76 citations · 149 across the 18 of their papers we have counts for
18 papers
SyzTrust: State-aware Fuzzing on Trusted OS Designed for IoT Devices
Qinying Wang, Boyu Chang, Shouling Ji +8
Trusted Execution Environments (TEEs) embedded in IoT devices provide a deployable solution to secure IoT applications at the hardware level. By design, in TEEs, the Trusted Operat…
Efficient Query-Based Attack against ML-Based Android Malware Detection under Zero Knowledge Setting
Ping He, Yifan Xia, Xuhong Zhang +1
The widespread adoption of the Android operating system has made malicious Android applications an appealing target for attackers. Machine learning-based (ML-based) Android malware…
UVSCAN: Detecting Third-Party Component Usage Violations in IoT Firmware
Binbin Zhao, Shouling Ji, Xuhong Zhang +5
Nowadays, IoT devices integrate a wealth of third-party components (TPCs) in firmware to shorten the development cycle. TPCs usually have strict usage specifications, e.g., checkin…
Tram: A Token-level Retrieval-augmented Mechanism for Source Code Summarization
Tong Ye, Lingfei Wu, Tengfei Ma +5
Automatically generating human-readable text describing the functionality of a program is the intent of source code summarization. Although neural language models achieve significa…
Diff-ID: An Explainable Identity Difference Quantification Framework for DeepFake Detection
Chuer Yu, Xuhong Zhang, Yuxuan Duan +5
Despite the fact that DeepFake forgery detection algorithms have achieved impressive performance on known manipulations, they often face disastrous performance degradation when gen…
Watch Out for the Confusing Faces: Detecting Face Swapping with the Probability Distribution of Face Identification Models
Yuxuan Duan, Xuhong Zhang, Chuer Yu +3
Recently, face swapping has been developing rapidly and achieved a surprising reality, raising concerns about fake content. As a countermeasure, various detection approaches have b…
Edge Deep Learning Model Protection via Neuron Authorization
Jinyin Chen, Haibin Zheng, Tao Liu +4
With the development of deep learning processors and accelerators, deep learning models have been widely deployed on edge devices as part of the Internet of Things. Edge device mod…
MINER: A Hybrid Data-Driven Approach for REST API Fuzzing
Chenyang Lyu, Jiacheng Xu, Shouling Ji +6
In recent years, REST API fuzzing has emerged to explore errors on a cloud service. Its performance highly depends on the sequence construction and request generation. However, exi…
One Bad Apple Spoils the Barrel: Understanding the Security Risks Introduced by Third-Party Components in IoT Firmware
Binbin Zhao, Shouling Ji, Jiacheng Xu +8
Currently, the development of IoT firmware heavily depends on third-party components (TPCs) to improve development efficiency. Nevertheless, TPCs are not secure, and the vulnerabil…
HashVFL: Defending Against Data Reconstruction Attacks in Vertical Federated Learning
Pengyu Qiu, Xuhong Zhang, Shouling Ji +3
Vertical Federated Learning (VFL) is a trending collaborative machine learning model training solution. Existing industrial frameworks employ secure multi-party computation techniq…
"Is your explanation stable?": A Robustness Evaluation Framework for Feature Attribution
Yuyou Gan, Yuhao Mao, Xuhong Zhang +5
Understanding the decision process of neural networks is hard. One vital method for explanation is to attribute its decision to pivotal features. Although many algorithms are propo…
MPInspector: A Systematic and Automatic Approach for Evaluating the Security of IoT Messaging Protocols
Qinying Wang, Shouling Ji, Yuan Tian +8
Facilitated by messaging protocols (MP), many home devices are connected to the Internet, bringing convenience and accessibility to customers. However, most deployed MPs on IoT pla…
Improving Long Tailed Document-Level Relation Extraction via Easy Relation Augmentation and Contrastive Learning
Yangkai Du, Tengfei Ma, Lingfei Wu +4
Towards real-world information extraction scenario, research of relation extraction is advancing to document-level relation extraction(DocRE). Existing approaches for DocRE aim to…
Transfer Attacks Revisited: A Large-Scale Empirical Study in Real Computer Vision Settings
Yuhao Mao, Chong Fu, Saizhuo Wang +7
One intriguing property of adversarial attacks is their "transferability" -- an adversarial example crafted with respect to one deep neural network (DNN) model is often found effec…
Seeing is Living? Rethinking the Security of Facial Liveness Verification in the Deepfake Era
Changjiang Li, Li Wang, Shouling Ji +4
Facial Liveness Verification (FLV) is widely used for identity authentication in many security-sensitive domains and offered as Platform-as-a-Service (PaaS) by leading cloud vendor…
NeuronFair: Interpretable White-Box Fairness Testing through Biased Neuron Identification
Haibin Zheng, Zhiqing Chen, Tianyu Du +6
Deep neural networks (DNNs) have demonstrated their outperformance in various domains. However, it raises a social concern whether DNNs can produce reliable and fair decisions espe…
Backdoor Pre-trained Models Can Transfer to All
Lujia Shen, Shouling Ji, Xuhong Zhang +6
Pre-trained general-purpose language models have been a dominating component in enabling real-world natural language processing (NLP) applications. However, a pre-trained model wit…
Constructing Contrastive samples via Summarization for Text Classification with limited annotations
Yangkai Du, Tengfei Ma, Lingfei Wu +4
Contrastive Learning has emerged as a powerful representation learning method and facilitates various downstream tasks especially when supervised data is limited. How to construct…