76 citations · 260 across the 32 of their papers we have counts for
9 papers · 1 filter
The Impact of Data Distribution on Fairness and Robustness in Federated Learning
Mustafa Safa Ozdayi, Murat Kantarcioglu
Federated Learning (FL) is a distributed machine learning protocol that allows a set of agents to collaboratively train a model without sharing their datasets. This makes FL partic…
Multi-concept adversarial attacks
Vibha Belavadi, Yan Zhou, Murat Kantarcioglu +1
As machine learning (ML) techniques are being increasingly used in many applications, their vulnerability to adversarial attacks becomes well-known. Test time attacks, usually laun…
Learning Generative Deception Strategies in Combinatorial Masking Games
Junlin Wu, Charles Kamhoua, Murat Kantarcioglu +1
Deception is a crucial tool in the cyberdefence repertoire, enabling defenders to leverage their informational advantage to reduce the likelihood of successful attacks. One way dec…
Topological Anomaly Detection in Dynamic Multilayer Blockchain Networks
Dorcas Ofori-Boateng, Ignacio Segovia Dominguez, Murat Kantarcioglu +2
Motivated by the recent surge of criminal activities with cross-cryptocurrency trades, we introduce a new topological perspective to structural anomaly detection in dynamic multila…
Dynamically Adjusting Case Reporting Policy to Maximize Privacy and Utility in the Face of a Pandemic
J. Thomas Brown, Chao Yan, Weiyi Xia +5
Supporting public health research and the public's situational awareness during a pandemic requires continuous dissemination of infectious disease surveillance data. Legislation, s…
Fair Machine Learning under Limited Demographically Labeled Data
Mustafa Safa Ozdayi, Murat Kantarcioglu, Rishabh Iyer
Research has shown that, machine learning models might inherit and propagate undesired social biases encoded in the data. To address this problem, fair training algorithms are deve…