Latest Articles for Data Integrity

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.

This method improves data tracking through advanced watermarking techniques.

A new watermarking method aids in identifying synthetic tabular data.

New methods combine linear block codes and neural networks for better data transmission.

This article explores the impact of data poisoning on language model alignment.

A new defense strategy for LLMs against backdoor attacks.

Data contamination affects the evaluation of large language models significantly.

A new method improves quantum error correction accuracy via decoder prior optimization.

This article discusses DRAM read disturbance and innovative management techniques.

This article discusses creating reliable hypothesis tests despite data corruption.

Missing data affects model performance and insights derived from machine learning.

Explore the risks and defenses in rank aggregation processes.

A look into the MiniFS file system and its security concerns.

Examining deep learning's impact on watermarking techniques and security challenges.

New methods improve the efficiency of quantum error correction in computing.

Research highlights methods to maintain dialogue consistency in restaurant-related conversations.

Quantum digital signatures ensure secure and authentic communications in our digital world.

This paper examines backdoor attacks and their implications on machine learning security.

A look at error bounds and reliable compression methods in scientific research.

Learn how error-correcting codes maintain communication reliability and data accuracy.

Learn strategies to manage incomplete data in databases effectively.

Learn about data dependencies and their importance in maintaining database integrity.

This method aims to help radio telescopes and satellites coexist without disruption.

This study investigates the vulnerability of VSS models to backdoor attacks.

A novel approach improves the effectiveness of backdoor attacks on NLP models.

New method BaDLoss enhances protection against data poisoning in machine learning.

A look into the complexities of identifying candidate keys in database design.

FIP enhances model training to prevent harmful data manipulation.

NoiseAttack alters multiple classes in backdoor attacks using subtle noise patterns.

New methods enhance digital signature security against future computing threats.

Learn how hidden triggers can manipulate language models and pose serious risks.

Learn how to obtain reliable aggregation results despite data inconsistencies.

Understanding quantum and classical noise improves the reliability of information transfer.

Exposing the manipulation risks of influence functions in machine learning.