4.6
Impact Factor
10.0
CiteScore
15 days
Submission to First Decision
4 days
Acceptance to Publication

Future Internet, Volume 17, Issue 12

2025 December - 53 articles

Cover Story: The Internet’s evolution from Web 1.0 to Web 3.0 has expanded the attack surface for cybercriminals, making malware attacks more sophisticated. The use of AI in antivirus solutions challenges traditional detection methods. Research shows that converting malware files into textured images enhances resistance to obfuscation and improves the detection of zero-day threats. This paper explores the use of image quality assessment (IQA) to enhance the curation of visual malware datasets. We propose MalScore, a no-reference IQA algorithm designed to evaluate dataset quality and guide future dataset development. Our evaluation demonstrates that MalScore effectively differentiates dataset quality, with MalNet Tiny scoring 95% and NARAD 50%, highlighting its potential for visual malware detection and the integration of IQA techniques. View this paper

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2 Citations

2,491 Views

42 Pages

Blockchain–AI–Geolocation Integrated Architecture for Mobile Identity and OTP Verification

Gajasin Gamage Damith Sulochana and
Dilshan Indraraj De Silva

Future Internet2025, 17(12), 534;https://doi.org/10.3390/fi17120534

23 November 2025

One-Time Passwords (OTPs) are a core component of multi-factor authentication in banking, e-commerce, and digital platforms. However, conventional delivery channels such as SMS and email are increasingly vulnerable to SIM-swap fraud, phishing, spoofi...

(This article belongs to the Special Issue Advances in Wireless and Mobile Networking—2nd Edition)

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1 Citations

827 Views

23 Pages

RIS-Assisted Joint Communication, Sensing, and Multi-Tier Computing Systems

Yunzhe Wang and
Minzheng Li

Future Internet2025, 17(12), 533;https://doi.org/10.3390/fi17120533

23 November 2025

This paper investigates the application of Reconfigurable Intelligent Surfaces (RIS) in Joint Communication, Sensing, and Multi-tier Computing (JCSMC). An RIS-assisted JCSMC framework is proposed, wherein a full-duplex multi-antenna Base Station (BS)...

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3 Citations

1,812 Views

25 Pages

A Resilient Deep Learning Framework for Mobile Malware Detection: From Architecture to Deployment

Aysha Alfaw,
Mohsen Rouached and
Aymen Akremi

Future Internet2025, 17(12), 532;https://doi.org/10.3390/fi17120532

21 November 2025

Mobile devices are frequent targets of malware due to the large volume of sensitive personal, financial, and corporate data they process. Traditional static, dynamic, and hybrid analysis methods are increasingly insufficient against evolving threats....

(This article belongs to the Special Issue Cybersecurity in the Age of AI, IoT, and Edge Computing)

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Future Internet - ISSN 1999-5903

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