Latest Articles for Cybersecurity

New methods aim to secure machine learning models against backdoor threats.

Examining the role of red teaming in testing AI systems for risks.

A study revealing security flaws in popular mobile payment applications.

Leveraging social media to enhance vehicle cybersecurity and mitigate emerging threats.

A study on teaching cybersecurity in computer programming courses.

Exploring the benefits of Federated Learning for anomaly detection in IoT networks.

Study reveals how 5G data patterns can expose user activity.

New models help developers, but backdoor attacks pose serious security risks.

A look at federated learning’s privacy and integrity challenges and solutions.

A new method merges LLMs with traditional disassembly techniques for effective analysis.

Tackling data contamination for better cybersecurity and anomaly detection systems.

Combining neural networks with cryptography enhances secure communication methods.

Introducing HO-FMN for better evaluation of machine learning model robustness against adversarial attacks.

Research highlights model robustness and defenses in decentralized federated learning.

New methods tackle privacy risks in human movement data prediction.

Exploring the digital shift and its impact on maritime cybersecurity.

A fresh method to compare privacy mechanisms in machine learning.

New methods improve black-box attacks using unlabeled data for machine learning.

Exploring vulnerabilities present in code generated by language models.

A novel approach to enhance security in federated learning against backdoor attacks.

Discover the role of quantum authentication in enhancing digital security.

Innovative method enhances IoT security using artificial noise and rate-splitting techniques.

Using mixed reality to enhance drone testing against data attacks.

A look into collective remote attestation and its impact on IoT device security.

New protocols enhance security and efficiency in quantum digital signatures.

A new method enhances the security of deep learning models against hidden threats.

Exploring new approaches to enhance DRAM security against Rowhammer threats.

This article discusses methods to keep agents' decision-making processes private.

A new approach to detect anomalies in IoT devices using collaborative learning.

CICAPT-IIoT aids in detecting advanced cyber threats in industrial IoT networks.

Debloating software enhances speed and security by removing unnecessary code.

This article discusses improving VLMs' resistance to adversarial attacks through design choices.

This article examines how data preparation affects machine learning in cybersecurity.

This article discusses safeguarding GNNs from data poisoning and backdoor attacks.

Analyzing effective clean-label backdoor attack techniques in machine learning.

Memory encryption offers a new way to keep cloud data safe and efficient.

Data augmentation boosts software vulnerability assessment accuracy amidst data imbalance.

A method to improve communication and efficiency in power grids.

Study reveals security risks from data poisoning in large language models.

A new method improves verification of processor security against speculative execution vulnerabilities.