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Special Sessions

Special sessions are very small and specialized events to be held during the conference as a set of oral and poster presentations that are highly specialized in some particular theme or consisting of the works of some particular international project. The goal of special sessions (minimum 4 papers; maximum 9) is to provide a focused discussion on innovative topics. All accepted papers will be published in a special section of the conference proceedings book, under an ISBN reference, and on digital support. All papers presented at the conference venue will be available at the SCITEPRESS Digital Library. SCITEPRESS is a member of CrossRef and every paper is given a DOI (Digital Object Identifier). The proceedings are submitted for indexation by SCOPUS, Google Scholar, DBLP, Semantic Scholar, EI and Web of Science / Conference Proceedings Citation Index.


DMMLACS 20233rd International Special Session on Data Mining and Machine Learning Applications for Cyber Security
Chair(s): Alaa Mohasseb and Benjamin Aziz

3rd International Special Session on Data Mining and Machine Learning Applications for Cyber Security - DMMLACS 2023

Paper Submission: September 15, 2023 (expired)
Authors Notification: September 29, 2023 (expired)
Camera Ready and Registration: October 9, 2023 (expired)


Alaa Mohasseb
School of Computing, University of Portsmouth
United Kingdom
Benjamin Aziz
Creative and Digital Industries, Buckinghamshire New University
United Kingdom

The increasing amount and complexity of cybersecurity attacks in recent years have made cyber threats emerge as an important issue in companies and with the implementation of data mining and machine learning techniques it has become an important topic and factor in discovering features of such attacks and detecting future security threats. This special session aims to bring together practitioners and researchers from academia and industry to obtain insight into the current state of the practice of data mining and machine learning applications and to discuss the challenges, approaches and importance of cyber threats predictions and how using emerging technologies such as machine learning could improve the prevention of such attacks.