Special Issue

Topic: Network Security in the Era of AI: Trends, Issues, and Challenges

A Special Issue of Journal of Surveillance, Security and Safety

ISSN 2694-1015 (Online)

Submission deadline: 31 Dec 2023

Guest Editor(s)

Dr. Fei Hu
Department of Electrical and Computer Engineering, The University of Alabama, Tuscaloosa, AL, USA.
Dr. Da Yan
Department of Computer Science, The University of Alabama at Birmingham, Birmingham, AL, USA.
Dr. Yang Zhou
Department of Computer Science and Software Engineering, Samuel Ginn College of Engineering, Auburn University, Auburn, AL, USA.

Special Issue Introduction

In the past few years, more than 20 million new malware infiltrations have been recorded on computers running major brand antivirus software. In global aggregate numbers, cyber-attacks generate 10G bits per second of malicious data on enterprise and government servers -- with the nefarious goal of consuming network bandwidth and disabling the servers. At the same time, there are hundreds of millions of network-attached security cameras, Wi-Fi printers, personal computers, digital assistants, and Internet of Things (IoT) gadgets that often lack current security patches. These IoT devices can act as entry bridges for criminal states and individuals seeking access to confidential information of an organization. Consequently, all too often, this results in security breaches of important confidential data.

Given the incredible scope of the increasingly complex threat – conventional security methods are no longer sufficient to protect against today's sinister state-sponsored security threats. The solution is to employ a combination of Artificial Intelligence (AI) and Machine Learning (a subset of AI) on secure hardware designed and manufactured in the US and Europe. AI duplicates the rational human intellect at machine speed – enabling computers to rapidly identify and accurately scope the threat magnitude. AI utilizes an ML model using Artificial Neural Networks (ANNs), which use computing elements to construct a system that is modeled after the operation of neurons in the human brain. In ML, models are fed huge quantities of information, and the system then analyzes the information and optimizes processes based on new strategies and competencies utilized by an attack or malware attack.

In this Special Issue, we will publish a series of excellent ideas on the use of the latest AI models, such as deep learning (DL) and federated learning, for the detection and prevention of network attacks. The Topics could include any of the following items or unlisted ones:
● Identifying the Cyber Threats using ML models
● AI-Based Antivirus Software
● User Behavior Modeling for malicious event detection
● IoT security via federated learning
● Wireless network security based on AI
● Unmanned aerial vehicle network security
● Vehicle network security via ML/DL
● Telemedicine protection and privacy preservation via AI

All papers should be original contributions instead of previously published materials. The length of each journal paper should be between 10 and 20 pages long, with clear figures and results. All submissions will go through peer review.


Network security, artificial intelligence (AI), machine learning, security issues, privacy

Submission Deadline

31 Dec 2023

Submission Information

For Author Instructions, please refer to https://oaepublish.com/jsss/author_instructions
For Online Submission, please login at https://oaemesas.com/login?JournalId=jsss&SpecialIssueId=jsss230530
Submission Deadline: 31 Dec 2023
Contacts: Yoyo Bai, Assistant Editor, assistant-editor@jsssjournal.com

Published Articles

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Journal of Surveillance, Security and Safety
ISSN 2694-1015 (Online)
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