Adversarial Attacks and Cyber Security
A special issue of Future Internet (ISSN 1999-5903). This special issue belongs to the section "Cybersecurity".
Deadline for manuscript submissions: 30 June 2026 | Viewed by 77
Special Issue Editors
Interests: deep learning; adversarial machine learning; visualization; cybersecurity
Interests: virtual reality; multimedia security; adversarial machine learning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Cybersecurity aims to protect networks, devices, and data from unauthorized access or criminal use and ensure the confidentiality, integrity, and availability of information. With the rapid advancement of artificial intelligence, deploying machine learning (ML) technologies, especially deep learning technologies, for cybersecurity has attracted increasing attention from experts. For instance, deep neural networks are now widely used for network intrusion detection, malware detection, and spam detection. Nonetheless, researchers have shown that adversarial attacks pose practical threats to ML systems. Adversarial examples and backdoor attacks are examples of adversarial attacks against machine learning models that aim to deceive or compromise their performance. Adversarial examples are specially crafted inputs that can fool a model into making incorrect predictions, while backdoor attacks introduce hidden triggers that cause a model to misclassify certain inputs. Another adversarial threat are model stealing attacks, also known as model extraction attacks, which refer to the unauthorized copying or replication of a machine learning model. Taking into consideration these adversarial threats to cybersecurity systems, it is essential to proactively manage and mitigate risks by implementing robust cybersecurity measures.
This Special Issue aims to promote the dissemination of the latest methodologies, solutions, and case studies pertaining to adversarial attacks in cybersecurity. Our objective is to publish high‐quality articles presenting practical adversarial attacks, security algorithms, and solutions for cybersecurity measures. Technical papers describing previously unpublished, original, state‐of‐the‐art research, not currently under review by a conference or journal, will be considered.
Possible topics of interest of this Special Issue include, but are not limited to, the following:
- Adversarial examples in cybersecurity;
- Backdoor attacks in cybersecurity;
- Robust cybersecurity measures;
- Model stealing in cybersecurity;
- Intellectual property protection in cybersecurity;
- AI-powered robust cybersecurity techniques;
- Big data-driven robust cybersecurity methods, including analytics and visualization;
- Adversarial attacks against cybersecurity systems;
- Machine/deep learning methods for robust cybersecurity systems.
Dr. Wei Zong
Dr. Yang-Wai Chow
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. Future Internet is an international peer-reviewed open access monthly 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 1600 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
- cybersecurity
- artificial intelligence
- big data
- machine/deep learning
- adversarial attacks
- adversarial robustness
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