6 citations · 9 across the 6 of their papers we have counts for
6 papers
Spiking Neural Networks in Vertical Federated Learning: Performance Trade-offs
Maryam Abbasihafshejani, Anindya Maiti, Murtuza Jadliwala
Federated machine learning enables model training across multiple clients while maintaining data privacy. Vertical Federated Learning (VFL) specifically deals with instances where…
An Analysis of Recent Advances in Deepfake Image Detection in an Evolving Threat Landscape
Sifat Muhammad Abdullah, Aravind Cheruvu, Shravya Kanchi +4
Deepfake or synthetic images produced using deep generative models pose serious risks to online platforms. This has triggered several research efforts to accurately detect deepfake…
Towards a Game-theoretic Understanding of Explanation-based Membership Inference Attacks
Kavita Kumari, Murtuza Jadliwala, Sumit Kumar Jha +1
Model explanations improve the transparency of black-box machine learning (ML) models and their decisions; however, they can also be exploited to carry out privacy threats such as…
Causative Insights into Open Source Software Security using Large Language Code Embeddings and Semantic Vulnerability Graph
Nafis Tanveer Islam, Gonzalo De La Torre Parra, Dylan Manual +2
Open Source Software (OSS) security and resilience are worldwide phenomena hampering economic and technological innovation. OSS vulnerabilities can cause unauthorized access, data…
TorMult: Introducing a Novel Tor Bandwidth Inflation Attack
Christoph Sendner, Jasper Stang, Alexandra Dmitrienko +2
The Tor network is the most prominent system for providing anonymous communication to web users, with a daily user base of 2 million users. However, since its inception, it has bee…
BayBFed: Bayesian Backdoor Defense for Federated Learning
Kavita Kumari, Phillip Rieger, Hossein Fereidooni +2
Federated learning (FL) allows participants to jointly train a machine learning model without sharing their private data with others. However, FL is vulnerable to poisoning attacks…