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Information Technology

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Displaying 51 - 75 of 2282

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

Measurement-Based Prediction of mmWave Channel Parameters Using Deep Learning and Point Cloud

August 2, 2024
Author(s)
Anuraag Bodi, Raied Caromi, Jian Wang, Jelena Senic, Camillo Gentile, Hang Mi, Bo Ai, Ruisi He
Millimeter-wave (MmWave) channel characteristics are quite different from sub-6 GHz frequency bands. The major differences include higher path loss and sparser multipath components (MPCs), resulting in more significant time-varying characteristics in

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

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
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