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Cyber Security and AI—2nd Edition
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Cyber Security and AI—2nd Edition

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".

Deadline for manuscript submissions: 31 December 2025 | Viewed by 1389

Special Issue Editors

Prof. Dr. Yushu Zhang

E-Mail Website
Guest Editor
College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
Interests: multimedia security; AI security; blockchain
Special Issues, Collections and Topics in MDPI journals
Dr. Zhongyun Hua

E-Mail Website
Guest Editor
School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen 518000, China
Interests: cyberspace security; multimedia security; chaos theory
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Cyber security is the protection of internet-connected sensor systems, such as hardware, software, and data, from cyberthreats. These cyberattacks are usually aimed at accessing, changing, or destroying sensitive information collected by sensors or interrupting normal business processes. Recently, with the fast development of artificial intelligence (AI), some classical cyber security problems in sensors have been solved. However, new technologies are gradually being used by criminals, which causes new security issues for cyberspace in sensors. The vulnerabilities of the system can be easily found, which makes the system easier to attack. When AI is applied to large-scale sensor network attacks, attackers can adaptively generate attack programs and pass a large number of automated attacks. Using AI, attackers can hide attack behaviors, attack paths, etc., making it more difficult for defenders to detect and prevent such attacks. AI technology may also be used to steal secret data from users, thereby causing more serious security problems. AI technology can be used to improve cyber security in sensors and can also cause many new security issues for cyberspace in sensors. This Special Issue of Sensors is dedicated to original research and recent developments in cyber security and AI in sensors.

This Special Issue covers all topics related to cyber security and AI.

Prof. Dr. Yushu Zhang
Dr. Zhongyun Hua
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • AI and machine learning for cybersecurity
  • adversarial attack for cybersecurity
  • generative adversarial networks for cybersecurity
  • automated and intelligent and data-driven cybersecurity model
  • AI security and neural networks
  • cloud computing security and AI
  • AI for multimedia networks security
  • security and privacy of AIGC

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Published Papers (1 paper)

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Research

21 pages, 795 KiB  
Article
LEDA—Layered Event-Based Malware Detection Architecture
by Radu Marian Portase, Raluca Laura Portase, Adrian Colesa and Gheorghe Sebestyen
Sensors 2024, 24(19), 6393; https://doi.org/10.3390/s24196393 - 2 Oct 2024
Viewed by 953
Abstract
The rapid increase in new malware necessitates effective detection methods. While machine learning techniques have shown promise for malware detection, most research focuses on identifying malware through the content of executable files or full behavior logs collected from process start to finish. However, [...] Read more.
The rapid increase in new malware necessitates effective detection methods. While machine learning techniques have shown promise for malware detection, most research focuses on identifying malware through the content of executable files or full behavior logs collected from process start to finish. However, detecting threats like ransomware via full logs is redundant, as this malware type openly informs users of the infection. To address this, we present LEDA, a novel malware detection architecture designed to monitor process behavior during execution and to identify malicious actions in real time. LEDA dynamically learns the most relevant features for detection and optimally triggers model evaluations to minimize the performance impact perceived by users. We evaluated LEDA using a dataset of Windows malware and legitimate applications collected over a year, examining our model’s temporal decay in effectiveness. Full article
(This article belongs to the Special Issue Cyber Security and AI—2nd Edition)
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