Yan Huang

The Cut-and-Choose Game and Its Application to Cryptographic Protocols

2016 · USENIX Security Symposium

The cut-and-choose technique plays a fundamental role in cryptographic-protocol design, especially for secure two-party computation in the malicious model. The basic idea is that one party constructs n versions of a message in a protocol …

Generalized Pareto Model Based on Particle Swarm Optimization for Anomaly Detection

2019 · IEEE Access

Anomaly detection of time series has been widely used in various fields. Most detection methods depend either on assumptions about data distribution or manual threshold setting. If the assumption is incorrect, the effectiveness of detection …

Knowledge-aware Leap-LSTM: Integrating Prior Knowledge into Leap-LSTM towards Faster Long Text Classification

2021 · Proceedings of the AAAI Conference on Artificial Intelligence

While widely used in industry, recurrent neural networks (RNNs) are known to have deficiencies in dealing with long sequences (e.g. slow inference, vanishing gradients etc.). Recent research has attempted to accelerate RNN models by developing …

Bag of Tricks for Training Data Extraction from Language Models

2023 · arXiv (Cornell University)

With the advance of language models, privacy protection is receiving more attention. Training data extraction is therefore of great importance, as it can serve as a potential tool to assess privacy leakage. However, due to …

MLST-FENet: Network traffic classification based on multilevel spatiotemporal feature fusion enhancement

2023 · Research Square

Abstract Network traffic classification is an important task for ensuring network security and managing resources. The existing solution strategies are based on predefined features extracted by experts, which leads to high uncertainty when applied to …

A new simulation platform for learning-empowered distributed sensing

2024

Emerging communication technologies, such as millimeter-wave (mmWave) and massive antenna arrays, facilitate highly directional and long-range communication through beamforming and Multiple-Input Multiple-Output (MIMO) techniques. Recent AI advancements hold significant promise for enhancing Radio Frequency (RF) …

Graph Contrastive Learning with Adversarial Structure Refinement (GCL-ASR)

2024

The scarcity of labeled data in graph neural networks (GNNs) has driven the development of graph contrastive learning (GCL), which has become the most widely used method in unsupervised representation learning. At present, many GCL …

Research and Implementation of Personalized Smart Teaching Platform Based on Collaborative Filtering Algorithm

2024

Fast expansion of distance education in recent times availed English language learners with a considerable multitude of dynamic resources. But locating the required information from the vast ocean of available resources still remains a significant …