[HTML][HTML] A novel machine learning approach for detecting first-time-appeared malware
Conventional malware detection approaches have the overhead of feature extraction, the
requirement of domain experts, and are time-consuming and resource-intensive. Learning …
requirement of domain experts, and are time-consuming and resource-intensive. Learning …
An experimental review of the ensemble-based data stream classification algorithms in non-stationary environments
Data streams are sequences of fast-growing and high-speed data points that typically suffer
from the infinite length, large volume, and specifically unstable data distribution. Ensemble …
from the infinite length, large volume, and specifically unstable data distribution. Ensemble …
An Improved Dandelion Optimizer Algorithm for Spam Detection: Next-Generation Email Filtering System
Spam emails have become a pervasive issue in recent years, as internet users receive
increasing amounts of unwanted or fake emails. To combat this issue, automatic spam …
increasing amounts of unwanted or fake emails. To combat this issue, automatic spam …
Enhancing IoT Network Security with Concept Drift-Aware Unsupervised Threat Detection
The dynamic characteristics of Internet of Things (IoT) systems create major challenges for
threat detection systems that rely on machine learning models. Over time, shifts in the …
threat detection systems that rely on machine learning models. Over time, shifts in the …
Amodal instance segmentation with dual guidance from contextual and shape priors
J Zhan, Y Luo, C Guo, Y Wu, B Yang, J Wang… - Applied Soft Computing, 2025 - Elsevier
Human perception possesses the remarkable ability to mentally reconstruct the complete
structure of occluded objects, which has inspired researchers to pursue amodal instance …
structure of occluded objects, which has inspired researchers to pursue amodal instance …
Dynamic malware detection based on supervised contrastive learning
S Yang, Y Yang, D Zhao, L Xu, X Li, F Yu… - Computers and Electrical …, 2025 - Elsevier
Abstract Application Programming Interface (API) calls record interactions between a
program and the operating system or other programs during runtime. Due to this precise …
program and the operating system or other programs during runtime. Due to this precise …
Armed boundary sabotage: A case study of human malicious behaviors identification with computer vision and explainable reasoning methods
Nowadays, the technologies in computer vision (CV) are labor-saving and convenient to
identify human malicious behaviors. However, they usually fail to consider the robustness …
identify human malicious behaviors. However, they usually fail to consider the robustness …
SEDARU-net: a squeeze-excitation dilated based residual U-Net with attention mechanism for automatic melanoma lesion segmentation
One of the most dangerous types of skin cancer, malignant melanoma, must be detected
early on in order to receive successful therapy. If melanoma is not diagnosed in a timely …
early on in order to receive successful therapy. If melanoma is not diagnosed in a timely …
Blockchain for Artificial Intelligence (AI): enhancing compliance with the EU AI Act through distributed ledger technology. A cybersecurity perspective
The article aims to investigate the potential of blockchain technology in mitigating certain
cybersecurity risks associated with artificial intelligence (AI) systems. Aligned with ongoing …
cybersecurity risks associated with artificial intelligence (AI) systems. Aligned with ongoing …
Mitigating concept drift in data streams: an incremental decision tree approach
While recognizing the significance of data in machine learning, we focus on addressing the
challenge of concept drift, particularly in dynamic data streams. We propose an innovative …
challenge of concept drift, particularly in dynamic data streams. We propose an innovative …