Methods and systems for training a computer-based classi fication model for classifying data
are presented. The com puter-based classification model is configured to classify data into …

A generator for generating artificial data, and training for the same. Data corresponding to a
first label is altered within a reference labeled data set. A discriminator is trained based on …

An analysis engine of an anomaly detection system receives an input captured by a
monitoring device, determines, based on a currently used anomaly detection model, that the …

Embodiments relate to a system, program product, and method for automatically determining
which activation data points in a neural model have been poisoned to erroneously indicate …

One or more computer processors generate a plurality of adversarial perturbations
associated with a model, wherein the plurality of adversarial perturbations comprises a …

A system and a method of prevention and/or detection of adversarial attacks against a
classifier may include for example: using a classifier adapted to classify data elements of a …

The disclosed computer-implemented method for detecting potentially malicious content in
decentralized machine-learning model updates may include (i) receiving messages …

Embodiments relate to a system, program product, and method for processing an untrusted
data set to automatically determine which data points there are poisonous. A neural network …

Embodiments relate to a system, program product, and method for automatically determining
which activation data points in a neural model have been poisoned to erroneously indicate …

This disclosure relates generally to online learning against data poisoning attack.
Conventional methods used data sanitization techniques for online learning against data …