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Displaying 1 - 25 of 2253

Report on Secure Hardware Assurance Reference Dataset (SHARD) Program

October 1, 2024
Author(s)
Paul E. Black, Vadim Okun
Significant vulnerabilities have been found in chips. Computer programs and methods have been developed to prevent, find, and mitigate them. We proposed Secure Hardware Assurance Reference Dataset (SHARD) as a repository of reference examples (test cases)

A Data Protection Approach for Cloud-Native Applications

September 30, 2024
Author(s)
Ramaswamy Chandramouli, Wesley Hales
This document addresses the need for effective data protection strategies in the evolving realm of cloud-native network architectures, including multi-cloud environments, service mesh networks, and hybrid infrastructures. By extending foundational data

Summary Report: CHIPS R&D Program Standards Summit

September 27, 2024
Author(s)
Mary Bedner, Chris Greer
The mission of the National Institute of Standards and Technology's (NIST) CHIPS Research and Development Office (CHIPS R&D) under the Department of Commerce's CHIPS for America Program is to accelerate the development and commercial deployment of

Proxy Validation and Verification for Critical AI Systems

September 26, 2024
Author(s)
Phillip Laplante, Joanna DeFranco, D. Richard Kuhn, Jeff Voas
This white paper offers a suggestion that prior testing artifacts from similar AI systems can be reused for new AI software. Testing AI and Machine learning software is difficult, and if prior testing results from similar systems could be applied as a

Building a Cybersecurity and Privacy Learning Program

September 12, 2024
Author(s)
Marian Merritt, SUSAN HANSCHE, BRENDA ELLIS, Julie Nethery Snyder, KEVIN SANCHEZ-CHERRY, DONALD WALDEN
This publication provides guidance for federal agencies and organizations to develop and manage a life cycle approach to building a Cybersecurity and Privacy Learning Program (CPLP). The approach is intended to address the needs of large and small

Report on the Block Cipher Modes of Operation in the NIST SP 800-38 Series

September 10, 2024
Author(s)
Nicky Mouha, Morris J. Dworkin
This report focuses on the NIST-recommended block cipher modes of operation specified in NIST Special Publications (SP) 800-38A through 800-38F. The goal is to provide a concise survey of relevant research results about the algorithms and their

NIST Cloud Computing Forensic Reference Architecture

July 30, 2024
Author(s)
Martin Herman, Michaela Iorga, Ahsen Michael Salim, Robert H. Jackson, Mark R. Hurst, Ross A. Leo, Anand Kumar Mishra, Nancy M. Landreville, Yien Wang
This document summarizes the research performed by the NIST Cloud Computing Forensic Science Working Group and presents the NIST Cloud Computing Forensic Reference Architecture (CC FRA or FRA), whose goal is to provide support for a cloud system's forensic

Energy Efficiency Scaling for 2 Decades (EES2) Roadmap for Computing

July 14, 2024
Author(s)
Jim Booth
Abstract—In response to the looming crisis in global energy consumption required for advanced computing applications, the United States Department of Energy (DOE) Advanced Materials and Manufacturing Technology Office (AMMTO) is leading a national effort

A Review of the Literature on Voter Verification and Ballot Review

July 8, 2024
Author(s)
Whitney Quesenbery, Suzanne Chapman, Christopher Patten, Roberto Spreggiaro, Shanee Dawkins
One of the major issues for voting systems today is whether they provide voters with a meaningful opportunity to verify their ballot before casting it. This opportunity is important in helping them vote their intent by catching errors or omissions made

How Voters Review and Verify Ballots

July 8, 2024
Author(s)
Suzanne Chapman, Lynn Baumeister, Whitney Quesenbery, Shanee Dawkins
Qualitative research to gain deeper insights about how voters mark, review, verify, and cast their ballots. Conducted as part of the work to update the human factors—accessibility, privacy, and usability—requirements in federal voting system standards and

An Adaptable AI Assistant for Network Management

July 3, 2024
Author(s)
Amar Abane, Abdella Battou, Mheni Merzouki
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

Enhancing Network Data Plane Analysis with Native Graph Database

July 3, 2024
Author(s)
Amar Abane, Abdella Battou, Mheni Merzouki
As modern networks grow in complexity, ensuring their reliability and security becomes increasingly vital. Data plane analysis is a key process for verifying network behavior, but traditional data plane analysis tools face challenges in extensibility

Global Community Technology Challenge (GCTC) Strategic Plan 2024-2026

June 28, 2024
Author(s)
Michael Dunaway, Thomas Roth, Edward Griffor, David A. Wollman
This document provides a strategy and a project plan for the Global Community Technology Challenge, a federal smart cities program led by the Smart Connected Systems Division at the National Institute of Standards and Technology, an agency of the U.S

Leveraging Combinatorial Coverage in the Machine Learning Product Lifecycle

June 27, 2024
Author(s)
Jaganmohan Chandrasekaran, erin lanus, tyler cody, laura freeman, Raghu N. Kacker, M S Raunak, D. Richard Kuhn
The data-intensive nature of machine learning (ML)-enabled systems introduces unique challenges in test and evaluation. We present an overview of combinatorial coverage, exploring its applications across the ML-enabled system lifecycle and its potential to

Evaluating Large Language Models for Real World Vulnerability Repair in C/C++ Code

June 19, 2024
Author(s)
Lan Zhang, Qingtian Zou, Anoop Singhal, Xiaoyan Sun, Peng Liu
The advent of Large Language Models (LLMs) has enabled advancement in automated code generation, translation, and summarization. Despite their promise, evaluating the use of LLMs in repairing real-world code vulnerabilities remains underexplored. In this

Analysis of Neural Network Detectors for Network Attacks

June 17, 2024
Author(s)
Qingtian Zou, Lan Zhang, Anoop Singhal, Xiaoyan Sun, Peng Liu
While network attacks play a critical role in many advanced persistent threat (APT) campaigns, an arms race exists between the network defenders and the adversary: to make APT campaigns stealthy, the adversary is strongly motivated to evade the detection

Anomaly Based Intrusion Detection using Large Language Models

June 15, 2024
Author(s)
Zineb Maasaoui, Abdella Battou, Mheni Merzouki, Ahmed LBATH
In the context of modern networks where cyber-attacks are increasingly complex and frequent, traditional Intrusion Detection Systems (IDS) often struggle to manage the vast volume of data and fail to detect novel attacks. Leveraging Artificial Intelligence
Displaying 1 - 25 of 2253