Latest Articles for Cybersecurity

A new method improves log analysis and anomaly detection without labeled data.

A method using VAEs enhances anomaly detection in Intrusion Detection Systems.

A new framework improves IoT device security using advanced methods.

A new method combines Federated Learning and Adversarial Training for insider threat detection.

Exploring Reverse Preference Attacks and their impact on model safety.

A new AI-driven platform aims to enhance security in healthcare.

PromSec optimizes prompts for generating secure and functional code with LLMs.

Introducing PureDiffusion to enhance defense mechanisms against backdoor threats.

Examining efficient attacks on Automatic Modulation Classification using the Golden Ratio.

Research reveals how drones can be tricked into unsafe flight paths.

Proxy contracts in Ethereum offer benefits but come with significant security concerns.

This article examines a fresh approach to secure public-key encryption.

This study focuses on enhancing fraud detection methods through advanced technology.

New methods improve strategies for defending systems against attacks.

A new approach to classify malware efficiently using fewer labeled samples.

A new method uses language models for better URL safety assessment.

Examining the privacy challenges associated with Federated Learning and gradient inversion attacks.

MEGA-PT improves penetration testing effectiveness and adaptability for better cybersecurity.

A study reveals the rise of cybercrime activity on Telegram channels.

RPKI strengthens Internet routing by verifying data authenticity.

This work presents new methods for detecting malware using visualization and machine learning.

Examining firmware vulnerabilities and the tools to enhance security.

Exploring the role of Semantic Communication and security in next-gen networks.

This article examines browser fingerprinting's role in online advertising and its privacy concerns.

A new memory allocator improves security against Rowhammer attacks while maintaining performance.

Addressing security risks in generative AI through red and blue teaming.

Assessing the effectiveness of LLMs for threat analysis.

Enhancing detection methods for harmful packages in software repositories.

New methods improve actuator security in Cyber-Physical Systems to prevent attacks.

Exploring the balance between adversarial threats and proactive measures in machine learning.

Research reveals risks in smartphone motion sensors, highlighting privacy concerns.

Analyzing connections between CAPEC and ATT&CK for improved risk assessments.

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

A new approach enhances fraud detection using quantum computing and SVM models.

A study on the importance of evaluation metrics in anomaly detection.

This benchmark evaluates privacy threats and defense mechanisms in NLP models.

A look at how AI detects and analyzes online fraud.

Selective encryption enhances privacy while maintaining model performance in collaborative learning.

Introducing a framework for secure training of machine learning models.

AI technology is changing the landscape of vishing scams, increasing risks for individuals.