Latest Articles for Cybersecurity

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.

A flexible testbed enhances research in Named Data Networking for better data access.

This article discusses enhancing unsupervised anomaly detection using classification methods.

A look into privacy-preserving computation and its efficiency through memory-centric designs.

A lightweight approach improves detection of silent vulnerability fixes in open-source software.

Enhancing LLMs' ability to repair buffer overflow vulnerabilities with context-aware techniques.

SOSK helps users track and extract keywords from software security reports.

Introducing Wavelet-CLIP for improved detection of deepfake images.

Research reveals vulnerabilities in AV lane detection through negative shadows.

Innovative methods improve detection of malware through deep packet inspection.

New design improves reliability and security for IoT devices using PUF technology.

As technology advances, software security faces new challenges and opportunities.

New methods enhance security practices in interconnected industrial systems.

Examining the impact and lessons of the DarkSeoul cyberattack on South Korea.

Investigating the quality and security concerns of AI-generated code.

Discover how tensor networks enhance anomaly detection across various fields.

Learn how to protect language models from manipulation and ensure secure responses.

A comprehensive dataset for network traffic analysis and anomaly detection.

An overview of traditional and deep learning methods in network security.

Research reveals weaknesses in online toxicity detection using ASCII art techniques.

Team semantics enhances verification of complex properties in software systems.

Automated tools are crucial for verifying hardware security in modern devices.

New methods improve data usage auditing in Federated Learning systems.

A study comparing privacy threats in spiking and artificial neural networks.

A new method safeguards decentralized learning from data poisoning attacks.

A framework using MLP and SVM identifies Android malware effectively.

TrojVLM exposes vulnerabilities in Vision Language Models to backdoor attacks.

A new method to improve Federated Learning's resilience against data attacks.

A new approach enhances malware detection while resisting adversarial attacks.

New method raises security concerns in EEG systems while highlighting potential protective uses.

Examining privacy vulnerabilities in federated learning and their implications for data security.

This paper discusses a new approach to cybersecurity using Probabilistic Obstruction Temporal Logic.

Explore how new encryption standards protect our data from quantum threats.

Mammogram analysis faces risks from cyber-attacks, demanding stronger AI defenses.

Automated testing enhances security in healthcare systems, addressing evolving cyber threats.

A look into membership inference attacks and their relevance in data privacy.