research
∙
09/06/2023
ORL-AUDITOR: Dataset Auditing in Offline Deep Reinforcement Learning
Data is a critical asset in AI, as high-quality datasets can significant...
share
research
∙
09/05/2023
Efficient Query-Based Attack against ML-Based Android Malware Detection under Zero Knowledge Setting
The widespread adoption of the Android operating system has made malicio...
research
∙
06/20/2023
UVSCAN: Detecting Third-Party Component Usage Violations in IoT Firmware
Nowadays, IoT devices integrate a wealth of third-party components (TPCs...
research
∙
05/18/2023
Tram: A Token-level Retrieval-augmented Mechanism for Source Code Summarization
Automatically generating human-readable text describing the functionalit...
research
∙
05/03/2023
On the Security Risks of Knowledge Graph Reasoning
Knowledge graph reasoning (KGR) – answering complex logical queries over...
research
∙
04/28/2023
Deep Intellectual Property: A Survey
With the widespread application in industrial manufacturing and commerci...
research
∙
04/17/2023
RNN-Guard: Certified Robustness Against Multi-frame Attacks for Recurrent Neural Networks
It is well-known that recurrent neural networks (RNNs), although widely ...
research
∙
03/30/2023
Diff-ID: An Explainable Identity Difference Quantification Framework for DeepFake Detection
Despite the fact that DeepFake forgery detection algorithms have achieve...
research
∙
03/23/2023
Watch Out for the Confusing Faces: Detecting Face Swapping with the Probability Distribution of Face Identification Models
Recently, face swapping has been developing rapidly and achieved a surpr...
research
∙
03/22/2023
Edge Deep Learning Model Protection via Neuron Authorization
With the development of deep learning processors and accelerators, deep ...
research
∙
03/05/2023
MINER: A Hybrid Data-Driven Approach for REST API Fuzzing
In recent years, REST API fuzzing has emerged to explore errors on a clo...
research
∙
02/28/2023
FreeEagle: Detecting Complex Neural Trojans in Data-Free Cases
Trojan attack on deep neural networks, also known as backdoor attack, is...
research
∙
02/12/2023
TextDefense: Adversarial Text Detection based on Word Importance Entropy
Currently, natural language processing (NLP) models are wildly used in v...
research
∙
12/29/2022
Towards Comprehensively Understanding the Run-time Security of Programmable Logic Controllers: A 3-year Empirical Study
Programmable Logic Controllers (PLCs) are the core control devices in In...
research
∙
12/28/2022
One Bad Apple Spoils the Barrel: Understanding the Security Risks Introduced by Third-Party Components in IoT Firmware
Currently, the development of IoT firmware heavily depends on third-part...
research
∙
12/01/2022
All You Need Is Hashing: Defending Against Data Reconstruction Attack in Vertical Federated Learning
Vertical federated learning is a trending solution for multi-party colla...
research
∙
12/01/2022
Hijack Vertical Federated Learning Models with Adversarial Embedding
Vertical federated learning (VFL) is an emerging paradigm that enables c...
research
∙
10/21/2022
Neural Architectural Backdoors
This paper asks the intriguing question: is it possible to exploit neura...
research
∙
10/13/2022
Demystifying Self-supervised Trojan Attacks
As an emerging machine learning paradigm, self-supervised learning (SSL)...
research
∙
09/27/2022
Reasoning over Multi-view Knowledge Graphs
Recently, knowledge representation learning (KRL) is emerging as the sta...
research
∙
09/05/2022
"Is your explanation stable?": A Robustness Evaluation Framework for Feature Attribution
Understanding the decision process of neural networks is hard. One vital...
research
∙
08/18/2022
MPInspector: A Systematic and Automatic Approach for Evaluating the Security of IoT Messaging Protocols
Facilitated by messaging protocols (MP), many home devices are connected...
research
∙
05/25/2022
VeriFi: Towards Verifiable Federated Unlearning
Federated learning (FL) is a collaborative learning paradigm where parti...
research
∙
05/21/2022
Improving Long Tailed Document-Level Relation Extraction via Easy Relation Augmentation and Contrastive Learning
Towards real-world information extraction scenario, research of relation...
research
∙
04/07/2022
Transfer Attacks Revisited: A Large-Scale Empirical Study in Real Computer Vision Settings
One intriguing property of adversarial attacks is their "transferability...
research
∙
03/13/2022
Model Inversion Attack against Transfer Learning: Inverting a Model without Accessing It
Transfer learning is an important approach that produces pre-trained tea...
research
∙
02/22/2022
Seeing is Living? Rethinking the Security of Facial Liveness Verification in the Deepfake Era
Facial Liveness Verification (FLV) is widely used for identity authentic...
research
∙
02/21/2022
GIFT: Graph-guIded Feature Transfer for Cold-Start Video Click-Through Rate Prediction
Short video has witnessed rapid growth in China and shows a promising ma...
research
∙
12/30/2021
Investigating Pose Representations and Motion Contexts Modeling for 3D Motion Prediction
Predicting human motion from historical pose sequence is crucial for a m...
research
∙
12/25/2021
NeuronFair: Interpretable White-Box Fairness Testing through Biased Neuron Identification
Deep neural networks (DNNs) have demonstrated their outperformance in va...
research
∙
12/24/2021
NIP: Neuron-level Inverse Perturbation Against Adversarial Attacks
Although deep learning models have achieved unprecedented success, their...
research
∙
12/23/2021
Adversarial Attacks against Windows PE Malware Detection: A Survey of the State-of-the-Art
The malware has been being one of the most damaging threats to computers...
research
∙
12/10/2021
Copy, Right? A Testing Framework for Copyright Protection of Deep Learning Models
Deep learning (DL) models, especially those large-scale and high-perform...
research
∙
10/27/2021
Towards Robust Reasoning over Knowledge Graphs
Answering complex logical queries over large-scale knowledge graphs (KGs...
research
∙
10/14/2021
AHEAD: Adaptive Hierarchical Decomposition for Range Query under Local Differential Privacy
For protecting users' private data, local differential privacy (LDP) has...
research
∙
10/12/2021
On the Security Risks of AutoML
Neural Architecture Search (NAS) represents an emerging machine learning...
research
∙
07/09/2021
GGT: Graph-Guided Testing for Adversarial Sample Detection of Deep Neural Network
Deep Neural Networks (DNN) are known to be vulnerable to adversarial sam...
research
∙
06/17/2021
Smart Contract Vulnerability Detection: From Pure Neural Network to Interpretable Graph Feature and Expert Pattern Fusion
Smart contracts hold digital coins worth billions of dollars, their secu...
research
∙
04/11/2021
Constructing Contrastive samples via Summarization for Text Classification with limited annotations
Contrastive Learning has emerged as a powerful representation learning m...
research
∙
04/06/2021
Fine-Grained Fashion Similarity Prediction by Attribute-Specific Embedding Learning
This paper strives to predict fine-grained fashion similarity. In this s...
research
∙
03/25/2021
EfficientTDNN: Efficient Architecture Search for Speaker Recognition in the Wild
Speaker recognition refers to audio biometrics that utilizes acoustic ch...
research
∙
03/17/2021
Aggregated Multi-GANs for Controlled 3D Human Motion Prediction
Human motion prediction from historical pose sequence is at the core of ...
research
∙
03/12/2021
Deep Dual Consecutive Network for Human Pose Estimation
Multi-frame human pose estimation in complicated situations is challengi...
research
∙
02/23/2021
Enhancing Model Robustness By Incorporating Adversarial Knowledge Into Semantic Representation
Despite that deep neural networks (DNNs) have achieved enormous success ...
research
∙
02/18/2021
Hierarchical Similarity Learning for Language-based Product Image Retrieval
This paper aims for the language-based product image retrieval task. The...
research
∙
02/02/2021
Progressive Localization Networks for Language-based Moment Localization
This paper targets the task of language-based moment localization. The l...
research
∙
01/22/2021
i-Algebra: Towards Interactive Interpretability of Deep Neural Networks
Providing explanations for deep neural networks (DNNs) is essential for ...
research
∙
12/16/2020
TROJANZOO: Everything you ever wanted to know about neural backdoors (but were afraid to ask)
Neural backdoors represent one primary threat to the security of deep le...
research
∙
11/18/2020
Privacy Leakage of Real-World Vertical Federated Learning
Federated learning enables mutually distrusting participants to collabor...
research
∙
10/25/2020
