29 citations · 35 across the 13 of their papers we have counts for
13 papers
PEMark: Watermarking API Responses Based on Proxy Gateways and Position Encoding
Yifei Zhou, Xianjun Gu, Xinyu Dai +2
Data leakage from API responses has drawn wide attention. APIs are often not fully regulated, making them easy to abuse. One common solution is to embed watermarks into API respons…
CLNX: Bridging Code and Natural Language for C/C++ Vulnerability-Contributing Commits Identification
Zeqing Qin, Yiwei Wu, Lansheng Han
Large Language Models (LLMs) have shown great promise in vulnerability identification. As C/C++ comprises half of the Open-Source Software (OSS) vulnerabilities over the past decad…
Research and application of artificial intelligence based webshell detection model: A literature review
Mingrui Ma, Lansheng Han, Chunjie Zhou
Webshell, as the "culprit" behind numerous network attacks, is one of the research hotspots in the field of cybersecurity. However, the complexity, stealthiness, and confusing natu…
HCL-MTSAD: Hierarchical Contrastive Consistency Learning for Accurate Detection of Industrial Multivariate Time Series Anomalies
Haili Sun, Yan Huang, Lansheng Han +2
Multivariate Time Series (MTS) anomaly detection focuses on pinpointing samples that diverge from standard operational patterns, which is crucial for ensuring the safety and securi…
Unsupervised Spatio-Temporal State Estimation for Fine-grained Adaptive Anomaly Diagnosis of Industrial Cyber-physical Systems
Haili Sun, Yan Huang, Lansheng Han +2
Accurate detection and diagnosis of abnormal behaviors such as network attacks from multivariate time series (MTS) are crucial for ensuring the stable and effective operation of in…
Research and application of Transformer based anomaly detection model: A literature review
Mingrui Ma, Lansheng Han, Chunjie Zhou
Transformer, as one of the most advanced neural network models in Natural Language Processing (NLP), exhibits diverse applications in the field of anomaly detection. To inspire res…
Large Language Models are Few-shot Generators: Proposing Hybrid Prompt Algorithm To Generate Webshell Escape Samples
Mingrui Ma, Lansheng Han, Chunjie Zhou
The frequent occurrence of cyber-attacks has made webshell attacks and defense gradually become a research hotspot in the field of network security. However, the lack of publicly a…
MTS-DVGAN: Anomaly Detection in Cyber-Physical Systems using a Dual Variational Generative Adversarial Network
Haili Sun, Yan Huang, Lansheng Han +3
Deep generative models are promising in detecting novel cyber-physical attacks, mitigating the vulnerability of Cyber-physical systems (CPSs) without relying on labeled information…
Few-shot Detection of Anomalies in Industrial Cyber-Physical System via Prototypical Network and Contrastive Learning
Haili Sun, Yan Huang, Lansheng Han +1
The rapid development of Industry 4.0 has amplified the scope and destructiveness of industrial Cyber-Physical System (CPS) by network attacks. Anomaly detection techniques are emp…
WebCrack: Dynamic Dictionary Adjustment for Web Weak Password Detection based on Blasting Response Event Discrimination
Xiang Long, Yan Huang, Zhendong Liu +3
The feature diversity of different web systems in page elements, submission contents and return information makes it difficult to detect weak password automatically. To solve this…
Neural-FacTOR: Neural Representation Learning for Website Fingerprinting Attack over TOR Anonymity
Haili Sun, Yan Huang, Lansheng Han +3
TOR (The Onion Router) network is a widely used open source anonymous communication tool, the abuse of TOR makes it difficult to monitor the proliferation of online crimes such as…
Gödel's Sentence Is An Adversarial Example But Unsolvable
Xiaodong Qi, Lansheng Han
In recent years, different types of adversarial examples from different fields have emerged endlessly, including purely natural ones without perturbations. A variety of defenses ar…
A Fixed point view: A Model-Based Clustering Framework
Jianhao Ding, Lansheng Han
With the inflation of the data, clustering analysis, as a branch of unsupervised learning, lacks unified understanding and application of its mathematical law. Based on the view of…