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20172026
most citedUnderstanding IoT Security Through the Data Crystal Ball: Where We Are Now and Where We Are Going to Be

48 citations · 69 across the 7 of their papers we have counts for

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10 papers · 1 filter

cs.CR2026

Differentially Private Paired Table-Image Multimodal Synthesis

Kai Chen, Josephine Lamp, Somesh Jha +1

Differentially private (DP) synthesis has been extensively studied for tabular and image data separately, yet many real-world datasets contain images paired with multivariate tabul…

cs.CR20211 cited

Secure Machine Learning over Relational Data

Qiyao Luo, Yilei Wang, Zhenghang Ren +3

A closer integration of machine learning and relational databases has gained steam in recent years due to the fact that the training data to many ML tasks is the results of a relat…

cs.CR20213 cited

Aegis: A Trusted, Automatic and Accurate Verification Framework for Vertical Federated Learning

Cengguang Zhang, Junxue Zhang, Di Chai +1

Vertical federated learning (VFL) leverages various privacy-preserving algorithms, e.g., homomorphic encryption or secret sharing based SecureBoost, to ensure data privacy. However…

cs.CR20202 cited

Confidential Attestation: Efficient in-Enclave Verification of Privacy Policy Compliance

Weijie Liu, Wenhao Wang, Xiaofeng Wang +9

A trusted execution environment (TEE) such as Intel Software Guard Extension (SGX) runs a remote attestation to prove to a data owner the integrity of the initial state of an encla…

cs.CR2019

Towards Security Threats of Deep Learning Systems: A Survey

Yingzhe He, Guozhu Meng, Kai Chen +2

Deep learning has gained tremendous success and great popularity in the past few years. However, deep learning systems are suffering several inherent weaknesses, which can threaten…

cs.CR2019

Interpretable Encrypted Searchable Neural Networks

Kai Chen, Zhongrui Lin, Jian Wan +1

In cloud security, traditional searchable encryption (SE) requires high computation and communication overhead for dynamic search and update. The clever combination of machine lear…