相关论文: Security Hardening Using FABRIC: Implementing a Un…

Unsupervised domain adaption (UDA) has emerged as a popular solution to tackle the divergence between the labeled source and unlabeled target domains. Recently, some research efforts have been made to leverage large vision-language models,…

This paper presents an open source stochastic unit commitment (UC) optimization tool, which is available on GitHub. In addition, it presents an example use case in which UC optimization is done for a waste-to-energy plant with heat storage…

This paper discusses the relationship between two frameworks: universal composability (UC) and robust compilation (RC). In cryptography, UC is a framework for the specification and analysis of cryptographic protocols with a strong…

In vulnerability assessments, software component-based CVE attribution is a common method to identify possibly vulnerable systems at scale. However, such version-centric approaches yield high false-positive rates for binary distributed…

There are hardly any data sets publicly available that can be used to evaluate intrusion detection algorithms. The biggest threat for industrial applications arises from state-sponsored and criminal groups. Often, formerly unknown exploits…

As emerging attacks increasingly target Industrial Control Systems (ICS), the security of Programmable Logic Controllers (PLCs) has become a critical concern. Binary Code Analysis (BCA), which enables analysts to understand compiled…

Crowdsourcing systems have been used to accumulate massive amounts of labeled data for applications such as computer vision and natural language processing. However, because crowdsourced labeling is inherently dynamic and uncertain,…

As automated web accessibility testing tools become enriched with new and improved tests, it can be impractical to leverage those advances. Each tool offers unique benefits, but effectively using multiple tools would require integrating…

As the scientific community continues to push the boundaries of computing capabilities, there is a growing responsibility to address the associated energy consumption and carbon footprint. This responsibility extends to the Worldwide LHC…

In critical software engineering, structured assurance cases (ACs) are used to demonstrate how key system properties are supported by evidence (e.g., test results, proofs). Creating rigorous ACs is particularly challenging in the context of…

Static analysis plays a crucial role in software vulnerability detection, yet faces a persistent precision-scalability tradeoff. In large codebases like the Linux kernel, traditional static analysis tools often generate excessive false…

Security-constrained unit commitment (SCUC) model is used for power system day-ahead scheduling. However, current SCUC model uses a static network to deliver power and meet demand optimally. A dynamic network can provide a lower optimal…

Insecure default values in software settings can be exploited by attackers to compromise the system that runs the software. As a countermeasure, there exist security-configuration guides specifying in detail which values are secure.…

Unit tests are critical in the hardware design lifecycle to ensure that component design modules are functionally correct and conform to the specification before they are integrated at the system level. Thus developing unit tests targeting…

Learned classifiers deployed in agentic pipelines face a fundamental reliability problem: predictions are probabilistic inferences, not verified conclusions, and acting on them without grounding in observable evidence leads to compounding…

\emph{Universal Safety Controllers (USCs)} are a promising logical control framework that guarantees the satisfaction of a given temporal safety specification when applied to any realizable plant model. Unlike traditional methods, which…

The growing uncertainty from renewable power and electricity demand brings significant challenges to unit commitment (UC). While various advanced forecasting and optimization methods have been developed to predict better and address this…

Confidence calibration is essential for making large language models (LLMs) reliable, yet existing training-free methods have been primarily studied under single-answer question answering. In this paper, we show that these methods break…

This study concerns with the diagnosis of aerospace structure defects by applying a HPC parallel implementation of a novel learning algorithm, named U-BRAIN. The Soft Computing approach allows advanced multi-parameter data processing in…

Control-Flow Attestation (CFA) is a security service that allows an entity (verifier) to verify the integrity of code execution on a remote computer system (prover). Existing CFA schemes suffer from impractical assumptions, such as…