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01/29/2023
Gradient Shaping: Enhancing Backdoor Attack Against Reverse Engineering
Most existing methods to detect backdoored machine learning (ML) models ...
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12/09/2022
Selective Amnesia: On Efficient, High-Fidelity and Blind Suppression of Backdoor Effects in Trojaned Machine Learning Models
In this paper, we present a simple yet surprisingly effective technique ...
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10/12/2022
Understanding Impacts of Task Similarity on Backdoor Attack and Detection
With extensive studies on backdoor attack and detection, still fundament...
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09/04/2021
Understanding TEE Containers, Easy to Use? Hard to Trust
As an emerging technique for confidential computing, trusted execution e...
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07/26/2021
HySec-Flow: Privacy-Preserving Genomic Computing with SGX-based Big-Data Analytics Framework
Trusted execution environments (TEE) such as Intel's Software Guard Exte...
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07/20/2020
Confidential Attestation: Efficient in-Enclave Verification of Privacy Policy Compliance
A trusted execution environment (TEE) such as Intel Software Guard Exten...
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07/14/2020
Bounding The Number of Linear Regions in Local Area for Neural Networks with ReLU Activations
The number of linear regions is one of the distinct properties of the ne...
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03/04/2020
Towards Fair Cross-Domain Adaptation via Generative Learning
Domain Adaptation (DA) targets at adapting a model trained over the well...
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08/02/2019
Demon in the Variant: Statistical Analysis of DNNs for Robust Backdoor Contamination Detection
A security threat to deep neural networks (DNN) is backdoor contaminatio...
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05/19/2019
Toward Scalable Fully Homomorphic Encryption Through Light Trusted Computing Assistance
It has been a long standing problem to securely outsource computation ta...
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02/13/2018
Understanding Membership Inferences on Well-Generalized Learning Models
Membership Inference Attack (MIA) determines the presence of a record in...
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02/04/2018