[ABE-L] Call for Papers: Homomorphic Data Analysis and Machine Learning (Special Issue)

[gilson]

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/cchts
[1], using the Hot Topic Code: BMS-CUCS-2024-HT-1

  Section Editor: Gilson Antonio Giraldi

Affiliation: National Laboratory for Scientific Computing, Petropolis,
Brazil

Email: gilson em lncc.br

Guest Editors:

Luiz Antônio Pereira Neves

Affiliation: Federal University of Paraná

Email: lapneves em gmail.com

Fábio Borges de Oliveira

Affiliation: National Laboratory for Scientific Computing

Email: borges em lncc.br

Bruno Richard Schulze

Affiliation: National Laboratory for Scientific Computing

Email: schulze em lncc.br
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