Latest Articles for Cybersecurity

An in-depth look at bribing attacks threatening blockchain systems.

Architectural backdoors pose serious security risks in neural networks, often remaining undetected.

A new method for managing database access with clarity and efficiency.

A study highlights key methods for effective anomaly detection across sectors.

New strategies allow Trojan attacks to bypass detection methods effectively.

Examining methods to lower centrality scores and reduce influence in networks.

A detailed look at CyberMetric's evaluation of AI and human experts in cybersecurity.

This article reviews a decentralized model for remote attestation that enhances security.

Quantum computing enhances secure multiparty computation by improving privacy and efficiency.

NeuroBench standardizes brainwave authentication studies for improved security techniques.

A new framework targets vulnerabilities in quantum classifiers from adversarial attacks.

A new model improves understanding of quantum communication security.

Exploring how companies approach secure software development in an evolving digital landscape.

NU-HUNCC combines innovative techniques for secure messaging against evolving threats.

A fresh approach to identify spear-phishing attacks using advanced language models.

Understanding unlearnable example attacks through game theory for better data protection.

SafeCoder improves the safety of code generated by language models.

A system designed to detect voice presentation attacks enhances security in voice recognition.

New detection method safeguards smart inverters from potential cyberattacks.

A new tool helps detect Reentrancy vulnerabilities in smart contracts more effectively.

Seagull improves routing verification while ensuring privacy for network configurations.

Examining risks and impacts of modded apps on users and developers.

A new framework targets cloud security risks with improved access control management.

Examining the adaptability of machine learning models in intrusion detection systems.

Combining Federated Learning with privacy techniques protects sensitive data while training models.

New methods in federated learning protect against attacks while maintaining data privacy.

Learn about the risks of EM-SCA and its impact on digital security.

TSTEM enhances cyber threat intelligence through automated data collection and analysis.

Study reveals language models struggle against simple text manipulations.

Learn how fuzzing can identify vulnerabilities in FPGA configurations, particularly in Xilinx devices.

This article examines privacy threats in decentralized learning methods and the tactics of potential attackers.

A benchmark tool for improving time series anomaly detection methods.

Research uncovers vulnerabilities in smartphone gait recognition technology.

A new method for intrusion detection in Wireless Sensor Networks using machine learning.

This article examines the threat of backdoor attacks on language model agents.

SPML enhances chatbot safety by monitoring user inputs and refining definitions.

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

A study reveals effective strategies for enhancing threat hunting in cybersecurity.

Examining how fine-tuning increases the risk of revealing sensitive training data.

Study examines two training methods for phishing awareness and response.