Advanced Cybersecurity, Threat Detection, and Digital Forensics for IoT Systems
A special issue of Future Internet (ISSN 1999-5903). This special issue belongs to the section "Internet of Things".
Deadline for manuscript submissions: 28 February 2027 | Viewed by 439
Special Issue Editors
Interests: cybersecurity; digital forensics; IoT security; artificial intelligence
Interests: digital forensics; cybersecurity; data cleaning; data quality
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The rapid proliferation of Internet of Things (IoT) devices has fundamentally transformed how systems collect, process, and transmit data, extending the attack surface far beyond traditional network boundaries. From smart home sensors and industrial control systems to healthcare wearables and critical infrastructure, IoT environments introduce unique security challenges: heterogeneous hardware, constrained resources, limited update mechanisms, and massive deployment scale. Securing these environments requires not only robust network-level defenses but also advanced threat detection capabilities and rigorous digital forensics frameworks that can operate effectively at the edge.
This Special Issue addresses the intersection of cybersecurity, threat detection, and digital forensics, specifically within IoT contexts. We welcome contributions that apply machine learning, deep learning, and AI-driven methods to detect, classify, and respond to threats across IoT systems. We are equally interested in forensic methodologies for evidence acquisition, log analysis, and attack reconstruction in resource-constrained and distributed environments. Topics of interest include anomaly detection, intrusion detection and prevention systems, malware analysis, adversarial attacks on IoT-integrated ML models, privacy-preserving security mechanisms, and the application of reinforcement learning and computer vision to cyber threat intelligence.
We invite researchers and practitioners to submit original research articles, reviews, and short communications that advance our collective understanding of securing the IoT ecosystem against an increasingly sophisticated and AI-accelerated threat landscape.
Dr. Khushi Gupta
Dr. Cihan Varol
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 250 words) can be sent to the Editorial Office for assessment.
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 1800 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
- IoT security and privacy
- threat detection and intrusion detection systems
- digital forensics for IoT
- machine learning for cybersecurity
- deep learning-based anomaly detection
- malware analysis and classification
- adversarial attacks on AI/ML systems
- network traffic analysis
- edge computing security
- computer vision for threat intelligence
- reinforcement learning in cybersecurity
- log analysis and attack reconstruction
- natural language processing for cyber threat intelligence
- lightweight security protocols for constrained devices
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