Latest Articles for Data Security

Examining key security issues related to large language models in AI.

A new framework improves recommendations while protecting user privacy.

Learn how PQC strengthens federated learning against quantum threats.

Learn how machine unlearning enhances privacy in machine learning models.

Discover methods to secure communication in distributed systems against eavesdroppers.

FreeMark enables watermarking of deep learning models without affecting performance.

A look into the risks and measures for protecting sensitive data.

This article explores how QUBO can enhance cryptographic solutions.

Oblivious data structures protect sensitive information by hiding access patterns.

Combining quantum security with machine learning improves speed and efficiency in communication.

Companies face hidden privacy threats in federated learning due to data distribution shifts.

A new method to improve deep learning models against adversarial attacks.

Combining blockchain and IPFS offers a secure and efficient solution for version control.

New architecture enhances large language model performance on edge devices.

WMCodec enhances audio watermarking for better security and authenticity.

PrivaMatch ensures privacy while matching DNA in criminal investigations.

Explore the privacy concerns surrounding membership inference attacks in machine learning.

A new approach boosts efficiency and distance in secure quantum communications.

Learn about blockchain technology and its applications in various fields.

Decentralized Social Networks empower users with data control and privacy.

Dynamical decoupling shields quantum computations from security risks.

MoJE enhances guardrails for LLMs, tackling jailbreak attacks effectively.

Exploring the potential of quantum dots in nanowires for future technologies.

Introducing TA-Cleaner, a method to improve multimodal model defenses against data poisoning.

This article presents solutions to protect user inputs in cloud-based language services.

Exploring federated learning's impact on medical data privacy and protection strategies.

Exploring Federated Learning's role in enhancing medical imaging while protecting patient privacy.

A study reveals vulnerabilities of DNA models to adversarial attacks.

Quantum systems offer a reliable method for producing unpredictable numbers.

Not all NVMe SSDs are safe; some might threaten your data.

Examining how adversarial attacks impact text and image classification models.

Investigating quantum hash functions to secure data against future threats.

Discover how a new system improves data privacy and processing speed for LLMs.

FedBlock enhances federated learning security using blockchain technology.

A deep dive into tracking insider risks in support agent workflows.

Learn how Federated Learning enhances privacy in machine learning while facing new threats.

Unlearning helps AI models forget specific information without losing critical skills.

Learn how advanced techniques protect sensitive medical images during transmission.

Randomness influences security, learning, and technology development in various fields.

AI enhances network slicing for efficient resource management and adaptation.