Latest Articles for Data Security

New hybrid circuits improve secure data transmission using entangled photon pairs.

A look into QUIC's performance enhancements over traditional protocols.

AgEncID offers a new method for securing FPGA data in cloud environments.

TbDd framework improves blockchain security and efficiency for IoT applications.

Examining backdoor attacks and labeling errors in medical AI models.

Investigating resilient algorithms for testing functions amid data loss challenges.

Study reveals backdoor attack risks in GNN link prediction tasks.

Learn how machine unlearning helps protect user privacy by removing data influence.

A new approach to improve federated learning performance while ensuring data privacy.

A look at how homomorphic encryption aids gradient descent in data security.

Using diffusion models to improve detection of adversarial examples in machine learning.

A look into string constraints and their importance in software systems.

Introducing a language to enhance the security of confidential computing in the cloud.

This study introduces WAVES, a benchmark to evaluate watermarking techniques against various attacks.

Machine unlearning methods are vital for respecting data privacy rights.

This paper discusses the importance of randomness in cryptographic systems.

New method enhances neural networks against adversarial attacks using set-based inputs.

A new method for improving neural networks' resistance to attacks while maintaining performance.

Learn how interactive coding enhances secure communication between parties.

Generative AI enhances blockchain security, scalability, and privacy.

Exploring challenges and solutions for safeguarding smart grids from data attacks.

Learn about Service Level Agreements and their impact on service quality.

This work enhances machine unlearning methods for better data privacy and efficiency.

Exploring ways to enhance trustworthiness in distributed artificial intelligence technologies.

Exploring how machine unlearning aids in data privacy and compliance.

This article explores challenges faced while adopting IoT in the cold supply chain.

This study explores using response headers to identify online trackers more effectively.

A new framework improves secure computing efficiency while ensuring data privacy.

Learn how harmless perturbations protect privacy in deep learning without affecting DNN functionality.

A new model combines searchable encryption with quantum computation for better data protection.

Exploring a modern approach to secure image sharing through quantum techniques.

A method for voice conversion improving privacy and speech quality.

Understanding how to build more reliable machine learning systems against adversarial threats.

Examining privacy risks and solutions for eye tracking in virtual reality.

An inside look at developing a safe LLM application for internal documents.

Exploring the advantages of qubit communication in modern information transfer.

Exploring how optical fibres can enhance quantum communication technology.

This study reviews vulnerabilities in AI models used for genomic applications.

Introducing FOMO, a method to improve DNNs against adversarial attacks through forgetting.

Exploring the threats posed by indiscriminate data poisoning in self-supervised learning.