A survey on graph neural networks for intrusion detection systems: methods, trends and challenges

M Zhong, M Lin, C Zhang, Z Xu - Computers & Security, 2024‏ - Elsevier
Intrusion detection systems (IDS) play a crucial role in maintaining network security. With the
increasing sophistication of cyber attack methods, traditional detection approaches are …

EgoMUIL: Enhancing spatio-temporal user identity linkage in location-based social networks with Ego-Mo hypergraph

H Huang, F Ding, H Yin, G Liu… - IEEE Transactions on …, 2023‏ - ieeexplore.ieee.org
Users tend to own multiple accounts on different location-based social network (LBSN)
platforms, and they typically engage with diverse social circles on each platform within the …

Hierarchical graph neural network with cross-attention for cross-device user matching

A Taghibakhshi, M Ma, A Aithal, O Yilmaz… - … Conference on Big Data …, 2023‏ - Springer
Cross-device user matching is a critical problem in numerous domains, including
advertising, recommender systems, and cybersecurity. It involves identifying and linking …

Advancing domain decomposition methods and entity resolution with graph neural networks

A Taghibakhshi - 2023‏ - ideals.illinois.edu
Abstract Domain decomposition methods (DDMs) are popular solvers for discretized
systems of PDEs, with one-level and multilevel variants. Yet the optimal construction of these …

Multi-text Attribute Embedding for Social Network User Alignment

J Liu, J Fan, L Wang - 2024 Sixth International Conference on …, 2024‏ - ieeexplore.ieee.org
The social network has brought colorful network services to people's life, and user
association mining between different social networks has become research hotpots, which …