Hermes: Boosting the Performance of Machine-Learning-Based Intrusion Detection System through Geometric Feature Learning
Anomaly-Based Intrusion Detection Systems (IDSs) have been extensively researched for
their ability to detect zero-day attacks. These systems establish a baseline of normal …
their ability to detect zero-day attacks. These systems establish a baseline of normal …
Harvesting Private Medical Images in Federated Learning Systems with Crafted Models
Federated learning (FL) allows a set of clients to collaboratively train a machine-learning
model without exposing local training samples. In this context, it is considered to be privacy …
model without exposing local training samples. In this context, it is considered to be privacy …
Gradient Inversion of Text-Modal Data in Distributed Learning
Z Ye, W Luo, Q Zhou, Y Tang, Z Zhu… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Gradient inversion attacks (GIAs) pose significant challenges to the privacy-preserving
paradigm of distributed learning. These attacks employ carefully designed strategies to …
paradigm of distributed learning. These attacks employ carefully designed strategies to …
Partner in Crime: Boosting Targeted Poisoning Attacks against Federated Learning
Federated Learning (FL) exposes vulnerabilities to targeted poisoning attacks that aim to
cause misclassification specifically from the source class to the target class. However, using …
cause misclassification specifically from the source class to the target class. However, using …
State-of-the-Art Approaches to Enhancing Privacy Preservation of Machine Learning Datasets: A Survey
C Zhang - arXiv preprint arXiv:2404.16847, 2024 - arxiv.org
This paper examines the evolving landscape of machine learning (ML) and its profound
impact across various sectors, with a special focus on the emerging field of Privacy …
impact across various sectors, with a special focus on the emerging field of Privacy …
Reinforcement Learning-Based Approaches for Enhancing Security and Resilience in Smart Control: A Survey on Attack and Defense Methods
Z Zhang - arXiv preprint arXiv:2402.15617, 2024 - arxiv.org
Reinforcement Learning (RL), one of the core paradigms in machine learning, learns to
make decisions based on real-world experiences. This approach has significantly advanced …
make decisions based on real-world experiences. This approach has significantly advanced …
Machine Learning-Based Intrusion Detection Systems: Capabilities, Methodologies, and Open Research Challenges
Intrusion Detection Systems (IDSs) are vital for protecting computer networks against
unauthorized access and evolving cyber threats. Traditional signature-based IDSs, while …
unauthorized access and evolving cyber threats. Traditional signature-based IDSs, while …