2026
PriAgent: A Collaborative Multi-Agent Framework for Auditing Android Privacy Compliance
AAAI 2026technical
Stringent regulations like General Data Protection Regulation (GDPR) mandate that an application
10 accepted papers
Stringent regulations like General Data Protection Regulation (GDPR) mandate that an application
Advanced Persistent Threats (APT) differ from traditional attacks by using more complex and covert strategies for long-term assaults, posing a severe threat to organizational and national security. Due to problems like the shortage of APT traffic data and encrypted traffic obfuscation, existing meth…
Next point-of-interest (POI) recommendations have garnered significant attention in industry and academia due to their crucial role in location-based social networks (LBSNs). Recent approaches have integrated sequence and geographical data to improve recommendation accuracy. However, traditional met…
Classical classification methods often fail in dynamic environments where data distributions shift over time, known as concept drift. Applications like flight delay prediction and weather forecasting require handling such dynamic data streams. Concept drift can be either virtual, affecting unconditi…
In this paper, we propose a novel heterogeneous graph neural networks (HGNNs) model that addresses two major limitations of existing metapath-based methods: (1) Defining suitable metapaths requires professional knowledge in the special domain. (2) The neighbor nodes of the target node also play cruc…
Heterogeneous graphs are increasingly used to represent complex real-world scenarios with diverse entities and interactions by meta structures. Recently, the search of meta structures is combined with graph neural architecture search to automatically extract the semantic knowledge for various tasks…
Medical-specific Large Language Models (LLMs) have demonstrated impressive performance on medical-related exams and tasks. Despite their success in single-turn question and answering, instruction-tuned LLMs often falter in real-world healthcare applications, highlighting a disconnect between existin…
Leveraging deep learning to detect malicious network traffic is a crucial technology in network management and network security. However, deep learning security has raised concerns among scholars. In this work, we explore executing targeted adversarial attacks for multi-classification malicious traf…
Fine-tuning is becoming widely used for leveraging the power of pre-trained foundation models in new downstream tasks. While there are many successes of fine-tuning on various tasks, recent studies have observed challenges in the generalization of fine-tuned models to unseen distributions (i.e., out…
Recently link weight prediction has attracted an increasing research interest due to its merits in quantifying the strength between nodes within a graph. Nonetheless, current link weight prediction methods focus solely on graph topology, disregarding node feature information embedded in graphs. In r…