activity
20152024
most citedDeepSweep: An Evaluation Framework for Mitigating DNN Backdoor Attacks using Data Augmentation

25 citations · 97 across the 15 of their papers we have counts for

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Showing cs.CRShow all

9 papers · 1 filter

cs.CR2021★ 4 cited

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…

cs.CR2020★ 25 cited

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…

cs.CR2020★ 2 cited

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…

cs.CR2020★ 4 cited

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…

cs.CR2020★ 14 cited

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…

cs.CR2019★ 9 cited

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…

cs.CR2019★ 6 cited

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…

cs.CR2018★ 2 cited

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…

cs.CR2015★ 7 cited

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…