121 citations · 357 across the 17 of their papers we have counts for
36 papers
Privacy-Preserving Online Content Moderation: A Federated Learning Use Case
Pantelitsa Leonidou, Nicolas Kourtellis, Nikos Salamanos +1
Users are daily exposed to a large volume of harmful content on various social network platforms. One solution is developing online moderation tools using Machine Learning techniqu…
YouTubers Not madeForKids: Detecting Channels Sharing Inappropriate Videos Targeting Children
Myrsini Gkolemi, Panagiotis Papadopoulos, Evangelos P. Markatos +1
In the last years, hundreds of new Youtube channels have been creating and sharing videos targeting children, with themes related to animation, superhero movies, comics, etc. Unfor…
A deep dive into the consistently toxic 1% of Twitter
Hina Qayyum, Benjamin Zi Hao Zhao, Ian D. Wood +3
Misbehavior in online social networks (OSN) is an ever-growing phenomenon. The research to date tends to focus on the deployment of machine learning to identify and classify types…
Leveraging Google's Publisher-specific IDs to Detect Website Administration
Emmanouil Papadogiannakis, Panagiotis Papadopoulos, Evangelos P. Markatos +1
Digital advertising is the most popular way for content monetization on the Internet. Publishers spawn new websites, and older ones change hands with the sole purpose of monetizing…
PPFL: Privacy-preserving Federated Learning with Trusted Execution Environments
Fan Mo, Hamed Haddadi, Kleomenis Katevas +3
We propose and implement a Privacy-preserving Federated Learning () framework for mobile systems to limit privacy leakages in federated learning. Leveraging the widespread pr…
A First Look into the Structural Properties and Resilience of Blockchain Overlays
Aristodemos Paphitis, Nicolas Kourtellis, Michael Sirivianos
Blockchain (BC) systems are highly distributed peer-to-peer networks that offer an alternative to centralized services and promise robustness to coordinated attacks. However, the r…