1 citations · 1 across the 12 of their papers we have counts for
12 papers
Defining Decentralization: An Ontological Perspective
Jakub Kacper Szeląg, Aydin Abadi, Mohammad Naseri
Decentralization as a concept in computer science has existed for over half a century. Despite its fundamental role across domains such as security, distributed computing, artifici…
Chained Attacks on Drone-Based Federated Learning: From Network Disruption to Device Impersonation
Suleiman Muhammad Sabo, Hamed Alkharsh, Peilin Li +4
Edge Intelligence (EI) has emerged as a transformative model for mission-critical unmanned platforms, such as drone swarms, by enabling collaborative model training at the network…
Adaptive Joint Compression and Synchronisation in Federated Split Learning for IoT Rainfall Prediction
Wenjie Ding, Yi Sin Lin, Jiale Liu +8
Federated split learning (FSL) enables collaborative training across bandwidth-constrained IoT devices, but repeated activation and gradient exchange creates a communication bot-tl…
Privacy-Preserving Federated Autoencoder for ECG Anomaly Detection on Edge Devices
Kaan Arda Akyol, Jakub Kacper Szeląg, Aydin Abadi +9
Continuous electrocardiography (ECG) monitoring could surface rhythm abnormalities before they escalate into cardiovascular events. However, a deployable system must satisfy three…
Oblivis: A Framework for Delegated and Efficient Oblivious Transfer
Aydin Abadi, Yvo Desmedt
As database deployments shift toward cloud platforms and edge devices, thin clients need to securely retrieve sensitive records without leaking their query intent or metadata to th…
Decentralized Weather Forecasting via Distributed Machine Learning and Blockchain-Based Model Validation
Rilwan Umar, Aydin Abadi, Basil Aldali +10
Weather forecasting plays a vital role in disaster preparedness, agriculture, and resource management, yet current centralized forecasting systems are increasingly strained by secu…
Impact of Data Duplication on Deep Neural Network-Based Image Classifiers: Robust vs. Standard Models
Alireza Aghabagherloo, Aydin Abadi, Sumanta Sarkar +2
The accuracy and robustness of machine learning models against adversarial attacks are significantly influenced by factors such as training data quality, model architecture, the tr…
Verifiable Homomorphic Linear Combinations in Multi-Instance Time-Lock Puzzles
Aydin Abadi
Time-Lock Puzzles (TLPs) have been developed to securely transmit sensitive information into the future without relying on a trusted third party. Multi-instance TLP is a scalable v…
Privacy-Preserving Data Deduplication for Enhancing Federated Learning of Language Models (Extended Version)
Aydin Abadi, Vishnu Asutosh Dasu, Sumanta Sarkar
Deduplication is a vital preprocessing step that enhances machine learning model performance and saves training time and energy. However, enhancing federated learning through dedup…
Delegated-Query Oblivious Transfer and its Practical Applications
Yvo Desmedt, Aydin Abadi
Databases play a pivotal role in the contemporary World Wide Web and the world of cloud computing. Unfortunately, numerous privacy violations have recently garnered attention in th…
Supersonic OT: Fast Unconditionally Secure Oblivious Transfer
Aydin Abadi, Yvo Desmedt
Oblivious Transfer (OT) is a fundamental cryptographic protocol with applications in secure Multi-Party Computation, Federated Learning, and Private Set Intersection. With the adve…
Tempora-Fusion: Time-Lock Puzzle with Efficient Verifiable Homomorphic Linear Combination
Aydin Abadi, Jakub K. Szelag
We present Tempora-Fusion, the first homomorphic TLP scheme with efficient public verification of both individual puzzle solutions and homomorphic linear combinations. Tempora-Fusi…