research
∙
09/14/2023
SLMIA-SR: Speaker-Level Membership Inference Attacks against Speaker Recognition Systems
Membership inference attacks allow adversaries to determine whether a pa...
share
research
∙
08/28/2023
CodeMark: Imperceptible Watermarking for Code Datasets against Neural Code Completion Models
Code datasets are of immense value for training neural-network-based cod...
research
∙
08/09/2023
An Empirical Study of Bugs in Open-Source Federated Learning Framework
Federated learning (FL), as a decentralized machine learning solution to...
research
∙
07/29/2023
An Automata-Theoretic Approach to Synthesizing Binarized Neural Networks
Deep neural networks, (DNNs, a.k.a. NNs), have been widely used in vario...
research
∙
07/02/2023
SAT-based Formal Fault-Resistance Verification of Cryptographic Circuits
Fault injection attacks represent a type of active, physical attack agai...
research
∙
05/26/2023
Automated Verification of Correctness for Masked Arithmetic Programs
Masking is a widely-used effective countermeasure against power side-cha...
research
∙
05/23/2023
QFA2SR: Query-Free Adversarial Transfer Attacks to Speaker Recognition Systems
Current adversarial attacks against speaker recognition systems (SRSs) r...
research
∙
12/10/2022
QVIP: An ILP-based Formal Verification Approach for Quantized Neural Networks
Deep learning has become a promising programming paradigm in software de...
research
∙
12/06/2022
QEBVerif: Quantization Error Bound Verification of Neural Networks
While deep neural networks (DNNs) have demonstrated impressive performan...
research
∙
09/13/2022
Learning to Prevent Profitless Neural Code Completion
Currently, large pre-trained models are widely applied in neural code co...
research
∙
07/02/2022
Abstraction and Refinement: Towards Scalable and Exact Verification of Neural Networks
As a new programming paradigm, deep neural networks (DNNs) have been inc...
research
∙
06/07/2022
Towards Understanding and Mitigating Audio Adversarial Examples for Speaker Recognition
Speaker recognition systems (SRSs) have recently been shown to be vulner...
research
∙
02/26/2022
Preventing Timing Side-Channels via Security-Aware Just-In-Time Compilation
Recent work has shown that Just-In-Time (JIT) compilation can introduce ...
research
∙
10/25/2021
CoProtector: Protect Open-Source Code against Unauthorized Training Usage with Data Poisoning
Github Copilot, trained on billions of lines of public code, has recentl...
research
∙
03/13/2021
Attack as Defense: Characterizing Adversarial Examples using Robustness
As a new programming paradigm, deep learning has expanded its applicatio...
research
∙
03/12/2021
BDD4BNN: A BDD-based Quantitative Analysis Framework for Binarized Neural Networks
Verifying and explaining the behavior of neural networks is becoming inc...
research
∙
07/16/2020
Accelerating Robustness Verification of Deep Neural Networks Guided by Target Labels
Deep Neural Networks (DNNs) have become key components of many safety-cr...
research
∙
06/16/2020
A Hybrid Approach to Formal Verification of Higher-Order Masked Arithmetic Programs
Side-channel attacks, which are capable of breaking secrecy via side-cha...
research
∙
04/15/2020
Advanced Evasion Attacks and Mitigations on Practical ML-Based Phishing Website Classifiers
Machine learning (ML) based approaches have been the mainstream solution...
research
∙
11/03/2019
Who is Real Bob? Adversarial Attacks on Speaker Recognition Systems
Speaker recognition (SR) is widely used in our daily life as a biometric...
research
∙
05/19/2019
Things You May Not Know About Adversarial Example: A Black-box Adversarial Image Attack
Numerous methods for crafting adversarial examples were proposed recentl...
research
∙
05/19/2019
Model-based Automated Testing of JavaScript Web Applications via Longer Test Sequences
JavaScript has become one of the most widely used languages for Web deve...
research
∙
01/28/2019
Quantitative Verification of Masked Arithmetic Programs against Side-Channel Attacks
Power side-channel attacks, which can deduce secret data via statistical...
research
∙
11/27/2018
Making Agents' Abilities Explicit
Alternating-time temporal logics (ATL/ATL*) represent a family of modal ...
research
∙
04/28/2018