20 citations · 20 across the 10 of their papers we have counts for
10 papers
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…
Are Neuro-Inspired Multi-Modal Vision-Language Models Resilient to Membership Inference Privacy Leakage?
David Amebley, Sayanton Dibbo
In the age of agentic AI, the growing deployment of multi-modal models (MMs) has introduced new attack vectors that can leak sensitive training data in MMs, causing privacy leakage…
Improving Robustness to Model Inversion Attacks via Sparse Coding Architectures
Sayanton V. Dibbo, Adam Breuer, Juston Moore +1
Recent model inversion attack algorithms permit adversaries to reconstruct a neural network's private and potentially sensitive training data by repeatedly querying the network. In…
LCANets++: Robust Audio Classification using Multi-layer Neural Networks with Lateral Competition
Sayanton V. Dibbo, Juston S. Moore, Garrett T. Kenyon +1
Audio classification aims at recognizing audio signals, including speech commands or sound events. However, current audio classifiers are susceptible to perturbations and adversari…
Are Your Sensitive Attributes Private? Novel Model Inversion Attribute Inference Attacks on Classification Models
Shagufta Mehnaz, Sayanton V. Dibbo, Ehsanul Kabir +2
Increasing use of machine learning (ML) technologies in privacy-sensitive domains such as medical diagnoses, lifestyle predictions, and business decisions highlights the need to be…
Opportunistic Multi-Modal User Authentication for Health-Tracking IoT Wearables
Alexa Muratyan, William Cheung, Sayanton V. Dibbo +1
With the advancement of technologies, market wearables are becoming increasingly popular with a range of services, including providing access to bank accounts, accessing cars, moni…