Tags → #stories

LaZer Library Introduces Quantum-Safe Cryptographic Solutions

The LaZer Library is a tool designed to implement lattice-based zero-knowledge proofs and succinct proofs for enhancing quantum-safe privacy in cryptographic applications.
Machine Learning Model Enhances Intrusion Detection in SDN

Recent research has developed a machine-learning method for detecting infections in software-defined networking (SDN) environments, with the Gradient Boosting classifier achieving the highest accuracy and effectiveness in real-time analysis.
Malicious npm Packages Identified as Threat to Developers

Multiple malicious npm packages have been discovered, posing risks to developers by impersonating legitimate utilities and containing trojans and cryptocurrency stealers.
Malware Linked to North Korea Discovered Using Flutter Framework

Jamf Threat Labs has identified malware samples potentially linked to North Korea that utilize the Flutter framework for obfuscation, marking a notable evolution in the actor's tactics.
Microsoft Introduces New Format for Security Vulnerability Data

The Microsoft Security Response Center is enhancing transparency around security vulnerabilities by introducing the Common Security Advisory Framework, designed for automated processing, while continuing to support existing CVE data channels.
Microsoft Releases November Security Update Addressing 89 Vulnerabilities

Microsoft's November security update addresses 89 vulnerabilities, including four zero-day flaws, with a focus on remote code execution issues and recommendations for mitigating risks.
New Automated Vulnerability Detection System Introduced: LProtector

A new automated vulnerability detection system called LProtector has been introduced, designed for C/C++ codebases and leveraging advanced techniques to improve performance in identifying software vulnerabilities.
New Benchmark CTIBench Evaluates LLMs in Cyber Threat Intelligence

A new benchmark called CTIBench has been launched to assess the performance of Large Language Models in Cyber Threat Intelligence tasks through specialized datasets and various evaluation metrics.
New Defense Mechanism Eguard Enhances LLM Embedding Security

A new defense mechanism called Eguard has been proposed to enhance the security of embedding vector databases used in large language models, significantly reducing the risk of embedding inversion attacks while maintaining performance in various natural language processing tasks.
New Framework Developed for Secure Medical Data Sharing

A new framework for privacy-preserving and secure data sharing in medical image analysis has been developed, integrating advanced encryption techniques and the Vision Transformer model to enhance performance and security while complying with regulations like HIPAA and GDPR.