the transition to cryptography standards less vulnerable to quantum attacks. The 22-page draft report, titled “Transition to Post-Quantum Cryptography Standards,” pinpoints the current quantum-vulnerable cryptographic standards and existing quantum-resistant algorithms proposed for deployment in the migration.

The U.S. Army Yuma Proving Ground, or YPG, is advancing practical artificial intelligence use through its data architecture to support the post’s testing missions. The unit is continuing to develop its AI and enterprise data processes in tandem with the Army Test and Evaluation Command, the Army said Wednesday.

According to the service, YPG has an edge in tapping AI with the vast historical data it has stored from decades of testing and potentially useful for training AI models in automated analysis. The Army cited as an example YPG’s data use in the development of an algorithm to help facilitate air-to-surface-missile operations.

Potential Use in Maintenance, Sensor Development

Progress on AI deployment on data can also benefit most YPG’s non-destructive testing facility, the service noted. The technology can be used in the facility to assess potential problems with artillery tube depreciation through data compiled from laser-bore measurements. With AI, YPG can also explore the development of sensors that would enable faster firepower in near-peer combat situations, the Army said.

Ross Gwynn, YPG technical director, described AI application on the post’s database, as a “huge advantage” for the unit’s managers, especially if combined with business information.

“If we can automate that stream of business data in a similar manner as test data, it would have a lot of upside in efficiency gains,” he said.

AI is also the focus of the Army’s Network Enterprise Technology Command Data Science Directorate, which is launching NETCOM Edge, an advanced data analytics environment powered by the technology and machine learning capabilities.