NIST SPECIAL PUBLICATION 1800-28 Data Confidentiality: Identifying and Protecting Assets Against Data Breaches
Attacks that target data are of concern to companies and organizations across many industries. Data breaches represent a threat that can have monetary, reputational, and legal impacts. This guide seeks to provide guidance concerning the threat of data
Application of the Hybrid Satellite Network Cybersecurity Framework Profile: An Example Implementation of NIST IR 8441
The space sector is transitioning towards Hybrid Satellite Networks (HSN), an aggregation of independently owned and operated terminals, antennas, satellites, payloads, or other components that comprise a satellite system. The elements of an HSN may have
Provenience-based cross-verification of digital forensic artifacts applied to NTFS
In digital forensics, file system analysis is a precursor task to event reconstruction. Often, unallocated content within a file system is content of interest to an investigation, and thus recognition, extraction, and ascription of unallocated files are
Implementing the Health Insurance Portability and Accountability Act (HIPAA) Security Rule A Cybersecurity Resource Guide
The HIPAA Security Rule focuses on safeguarding electronic protected health information (ePHI) held or maintained by regulated entities. The ePHI that a regulated entity creates, receives, maintains, or transmits must be protected against reasonably
Strategies for the Integration of Software Supply Chain Security in DevSecOps CI/CD Pipelines
The predominant application architecture for cloud-native applications consists of multiple microservices, accompanied in some instances by a centralized application infrastructure, such as a service mesh, that provides all application services. This class
High-Performance Computing Security Architecture, Threat Analysis, and Security Posture
Security is essential component of high-performance computing (HPC). HPC systems often differ based on the evolution of their system designs, the applications they run, and the missions they support. An HPC system may also have its own unique security
UniSpec: Deep Learning for Predicting the Full Range of Peptide Fragment Ion Series to Enhance the Proteomics Data Analysis Workflow
We present UniSpec, an attention-driven deep neural network designed to predict comprehensive collision-induced fragmentation spectra, thereby improving peptide identification in shotgun proteomics. Utilizing a training data set of 1.8 million unique high
Human-in-the-loop for Bayesian autonomous materials phase mapping
Autonomous experimentation achieves user objectives more efficiently than Edisonian studies by combining machine learning and laboratory automation to iteratively select and perform experiments. Integrating knowledge from theory, simulations, literature
Combinatorial testing for building reliable systems
Combinatorial testing is an approach where test suites are developed by efficiently covering interactions of parameter values and configuration settings. Multiple studies over the years have shown the interesting phenomenon where almost all defects in a
Informing an Artificial Intelligence risk aware culture with the NIST AI Risk Management Framework
The Artificial Intelligence Risk Management Framework (AI RMF) produced by the National Institute of Standards and Technology (NIST) is a voluntary resource for organizations to manage the risks posed by AI technologies to individuals, communities, society
This document is a Cybersecurity Framework Profile developed for voting equipment and information systems supporting elections. This Election Infrastructure Profile can be utilized by election administrators and IT professionals managing election
Use Cases for Secure and Trusted Granular Data Sharing Among Disparate Databases
Sharing data among disparate organizations can be extremely difficult, when the data comes from different database management systems (DBMS). Most problematic is that data stored at another organization most likely uses different DBMS schemas and
Comprehensively Labeled Weakness and Vulnerability Datasets via Unambiguous Formal Bugs Framework (BF) Specifications
The current state of the art in software security -- describing weaknesses as CWEs, vulnerabilities as CVEs, and labeling CVEs with CWEs -- is not keeping up with the modern cybersecurity research and application requirements for comprehensively labeled
Training in machine learning necessarily involves more operations than inference only, with higher precision, more memory, and added computational complexity. In hardware, many implementations side-step this issue by designing "inference-only" hardware