Xg-nid: Dual-modality network intrusion detection using a heterogeneous graph neural network and large language model
In the rapidly evolving field of cybersecurity, the integration of flow-level and packet-level
information for real-time intrusion detection remains a largely untapped area of research …
information for real-time intrusion detection remains a largely untapped area of research …
Graph attention contrastive learning with missing modality for multimodal recommendation
W Zhao, K Yang, P Ding, C Na, W Li - Knowledge-Based Systems, 2025 - Elsevier
Multimodal recommendation plays an important role in many online content-sharing
platforms. Most existing reported approaches of multimodal recommendation employ user …
platforms. Most existing reported approaches of multimodal recommendation employ user …
A Multi-Level Network Traffic Classification in Combating Cyberattacks Using Stack Deep Learning Models
Recent advances in computing power and the growing number of threats to IT infrastructure
have increased the use of Deep Learning (DL) models in combating attacks due to their …
have increased the use of Deep Learning (DL) models in combating attacks due to their …
HyDeck: Hybrid Decider-K for IoT Intrusion Detection System
RBM Putra, LA Sanjani, CD Renggana… - 2024 9th …, 2024 - ieeexplore.ieee.org
The Internet of Things (IoT) is currently experiencing rapid growth in various sectors of
human life, leading to significant advancements in technology and convenience. However …
human life, leading to significant advancements in technology and convenience. However …
[PDF][PDF] Attack detection system based on network traffic analysis by means of fuzzy inference
N Petliak, Y Klots, V Titova, ABM Salem - 2024 - ceur-ws.org
This article presents an approach to analyzing network traffic using packet headers that
provide information about the connection between network nodes. The bulk of the traffic is …
provide information about the connection between network nodes. The bulk of the traffic is …