most citedET-BERT: A Contextualized Datagram Representation with Pre-training Transformers for Encrypted Traffic Classification

550 citations · 808 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CR2022145 cited

TTAGN: Temporal Transaction Aggregation Graph Network for Ethereum Phishing Scams Detection

Sijia Li, Gaopeng Gou, Chang Liu +3

In recent years, phishing scams have become the most serious type of crime involved in Ethereum, the second-largest blockchain platform. The existing phishing scams detection techn…

cs.NI202257 cited

6GAN: IPv6 Multi-Pattern Target Generation via Generative Adversarial Nets with Reinforcement Learning

Tianyu Cui, Gaopeng Gou, Gang Xiong +3

Global IPv6 scanning has always been a challenge for researchers because of the limited network speed and computational power. Target generation algorithms are recently proposed to…

cs.NI20224 cited

A Comprehensive Study of Accelerating IPv6 Deployment

Tianyu Cui, Chang Liu, Gaopeng Gou +2

Since the lack of IPv6 network development, China is currently accelerating IPv6 deployment. In this scenario, traffic and network structure show a huge shift. However, due to the…

cs.CR20224 cited

SiamHAN: IPv6 Address Correlation Attacks on TLS Encrypted Traffic via Siamese Heterogeneous Graph Attention Network

Tianyu Cui, Gaopeng Gou, Gang Xiong +3

Unlike IPv4 addresses, which are typically masked by a NAT, IPv6 addresses could easily be correlated with user activity, endangering their privacy. Mitigations to address this pri…

cs.NI202246 cited

6GCVAE: Gated Convolutional Variational Autoencoder for IPv6 Target Generation

Tianyu Cui, Gaopeng Gou, Gang Xiong

IPv6 scanning has always been a challenge for researchers in the field of network measurement. Due to the considerable IPv6 address space, while recent network speed and computatio…

cs.CR2022550 cited

ET-BERT: A Contextualized Datagram Representation with Pre-training Transformers for Encrypted Traffic Classification

Xinjie Lin, Gang Xiong, Gaopeng Gou +3

Encrypted traffic classification requires discriminative and robust traffic representation captured from content-invisible and imbalanced traffic data for accurate classification,…