Secure Approach

Secure approaches in various domains are actively researched, focusing on mitigating vulnerabilities in AI models, data sharing, and distributed computing. Current efforts involve developing robust algorithms and architectures, such as federated learning, secure multi-party computation, and homomorphic encryption, to protect data privacy and model integrity while maintaining efficiency. These advancements are crucial for enabling trustworthy AI applications in sensitive areas like healthcare, finance, and cybersecurity, and for fostering secure collaboration in distributed systems.

Papers

March 24, 2023

A Survey on Secure and Private Federated Learning Using Blockchain: Theory and Application in Resource-constrained Computing
Ervin Moore, Ahmed Imteaj, Shabnam Rezapour, M. Hadi Amini
Theoretical Understanding Blockchain Based Platform Private Federated Learning Secure Approach Resource Constraint Public Blockchain

March 5, 2023

A Provably Secure Strong PUF based on LWE: Construction and Implementation
Xiaodan Xi, Ge Li, Ye Wang, Yeonsoo Jeon, Michael Orshansky
Practical Implementation Construction Industry Secure Approach Learning With Error Unclonable Function

February 20, 2023

Harris Hawks Feature Selection in Distributed Machine Learning for Secure IoT Environments
Neveen Hijazi, Moayad Aloqaily, Bassem Ouni, Fakhri Karray, Merouane Debbah
Internet of Thing Internet of Thing Device Distributed Learning Secure Approach Internet of Thing Environment Feature Combination

January 23, 2023

Learning to Linearize Deep Neural Networks for Secure and Efficient Private Inference
Souvik Kundu, Shunlin Lu, Yuke Zhang, Jacqueline Liu, Peter A. Beerel
Neural Network LeArning Abstract Deep Neural Network ReLU Layer Secure Approach Private Inference ReLU Function

January 7, 2023

IronForge: An Open, Secure, Fair, Decentralized Federated Learning
Guangsheng Yu, Xu Wang, Caijun Sun, Qin Wang, Ping Yu, Wei Ni, Ren Ping Liu, Xiwei Xu
Decentralized Federated Learning Secure Approach Fair Incentive

December 21, 2022

Secure and Privacy Preserving Proxy Biometrics Identities
Harkeerat Kaur, Rishabh Shukla, Isao Echizen, Pritee Khanna
Secure Approach Biometric Information Artificial Fingerprint

December 7, 2022

Bringing the Algorithms to the Data -- Secure Distributed Medical Analytics using the Personal Health Train (PHT-meDIC)
Marius de Arruda Botelho Herr, Michael Graf, Peter Placzek, Florian König, Felix Bötte, Tyra Stickel, David Hieber, Lukas Zimmermann, Michael Slupina, Christopher Mohr, Stephanie Biergans, Mete Akgün, Nico Pfeifer, Oliver Kohlbacher
Practical Algorithm Sensitive Data Medical Image Data Healthcare Data Secure Approach Data Analysis Data Analysis Pipeline

December 6, 2022

Pre-trained Encoders in Self-Supervised Learning Improve Secure and Privacy-preserving Supervised Learning
Hongbin Liu, Wenjie Qu, Jinyuan Jia, Neil Zhenqiang Gong
Self Supervised Learning Pre Trained Supervised Learning Encoder Side Inference Attack Secure Approach

November 13, 2022

Secure and Privacy-Preserving Automated Machine Learning Operations into End-to-End Integrated IoT-Edge-Artificial Intelligence-Blockchain Monitoring System for Diabetes Mellitus Prediction
Alain Hennebelle, Leila Ismail, Huned Materwala, Juma Al Kaabi, Priya Ranjan, Rajiv Janardhanan
Machine Learning Artificial Intelligence Secure Approach Diabetes Prediction

October 28, 2022

Secure Distributed Optimization Under Gradient Attacks
Shuhua Yu, Soummya Kar
Optimization Purpose Stochastic Gradient Secure Approach Multi Agent Network Gradient Attack Gradient Oracle

October 24, 2022

Secure and Trustworthy Artificial Intelligence-Extended Reality (AI-XR) for Metaverses
Adnan Qayyum, Muhammad Atif Butt, Hassan Ali, Muhammad Usman, Osama Halabi, Ala Al-Fuqaha, Qammer H. Abbasi, Muhammad Ali Imran, Junaid Qadir
Trustworthy Artificial Intelligence Ubiquitous Semantic Metaverse Secure Approach Metaverse Application Human Automation Trust

October 4, 2022

Beam Management in Ultra-dense mmWave Network via Federated Reinforcement Learning: An Intelligent and Secure Approach
Qing Xue, Yi-Jing Liu, Yao Sun, Jian Wang, Li Yan, Gang Feng, Shaodan Ma
mmWave Signal Federated Reinforcement Learning Secure Approach Ultra Dense Network Beam Management mmWave Network

August 21, 2022

Cluster Based Secure Multi-Party Computation in Federated Learning for Histopathology Images
S. Maryam Hosseini, Milad Sikaroudi, Morteza Babaei, H. R. Tizhoosh
Differential Privacy Histopathology Image Cluster Structure Secure Approach Private Training Secure Multiparty Computation Party Computation Patient Privacy

August 2, 2022

CAPD: A Context-Aware, Policy-Driven Framework for Secure and Resilient IoBT Operations
Sai Sree Laya Chukkapalli, Anupam Joshi, Tim Finin, Robert F. Erbacher
Top Level Ontology Multi Domain Situational Awareness Secure Approach Dexterous Policy Semantic Sensor Network

July 11, 2022

Horizontal Federated Learning and Secure Distributed Training for Recommendation System with Intel SGX
Siyuan Hui, Yuqiu Zhang, Albert Hu, Edmund Song
Deep Learning Training Data Recommendation System Secure Approach Deep Learning Recommendation Model Horizontal Federated Learning Intel Xeon

June 18, 2022

Secure Embedding Aggregation for Federated Representation Learning
Jiaxiang Tang, Jinbao Zhu, Songze Li, Lichao Sun
Jina Embeddings Private Data Data Aggregation Secure Approach Representation Learning Framework Local Embeddings Federated Representation Learning

May 11, 2022

Secure & Private Federated Neuroimaging
Dimitris Stripelis, Umang Gupta, Hamza Saleem, Nikhil Dhinagar, Tanmay Ghai, Rafael Chrysovalantis Anastasiou, Armaghan Asghar, Greg Ver Steeg, Srivatsan Ravi, Muhammad Naveed, Paul M. Thompson, Jose Luis Ambite
Private Data Secure Approach Global Deep Federated Learning Architecture

May 10, 2022

Secure and Private Source Coding with Private Key and Decoder Side Information
Onur Günlü, Rafael F. Schaefer, Holger Boche, H. Vincent Poor
Secure Approach Private Training Secret Key Source Reconstruction

April 24, 2022

Secure Approach

Papers

A Survey on Secure and Private Federated Learning Using Blockchain: Theory and Application in Resource-constrained Computing

A Provably Secure Strong PUF based on LWE: Construction and Implementation

Harris Hawks Feature Selection in Distributed Machine Learning for Secure IoT Environments

Learning to Linearize Deep Neural Networks for Secure and Efficient Private Inference

IronForge: An Open, Secure, Fair, Decentralized Federated Learning

Secure and Privacy Preserving Proxy Biometrics Identities

Bringing the Algorithms to the Data -- Secure Distributed Medical Analytics using the Personal Health Train (PHT-meDIC)

Pre-trained Encoders in Self-Supervised Learning Improve Secure and Privacy-preserving Supervised Learning

Secure and Privacy-Preserving Automated Machine Learning Operations into End-to-End Integrated IoT-Edge-Artificial Intelligence-Blockchain Monitoring System for Diabetes Mellitus Prediction

Secure Distributed Optimization Under Gradient Attacks

Secure and Trustworthy Artificial Intelligence-Extended Reality (AI-XR) for Metaverses

Beam Management in Ultra-dense mmWave Network via Federated Reinforcement Learning: An Intelligent and Secure Approach

Cluster Based Secure Multi-Party Computation in Federated Learning for Histopathology Images

CAPD: A Context-Aware, Policy-Driven Framework for Secure and Resilient IoBT Operations

Horizontal Federated Learning and Secure Distributed Training for Recommendation System with Intel SGX

Secure Embedding Aggregation for Federated Representation Learning

Secure & Private Federated Neuroimaging

Secure and Private Source Coding with Private Key and Decoder Side Information

Secure Distributed/Federated Learning: Prediction-Privacy Trade-Off for Multi-Agent System

Generalized Lagrange Coded Computing: A Flexible Computation-Communication Tradeoff for Resilient, Secure, and Private Computation