20 citations · 20 across the 10 of their papers we have counts for
5 papers · 1 filter
Rethinking Generative Reconstruction Attacks against Graph Neural Network Models
Adebayo Keji, Sayanton Dibbo
The application of graph data in numerous disciplines raises the need for gathering and analyzing huge volumes of data, some of which is private and sensitive. The non-Euclidean na…
Quantum-Resilient Decentralized AI Economies: Proof-of-Useful-Work and Post-Quantum Security
Connor Barbaccia, Sudip Vhaduri, Sayanton Dibbo
Proof-of-Work blockchains secure consensus through hash puzzles, producing no external value. In this research, we propose a decentralized AI economy where nodes are rewarded for u…
The Value of Spike Timing: A Leakage-Resistant Benchmark of SNN Design Choices for Network Intrusion Detection
Raj Patel, Shaswata Mitra, David Amebley +4
Spiking neural networks (SNNs) are increasingly studied for network intrusion detection, but comparative evidence on how neuron models and spike encodings affect performance remain…
Do We Really Need Quantum Machine Learning?: A Multidimensional Empirical Study
Sudip Vhaduri, Ryan Gammon, Sayanton Dibbo
The rapid growth of computer vision and increasingly complex image recognition tasks has exposed fundamental computational limitations of classical machine learning models, motivat…
Beyond Attack Success Rate: A Multi-Metric Evaluation of Adversarial Transferability in Medical Imaging Models
Emily Curl, Kofi Ampomah, Md Erfan +1
While deep learning systems are becoming increasingly prevalent in medical image analysis, their vulnerabilities to adversarial perturbations raise serious concerns for clinical de…