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Turning Hash-Based Signatures into Distributed Signatures and Threshold Signatures
We introduce techniques to transform existing stateful hash based signature (HBS) schemes, such as LMS [MCF19] or XMSS [HBG+18], into efficient threshold and distributed signature schemes. Our approach requires a trusted dealer for setup, and uses a large
Turning Hash-Based Signatures into Distributed Signatures and Threshold Signatures: Delegate Your Signing Capability, and Distribute it Among Trustees
Analyzing Collusion Threats in the Semiconductor Supply Chain
In this work, we propose a comprehensive framework to analyze threats related to semiconductor supply chain. The framework introduces a metric which quantifies the severity of different threats subjected to a collusion of adversaries from different stages
Analyzing Collusion Threats in the Semiconductor Supply Chain
Guidelines for API Protection for Cloud-Native Systems
Modern enterprise IT systems rely on a family of application programming interfaces (APIs) for integration to support organizational business processes. Hence, a secure deployment of APIs is critical for overall enterprise security. This, in turn, requires
Guidelines for API Protection for Cloud-Native Systems
Digital-Twin-Assisted Clustering of Radio-Frequency Multipath Components
Clustering radio-frequency (RF) multipath components (MPCs) fosters compact channel models by capturing the geometry of the scattering environment, yet "blind" methods based solely on RF data struggle to associate MPCs with individual scatterers. We
Can AI Fix Buggy Code? Exploring the Use of Large Language Models in Automated Program Repair
This article reviews the current human–large language models collaboration approach to bug fixing and points out the research directions toward (the development of) autonomous program repair artificial intelligence agents.
Can AI Fix Buggy Code? Exploring the Use of Large Language Models in Automated Program Repair
2024 NIST GenAI (Pilot Study): Text-to-Text Evaluation Overview and Results
The 2024 NIST Generative AI (GenAI) Pilot Study focuses on evaluating text-to-text (T2T) generation and discrimination tasks to assess the capabilities and limitations of generative AI models and AI detectors. The study aims to measure the effectiveness of
Hallucination Detection in Large Language Models Using Diversion Decoding
Large language models (LLMs) have emerged as a powerful tool for retrieving knowledge through seamless, human-like interactions. Despite their advanced text generation capabilities, LLMs exhibit hallucination tendencies, where they generate factually
Hallucination Detection in Large Language Models Using Diversion Decoding
Analog end-to-end adaptive training with locally-updated physical gradients on integrated photonic platform
Analysis of Propagation of Regular, Extended, and Large BGP Communities
This study focuses on the analysis of propagation of Regular, Extended, and Large Communities in the Border Gateway Protocol (BGP). Once added, these communities are often intended to be transitive by default, meaning that they should be propagated from
AI-Assisted Configuration of Reverberation Chambers for Precision RF Environments Emulation
Industrial wireless channels differ significantly from home and office channels due to factors like larger distances, existence of heavy machinery, and composition of surroundings. Industrial environments can vary significantly in their physical
5G Network Security Design Principles: Applying 5G Cybersecurity and Privacy Capabilities
Secure Software Development Framework (SSDF) Version 1.1: Recommendations for Mitigating the Risk of Software Vulnerabilities (French translation)
Few software development life cycle (SDLC) models explicitly address software security in detail, so secure software development practices usually need to be added to each SDLC model to ensure that the software being developed is well-secured. This
Secure Software Development Framework (SSDF) Version 1.1: Recommendations for Mitigating the Risk of Software Vulnerabilities (Portuguese translation)
Few software development life cycle (SDLC) models explicitly address software security in detail, so secure software development practices usually need to be added to each SDLC model to ensure that the software being developed is well-secured. This
Secure Software Development Framework (SSDF) Version 1.1: Recommendations for Mitigating the Risk of Software Vulnerabilities (Spanish translation)
Few software development life cycle (SDLC) models explicitly address software security in detail, so secure software development practices usually need to be added to each SDLC model to ensure that the software being developed is well-secured. This
Super-wideband Spectrum Sensing Using A Simplified Receiver Architecture
To achieve radio spectrum awareness for current and next generation wireless communication systems, it is critical to develop the capability of super-wideband spectrum sensing with low-cost devices. In this paper, we report a novel wideband sensing
Gradient Descent in Recurrent Neural Networks with Model-Free Multiplexed Gradient Descent: Toward Temporal On-Chip Neuromorphic Learning
The brain implements recurrent neural networks (RNNs) efficiently, and modern computing hardware does not. Although specialized neuromorphic hardware is well suited for recurrent implementations in the inference phase, it does not lend itself to the
Smart Home Users' Security and Privacy Perceptions and Actions Differ by Device Category: Results from a U.S. Survey
Explaining poisoned AI models
This work presents a hierarchical approach to explaining poisoned artificial intelligence (AI) models. The motivation comes from using AI models in security and safety-critical applications, for instance, AI models for classifying road traffic signs in
Implementing a Zero Trust Architecture: High-Level Document
A zero trust architecture (ZTA) enables secure authorized access to enterprise resources that are distributed across on-premises and multiple cloud environments, while enabling a hybrid workforce and partners to access resources from anywhere, at any time
Implementing a Zero Trust Architecture: High-Level Document
Ensuring Reliability through Combinatorial Sequence Coverage
Errors in software and hardware systems do not always result from only a single set of input values. Instead a series of input values or events often lead to failures. These sequence of events may or may not need to be contiguous. In either scenario
PRE-DRAFT Call for Comments: NIST Launches Development of Cryptographic Accordions
Exploring Prompt Patterns for Effective Vulnerability Repair in Real-World Code by Large Language Models
Large Language Models (LLMs) have shown promise in automating code vulnerability repair, but their effectiveness in handling real-world code remains limited. This paper investigates the capability of LLMs, in repairing vulnerabilities and proposes a
Metrics and Methodology for Hardware Security Constructs
Exploring Prompt Patterns for Effective Vulnerability Repair in Real-World Code by Large Language Models