Split learning (SL) is a promising distributed learning framework that enables to utilize the
huge data and parallel computing resources of mobile devices. SL is built upon a model …

Disclosed is an improved method, system, and computer program product for learning
representations or embeddings of network flow traffic. The disclosed invention operates on …

A method, computer readable medium, and system are disclosed for implementing a
temporal ensembling model for training a deep neural network. The method for training the …

Computer instructions corresponding to a neural-network model are received and encrypted
using an encryption technique. Training data encrypted using the encryption technique is …

Multiple data sources encrypt data using encryption key data received from a first system; a
second system does not have access to the encryption key data. The second system …

In recent years, split learning (SL) has emerged as a promising distributed learning
framework that can utilize Big Data in parallel without privacy leakage while reducing client …

Automatic modulation classification (AMC) is a technology that identifies a modulation
scheme without prior signal information and plays a vital role in various applications …

Abstract A Convolutional Neural Network (CNN) based-signal processing includes receiving
of an encrypted output from a first layer of a multi-layer CNN data. The received encrypted …

Embodiments of the present invention provide a system and methods to mitigate poisoning
attacks within machine learning systems. The invention includes an improved data analysis …

An information processing method for embedding water mark bits into weights of a first
neural network includes: obtaining an output of a second neural network by inputting a …