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Recommendation for Stateful Hash-Based Signature Schemes
This recommendation specifies two algorithms that can be used to generate a digital signature, both of which are stateful hash-based signature schemes: the Leighton-Micali Signature (LMS) system and the eXtended Merkle Signature Scheme (XMSS), along with
Control Baselines for Information Systems and Organizations
This publication provides security and privacy control baselines for the Federal Government. There are three security control baselines (one for each system impact level: low-impact, moderate-impact, and high-impact), as well as a privacy baseline that is
Control Baselines for Information Systems and Organizations
Recommendation for Stateful Hash-Based Signature Schemes
Security Guidelines for Storage Infrastructure
Combinatorial Methods for Explainable AI
This paper introduces an approach to producing explanations or justifications of decisions made by artificial intelligence and machine learning (AI/ML) systems, using methods derived from fault location in combinatorial testing. We use a conceptually
Combinatorial Methods for Explainable AI
Prognostics and Health Management to Improve Resilient Manufacturing
Manufacturers need to be resilient to effectively mitigate substantial disruptions to manufacturing operations so they may remain competitive. Disruptions resulting from the COVID-19 global pandemic have caused manufacturers to experience new challenges
The New NIST Phish Scale, Revealing Why End Users Click
Developed based on over 4 years of NIST phishing training data, the NIST Phish Scale is a DIY method for rating human phishing detection difficulty key to understanding variability in phishing click rates. This talk will cover why users click, why its
An Empirical Study on Flow-based Botnet Attacks Prediction
In the era of the Internet of Things, botnet threats are rising, which has prompted many studies on botnet detection and measurement. In contrast, this study aims to predict botnet attacks, such as massive spam emails and distributed denial-of-service
An Empirical Study on Flow-based Botnet Attacks Prediction
Cybersecurity Profile for the Responsible Use of Positioning, Navigation, and Timing (PNT) Services
International Workshop on Deep Video Understanding
This is the introduction paper to the International Workshop on Deep Video Understanding. In recent years, a growing trend towards working on understanding videos (in particular movies) in a more deeper level started to motivate researchers working in
Implementing a Zero Trust Architecture
Roadmap on Emerging Hardware and Technology for Machine Learning: Section 12 - Superconducting Hardware for Neuromorphic Computing
Recent progress in artificial intelligence is largely attributed to the rapid development of machine learning, especially in the algorithm and neural network models. However, it is the performance of the hardware, in particular the energy efficiency of a
Augmenting Deep Learning Models for Speech Emotion Recognition
We present a Multi-Window Data Augmentation (MWA-SER) approach for speech emotion recognition. MWA-SER is a unimodal approach that focuses on two key concepts; designing the speech augmentation method and building the deep learning model to recognize the
FPGA Implementation of a Low Latency and High SFDR Direct Digital Synthesizer for Resource-Efficient Quantum-Enhanced Communication
In most modulation schemes for a telecommunication system, a fast and efficient sinusoidal signal generator is needed. Here we report on an FPGA implementation of a versatile CORDIC Based Direct Digital Synthesizer (DDS). Most commercial lightwave
Cognitive Automation and its Impact on Additive Manufacturing
The English word manufacturing firstly appeared in 1683 and it was derived from Latin manu factus, meaning making by hand. For more than thousands of years now, and four Industrial Revolutions, the physical, and mostly mechanical processes, associated with
Integrating Cybersecurity and Enterprise Risk Management (ERM)
Trojan Detection Evaluation: Finding Hidden Behavior in AI Models
Neural Networks are trained on data, learn relationships in that data, and then are deployed to the world to operate on new data. For example, a traffic sign classification AI can differentiate stop signs and speed limit signs. One potential problem is
Formal Verification of Bootstrapping Remote Secure Key Infrastructures (BRSKI) Protocol Using AVISPA
The last decade has seen significant growth in the number of IoT devices. These devices can connect to each other and networks. The process through which a new IoT device connects to the network and subsequently enables its services is called bootstrapping
Cybersecurity Framework Version 1.1 Manufacturing Profile
This document provides the Cybersecurity Framework (CSF) Version 1.1 implementation details developed for the manufacturing environment. The "Manufacturing Profile" of the CSF can be used as a roadmap for reducing cybersecurity risk for manufacturers that
Cybersecurity Framework Version 1.1 Manufacturing Profile
A Case Study of Medical Device Wireless Coexistence Evaluation
This article aims to provide a narrative for addressing wireless coexistence in medical devices to help medical device developers, test engineers, and regulatory affairs personnel throughout the device life cycle. Accordingly, we present a case-study
Security Awareness Training for the Workforce: Moving Beyond "Check-the-Box" Compliance
ISCMA: An Information Security Continuous Monitoring Program Assessment
Securing Data Integrity Against Ransomware Attacks: Using the NIST Cybersecurity Framework and NIST Cybersecurity Practice Guides
Security Awareness Training for the Workforce: Moving Beyond "Check-the-box" Compliance
Security awareness training requirements set a minimum baseline for introducing security practices to an organization's workforce. But is simple compliance enough to result in behavior change?
Blockchain Networks: Token Design and Management Overview
Adaptive Estimation of Near-Optimal Electrostatic Force in Micro Energy-Harvesters
Recent advancements in micro-electronics have led to the development of miniature-sized wearable sensors that can be used for a variety of health monitoring applications. These sensors are typically powered by small batteries which could require frequent