Artificial Intelligence in Cybersecurity (AICS) journal, proudly published by Sciences Force Publisher, stands at the forefront of cutting-edge research at the intersection of artificial intelligence and cybersecurity. AICS serves as a dedicated platform for researchers, academics, and industry professionals to explore, advance, and disseminate knowledge on the dynamic and critical nexus between artificial intelligence and the ever-evolving landscape of cybersecurity.

Editor(s)-in-Chief

Nour Moustafa

Researcher profiles: |ORCID|Scopus|

Affiliation: School of Systems & Computing, University of New South Wales at ADFA, Canberra, ACT 2612, Australia.

E-mail: nour.moustafa@ieee.org


Mohamed Abdel-Basset

Researcher profiles: |Scopus|ORCID|

Affiliation: Head of Department of Computer Science, Faculty of Computers and Informatics, Zagazig University, Egypt.

Email: mohamedbasset@ieee.org

 

 

Full Editorial Board

Vol. 1 (2024): Artificial Intelligence in Cybersecurity

Published: 01-01-2024

Hybrid Deep Learning-Based Model for Intrusion Detection

Ahmed Tolba, Nihal N. Mostafa, Karam M. Sallam (Author)

1-11

DOI: https://doi.org/10.61356/j.aics.2024.1198
DOI: https://doi.org/10.61356/j.aics.2024.1212
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Artificial Intelligence in Cybersecurity (AICS) journal, a distinguished publication proudly affiliated with Sciences Force Publisher, was established to serve the evolving landscape of artificial intelligence applied to the realm of cybersecurity. Launched in early 2024, AICS is dedicated to advancing the intersection of artificial intelligence and cybersecurity through the dissemination of high-quality scientific papers.

Aims and Scope:

AICS seeks to be a cornerstone for the latest advancements in the dynamic field of artificial intelligence in cybersecurity. We invite submissions that align with our Aims and Scope, covering a broad spectrum of topics such as machine learning for threat detection, anomaly analysis, predictive modeling, ethical considerations, and the innovative use of AI in addressing cybersecurity challenges.

Publication Frequency:

Published once time per year, AICS provides a regular and timely platform for researchers and practitioners to share their groundbreaking advancements and insights in the critical domain of artificial intelligence and cybersecurity. This periodicity ensures that our readership stays abreast of the latest developments in this rapidly evolving field.

Open Access:

As an open-access journal, AICS is committed to making valuable research freely accessible to a global audience. Our open-access policy grants readers the freedom to access, download, copy, distribute, print, search, or link to the full texts of articles without prior permission, fostering the widespread dissemination of knowledge.

Acceptance Rate and Timelines:

In its inaugural year, AICS aspires to uphold rigorous standards of quality and efficiency. Although historical acceptance rates are not yet established, our commitment is to maintain a selective acceptance rate, ensuring the publication of only high-quality research. For the year 2024, we aim for an initial editorial decision within 7 days from manuscript submission, a median time of 16 weeks from submission to acceptance, and an additional 10 days from acceptance to online publication.

These ambitious timelines are designed to streamline the publication process, enabling swift sharing of discoveries with the global scientific community. The AICS editorial team is dedicated to facilitating a seamless and efficient publication experience for contributors, building a legacy of excellence in artificial intelligence for cybersecurity research.

Archival Recognition:

Articles published in AICS will be archived and recognized by esteemed scientific archives, further emphasizing the journal's contribution to the global scientific discourse.

Publisher:

  • Publisher's Name: Sciences Force
  • Publisher's Address: Five Greentree Centre, 525 Route 73 North, STE 104, Marlton, New Jersey 08053.
  • Tel: +1 (509) 768-2249
  • Email: aics@scienceforce.com

Indexing: