25 citations · 97 across the 15 of their papers we have counts for
15 papers
Understanding the Dark Side of LLMs' Intrinsic Self-Correction
Qingjie Zhang, Di Wang, Haoting Qian +7
Intrinsic self-correction was proposed to improve LLMs' responses via feedback prompts solely based on their inherent capability. However, recent works show that LLMs' intrinsic se…
A General Framework for Defending Against Backdoor Attacks via Influence Graph
Xiaofei Sun, Jiwei Li, Xiaoya Li +5
In this work, we propose a new and general framework to defend against backdoor attacks, inspired by the fact that attack triggers usually follow a \textsc{specific} type of attack…
Fingerprinting Multi-exit Deep Neural Network Models via Inference Time
Tian Dong, Han Qiu, Tianwei Zhang +3
Transforming large deep neural network (DNN) models into the multi-exit architectures can overcome the overthinking issue and distribute a large DNN model on resource-constrained s…
FenceBox: A Platform for Defeating Adversarial Examples with Data Augmentation Techniques
Han Qiu, Yi Zeng, Tianwei Zhang +2
It is extensively studied that Deep Neural Networks (DNNs) are vulnerable to Adversarial Examples (AEs). With more and more advanced adversarial attack methods have been developed,…
DeepSweep: An Evaluation Framework for Mitigating DNN Backdoor Attacks using Data Augmentation
Han Qiu, Yi Zeng, Shangwei Guo +3
Public resources and services (e.g., datasets, training platforms, pre-trained models) have been widely adopted to ease the development of Deep Learning-based applications. However…
Privacy-preserving Collaborative Learning with Automatic Transformation Search
Wei Gao, Shangwei Guo, Tianwei Zhang +3
Collaborative learning has gained great popularity due to its benefit of data privacy protection: participants can jointly train a Deep Learning model without sharing their trainin…
Fine-tuning Is Not Enough: A Simple yet Effective Watermark Removal Attack for DNN Models
Shangwei Guo, Tianwei Zhang, Han Qiu +3
Watermarking has become the tendency in protecting the intellectual property of DNN models. Recent works, from the adversary's perspective, attempted to subvert watermarking mechan…
A Data Augmentation-based Defense Method Against Adversarial Attacks in Neural Networks
Yi Zeng, Han Qiu, Gerard Memmi +1
Deep Neural Networks (DNNs) in Computer Vision (CV) are well-known to be vulnerable to Adversarial Examples (AEs), namely imperceptible perturbations added maliciously to cause wro…
Mitigating Advanced Adversarial Attacks with More Advanced Gradient Obfuscation Techniques
Han Qiu, Yi Zeng, Qinkai Zheng +3
Deep Neural Networks (DNNs) are well-known to be vulnerable to Adversarial Examples (AEs). A large amount of efforts have been spent to launch and heat the arms race between the at…
Investigating Image Applications Based on Spatial-Frequency Transform and Deep Learning Techniques
Qinkai Zheng, Han Qiu, Gerard Memmi +1
This is the report for the PRIM project in Telecom Paris. This report is about applications based on spatial-frequency transform and deep learning techniques. In this report, there…
TEST: an End-to-End Network Traffic Examination and Identification Framework Based on Spatio-Temporal Features Extraction
Yi Zeng, Zihao Qi, Wencheng Chen +3
With more encrypted network traffic gets involved in the Internet, how to effectively identify network traffic has become a top priority in the field. Accurate identification of th…
Privacy-preserving Health Data Sharing for Medical Cyber-Physical Systems
Han Qiu, Meikang Qiu, Meiqin Liu +1
The recent spades of cyber security attacks have compromised end users' data safety and privacy in Medical Cyber-Physical Systems (MCPS). Traditional standard encryption algorithms…
An Efficient Data Protection Architecture Based on Fragmentation and Encryption
Han Qiu
In this thesis, a completely revisited data protection scheme based on selective encryption is presented. First, this new scheme is agnostic in term of data format, second it has a…
Learning Correlation Space for Time Series
Han Qiu, Hoang Thanh Lam, Francesco Fusco +1
We propose an approximation algorithm for efficient correlation search in time series data. In our method, we use Fourier transform and neural network to embed time series into a l…
Data Protection: Combining Fragmentation, Encryption, and Dispersion, a final report
Gerard Memmi, Katarzyna Kapusta, Patrick Lambein +1
Hardening data protection using multiple methods rather than 'just' encryption is of paramount importance when considering continuous and powerful attacks in order to observe, stea…