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 25, 2024

Towards Secure and Trusted-by-Design Smart Contracts
Zaynah Dargaye, Önder Gürcan, Florent Kirchner, Sara Tucci-Piergiovanni
Blockchain Based Platform Smart Contract Secure Approach Ledger Technology Evidential Transaction

January 18, 2024

A Fast, Performant, Secure Distributed Training Framework For Large Language Model
Wei Huang, Yinggui Wang, Anda Cheng, Aihui Zhou, Chaofan Yu, Lei Wang
Large Language Model System Performance Secure Approach Trusted Execution Environment Model Slicing Training Framework Domain Specific LLM

December 21, 2023

Secure Information Embedding in Images with Hybrid Firefly Algorithm
Sahil Nokhwal, Manoj Chandrasekharan, Ankit Chaudhary
Steganographic Performance Secure Approach PDF Document Steganalysis Model Firefly Algorithm

November 27, 2023

Privacy-Preserving Data Sharing in Agriculture: Enforcing Policy Rules for Secure and Confidential Data Synthesis
Anantaa Kotal, Lavanya Elluri, Deepti Gupta, Varun Mandalapu, Anupam Joshi
Agricultural Domain Data Privacy Data Sharing Secure Approach Policy Design Agricultural Data Winter Wheat Private Data Generation

November 26, 2023

Secure and Verifiable Data Collaboration with Low-Cost Zero-Knowledge Proofs
Yizheng Zhu, Yuncheng Wu, Zhaojing Luo, Beng Chin Ooi, Xiaokui Xiao
Secure Aggregation Byzantine Robust Secure Approach Zero Knowledge Data Collaboration

September 4, 2023

Secure and Efficient Federated Learning in LEO Constellations using Decentralized Key Generation and On-Orbit Model Aggregation
Mohamed Elmahallawy, Tie Luo, Mohamed I. Ibrahem
Federated Learning Secure Approach Privacy Preserving Federated Learning Satellite Data Orbit Model

August 8, 2023

Iterative Sketching for Secure Coded Regression
Neophytos Charalambides, Hessam Mahdavifar, Mert Pilanci, Alfred O. Hero
Machine Learning Novel Regression Linear Regression Secure Approach Iterative Stochastic Matrix Compression

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

Secure Approach

Papers

Towards Secure and Trusted-by-Design Smart Contracts

A Fast, Performant, Secure Distributed Training Framework For Large Language Model

Secure Information Embedding in Images with Hybrid Firefly Algorithm

Privacy-Preserving Data Sharing in Agriculture: Enforcing Policy Rules for Secure and Confidential Data Synthesis

Secure and Verifiable Data Collaboration with Low-Cost Zero-Knowledge Proofs

Secure and Efficient Federated Learning in LEO Constellations using Decentralized Key Generation and On-Orbit Model Aggregation

Iterative Sketching for Secure Coded Regression

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