Latest Articles for Data Integrity

Research develops methods to verify data integrity through agreement tests.

Learn how new techniques enhance the verification and discovery of denial constraints.

A study on resource allocation against stealthy attacks in interconnected systems.

Examining the effects of inter-dataset code duplication on model performance metrics.

Learn methods to test if missing data is random using covariance matrices.

TransTroj enhances backdoor attacks, improving effectiveness and resistance to detection.

Learn how remote attestation ensures system trust and prevents evidence tampering.

This study evaluates traditional and tree-based methods for handling missing data.

Data poisoning threatens the integrity of in-context learning systems, revealing hidden vulnerabilities.

Data contamination in language models poses serious trust issues for evaluations.

Investigating security risks and detection methods for diffusion models.

Examining the risks of data contamination in closed-source language models.

Exploring improved methods for error correction in quantum computing.

Architectural backdoors pose serious security risks in neural networks, often remaining undetected.

A look at how database resilience impacts data management and query processing.

This article reviews issues with AI watermarking and suggests improvements for security.

A novel approach reduces RowHammer risks in DRAM with low costs.

This article discusses read disturbance in DRAM and introduces a new solution.

A new method improves data cleaning while maintaining fairness in machine learning models.

ImgTrojan manipulates VLMs using deceptive training data.

New methods enhance watermarking in large language models while preserving text quality.

Discover the latest developments in error correction for modern memory technologies.

A novel approach to find backdoor samples without needing clean data.

Improving transparency is vital for credible scientific research and reliable findings.

FastFlip helps developers quickly find and analyze software errors.

A new method to protect machine learning models from malicious data attacks.

A framework combining device fingerprinting and watermarking for secure medical images.

This article presents a manipulation test for understanding treatment effects in complex settings.

A new method to confirm SQL integrity based on OCL rules.

Research highlights vulnerabilities of MNMT systems to backdoor attacks.

Exploring the role of the Bacon-Shor code in enhancing quantum error correction.

A tool simplifies database schema evolution while ensuring integrity.

A new tool aims to identify problematic studies in health research.

Introducing a framework for resilient statistical tests against outliers and weak instruments in research.

Methods to handle outliers effectively in data analysis.

DeepJSCC improves image quality in relay networks, integrating transmission with deep learning.

Discover a more effective way to handle missing data in research.

Quantum authentication provides a secure method for data verification using quantum mechanics.

Learn about locally correctable codes and their impact on error correction.

This study develops algorithms to enhance distributed systems' resistance to faulty devices.