Call for Papers: Homomorphic Data Analysis and Machine Learning - Special Issue

The “Current Computer Science (CUCS) journal has posted a ‘call for papers’ regarding the special issue: “Homomorphic Data Analysis and Machine Learning”

More details in the web site: https://www.eurekaselect.com/call-for-papers-detail/6163/specialissue

The main goal of this special issue is to explore homomorphic encryption techniques for data processing and data analysis in pattern recognition tasks. It is a standard thematic issue. Hence, no page charges will be levied on the contributing authors of this thematic issue.

Potential topics include but are not limited to the following:
a) Homomorphic encryption and machine learning;
b) Deep architectures working on encrypted data;
c) Statistical data analysis for data encrypted through homomorphic schemes;
d) Homomorphic techniques for image and video processing;
e) Database systems based on homomorphic encryption schemes;
f) Topological data analysis in homomorphic encrypted databases;
g) Software engineering for data analysis based on homomorphic encryption;
h) Learning topology and manifolds for data encrypted through homomorphic techniques;
I) Federated Learning;
j) Security and Privacy for Artificial Intelligence;
k) Artificial Intelligence for Security and Privacy.

Submission Deadline: 03 December, 2024

Authors are advised to submit their manuscripts via the journal's manuscript submission portal for editorial processing and peer review by first getting themselves registered on the Manuscript Processing System (MPS) via the link:https://bentham.manuscriptpoint.com/journals/cucs, and proceed with submission using this Hot Topic Code: BMS-CUCS-2024-HT-1.

• Section Editor

Gilson Antonio Giraldi
Affiliation: National Laboratory for Scientific Computing, Petropolis, Brazil
Email: gilson@lncc.br

• Guest Editors

Luiz Antônio Pereira Neves
Affiliation: Federal University of Paraná
Email: lapneves@gmail.com

Fábio Borges de Oliveira
Affiliation: National Laboratory for Scientific Computing
Email: borges@lncc.br

Bruno Richard Schulze
Affiliation: National Laboratory for Scientific Computing
Email: schulze@lncc.br