Autonomous systems are proliferating rapidly, with strong interest in everything from vacuum cleaners and lawnmowers, to self-driving cars and autonomous farm equipment. Can these systems be trusted to function safely? Many conventional software
Poster: Green Network Optimization with Multi-Agent Reinforcement Learning: Work in Progress
This paper proposes a distributed Green Network Optimization (GNO) with Multi-Agent Reinforcement Learning (MARL). GNO-MARL combines: (a) Network Utility Maximization (NUM) based network management, given the capacity constraints, on a "fast" time scale
Evaluating the security of CRYSTALS-Dilithium in the quantum random oracle model
In the wake of recent progress on quantum computing hardware, the National Institute of Standards and Technology (NIST) is standardizing cryptographic protocols that are resistant to attacks by quantum adversaries. The primary digital signature scheme that
Practical Attack on All Parameters of the DME Signature Scheme
DME is a multivariate scheme submitted to the call for additional signatures recently launched by NIST. Its performance is one of the best among all the candidates. The public key is constructed from the alternation of very structured linear and non-linear
Context-Aware Channel Sounder for AI-Assisted Radio-Frequency Channel Modeling
We describe a context-aware channel sounder that consists of three separate systems: a radio-frequency system to extract multipaths scattered from the surrounding environment in the 3D geometrical domain, a Lidar system to generate a point cloud of the
AI-Based Environment Segmentation Using a Context-Aware Channel Sounder
We describe how the data acquired from the camera and Lidar systems of our context-aware radio-frequency (RF) channel sounder is used to reconstruct a 3D mesh of the surrounding environment, segmented and classified into discrete objects. First, the images
Incorporating Syncable Authenticators Into NIST SP 800-63B
This supplement to NIST Special Publication 800-63B, Authentication and Lifecycle Management, provides agencies with additional guidance on the use of authenticators that may be synced between devices.
Developments and applications of the OPTIMADE API for materials discovery, design, and data exchange
The Open Databases Integration for Materials Design (OPTIMADE) application programming interface (API) empowers users with holistic access to a growing federation of databases, enhancing the accessibility and discoverability of materials and chemical data
Empirical Characterization of Doppler in Industrial Wireless Channels
This paper analyzes the temporal variation of the radio propagation channel in industrial environments. The results have been obtained by processing empirical data from the National Institute of Standards and Technology (NIST) in a field measurement
This paper presents a network management AI assistant built with Large Language Models. It adapts at runtime to the network state and specific platform, leveraging techniques like prompt engineering, document retrieval, and Knowledge Graph integration. The
Network management relies on extensive monitoring of network state to analyze network behavior, design optimizations, plan upgrades, and conduct troubleshooting. Network monitoring collects various data from network devices through different protocols and
Automated Network Programmability Using OpenConfig YANG Models and NETCONF Protocol
This paper introduces a microservice-based architecture designed to enable automation of network programmability and management. Amid the complexity of today's networks and the diversity of equipment, achieving efficient and reliable network
Design and Implementation of an Automated Network Traffic Analysis System using Elastic Stack
This paper builds upon our previous work on Network Security Traffic Analysis Platforms (NSTAP) [1], presenting an advanced framework for the real-time monitoring of network traffic and endpoint security in large-scale enterprises. We employ a fully
2024 NIST Generative AI (GenAI): Evaluation Plan for Text-to-Text (T2T) Discriminators
Generator (G) teams will be tested on their system's ability to generate content that is indistinguishable from human-generated content. For the pilot study, the evaluation will help determine strengths and weaknesses in their approaches including insights
2024 NIST Generative AI (GenAI): Data Creation Specification for Text-to-Text (T2T) Generators
Generator (G) teams will be tested on their system ability to generate content that is indistinguishable from human-generated content. For the pilot study, the evaluation will help determine strengths and weaknesses in their approaches including insights
Cyclostationary Channel Power Measurements for CBRS Coexistence Assessment
We present a compressive approach for channel power measurements in coexistence scenarios involving heterogeneous cyclostationary channel usage and an example application in the Citizens Broadband Radio Service (CBRS) band. The method leverages known cycle
As artificial intelligence (AI) systems continue to be developed, humans will increasingly participate in human-AI interactions. Humans interact with AI systems to achieve particular goals. To ensure that AI systems contribute positively to human-AI
Improving the TENOR of Labeling: Re-evaluating Topic Models for Content Analysis
Topic models are a popular tool for understanding text collections, but their evaluation has been a point of contention. Automated evaluation metrics such as coherence are often used, however, their validity has been questioned for neural topic models
From Ivory Tower to Real World: Building Bridges Between Research and Practice in Human-Centered Cybersecurity
Research insights critical to improving people's cybersecurity experiences and outcomes may not be integrated into practice, demonstrating the often-observed and dreaded "research-practice gap." This talk will describe recent NIST research efforts to