375 citations · 513 across the 15 of their papers we have counts for
17 papers
Username Squatting on Online Social Networks: A Study on X
Anastasios Lepipas, Anastasia Borovykh, Soteris Demetriou
Adversaries have been targeting unique identifiers to launch typo-squatting, mobile app squatting and even voice squatting attacks. Anecdotal evidence suggest that online social ne…
Data-driven initialization of deep learning solvers for Hamilton-Jacobi-Bellman PDEs
Anastasia Borovykh, Dante Kalise, Alexis Laignelet +1
A deep learning approach for the approximation of the Hamilton-Jacobi-Bellman partial differential equation (HJB PDE) associated to the Nonlinear Quadratic Regulator (NLQR) problem…
Stochastic Mirror Descent for Convex Optimization with Consensus Constraints
Anastasia Borovykh, Nikolas Kantas, Panos Parpas +1
The mirror descent algorithm is known to be effective in situations where it is beneficial to adapt the mirror map to the underlying geometry of the optimization model. However, th…
Quantifying and Localizing Usable Information Leakage from Neural Network Gradients
Fan Mo, Anastasia Borovykh, Mohammad Malekzadeh +3
In collaborative learning, clients keep their data private and communicate only the computed gradients of the deep neural network being trained on their local data. Several recent…
Honest-but-Curious Nets: Sensitive Attributes of Private Inputs Can Be Secretly Coded into the Classifiers' Outputs
Mohammad Malekzadeh, Anastasia Borovykh, Deniz Gündüz
It is known that deep neural networks, trained for the classification of non-sensitive target attributes, can reveal sensitive attributes of their input data through internal repre…
Layer-wise Characterization of Latent Information Leakage in Federated Learning
Fan Mo, Anastasia Borovykh, Mohammad Malekzadeh +2
Training deep neural networks via federated learning allows clients to share, instead of the original data, only the model trained on their data. Prior work has demonstrated that i…