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Future Internet
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Information and Future Internet Security, Trust and Privacy—Volume III
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Information and Future Internet Security, Trust and Privacy—Volume III

A special issue of Future Internet (ISSN 1999-5903). This special issue belongs to the section "Cybersecurity".

Deadline for manuscript submissions: 31 December 2024 | Viewed by 3076

Special Issue Editors

Dr. Weizhi Meng

E-Mail Website
Guest Editor
Department of Applied Mathematics and Computer Science, Technical University of Denmark, 2800 Kongens Lyngby, Denmark
Interests: cyber security; intrusion detection; mobile security and authentication; HCI security; malware analysis
Special Issues, Collections and Topics in MDPI journals
Dr. Christian D. Jensen

E-Mail Website
Guest Editor
Department of Applied Mathematics and Computer Science, Technical University of Denmark, 2800 Kongens Lyngby, Denmark
Interests: security in ubiquitous computing; secure collaboration in open dynamic systems; pervasive computing environments; sensor networks and the Internet of Things (IoT)
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Currently, the Internet of things (IoT) enables billions of Internet-connected devices, e.g., smart sensors, to communicate and interact with each other over the network/Internet worldwide. IoT can offer remote monitoring and control, and is now being adopted in many domains. For example, it is the basis for smart cities, helping to achieve a better quality of life and a lower consumption of resources. In addition, smartphones are the most commonly used IoT devices, and can help control washing machines, refrigerators, or cars. However, the IoT also faces many challenges concerning information and Internet security. For example, attackers can impersonate a relay node, compromising the integrity of information during communications. When they control or infect several internal nodes in an IoT network, the security of the whole distributed environment would be greatly threatened. Therefore, there is a need to safeguard information and the Internet environment against the plethora of modern external and internal threats.

This Special Issue will focus on information and Internet security in an attempt to solicit the latest technologies, solutions, case studies, and prototypes surrounding this topic.

Dr. Weizhi Meng
Dr. Christian D. Jensen
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

  • network security
  • trust management
  • intrusion detection
  • SDN security
  • data privacy
  • internet security
  • trust aggregation
  • blockchain in security and trust
  • AI in trust
  • critical system security

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Related Special Issues

Published Papers (3 papers)

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Research

24 pages, 4648 KiB  
Article
A Micro-Segmentation Method Based on VLAN-VxLAN Mapping Technology
by Di Li, Zhibang Yang, Siyang Yu, Mingxing Duan and Shenghong Yang
Future Internet 2024, 16(9), 320; https://doi.org/10.3390/fi16090320 - 4 Sep 2024
Viewed by 550
Abstract
As information technology continues to evolve, cloud data centres have become increasingly prominent as the preferred infrastructure for data storage and processing. However, this shift has introduced a new array of security challenges, necessitating innovative approaches distinct from traditional network security architectures. In [...] Read more.
As information technology continues to evolve, cloud data centres have become increasingly prominent as the preferred infrastructure for data storage and processing. However, this shift has introduced a new array of security challenges, necessitating innovative approaches distinct from traditional network security architectures. In response, the Zero Trust Architecture (ZTA) has emerged as a promising solution, with micro-segmentation identified as a crucial component for enabling continuous auditing and stringent security controls. VxLAN technology is widely utilized in data centres for tenant isolation and virtual machine interconnection within tenant environments. Despite its prevalent use, limited research has focused on its application in micro-segmentation scenarios. To address this gap, we propose a method that leverages VLAN and VxLAN many-to-one mapping, requiring that all internal data centre traffic routes through the VxLAN gateway. This method can be implemented cost-effectively, without necessitating business modifications or causing service disruptions, thereby overcoming the challenges associated with micro-segmentation deployment. Importantly, this approach is based on standard public protocols, making it independent of specific product brands and enabling a network-centric framework that avoids software compatibility issues. To assess the effectiveness of our micro-segmentation approach, we provide a comprehensive evaluation that includes network aggregation and traffic visualization. Building on the implementation of micro-segmentation, we also introduce an enhanced asset behaviour algorithm. This algorithm constructs behavioural profiles based on the historical traffic of internal network assets, enabling the rapid identification of abnormal behaviours and facilitating timely defensive actions. Empirical results demonstrate that our algorithm is highly effective in detecting anomalous behaviour in intranet assets, making it a powerful tool for enhancing security in cloud data centres. In summary, the proposed approach offers a robust and efficient solution to the challenges of micro-segmentation in cloud data centres, contributing to the advancement of secure and reliable cloud infrastructure. Full article
(This article belongs to the Special Issue Information and Future Internet Security, Trust and Privacy—Volume III)
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16 pages, 554 KiB  
Article
Optimal Weighted Voting-Based Collaborated Malware Detection for Zero-Day Malware: A Case Study on VirusTotal and MalwareBazaar
by Naonobu Okazaki, Shotaro Usuzaki, Tsubasa Waki, Hyoga Kawagoe, Mirang Park, Hisaaki Yamaba and Kentaro Aburada
Future Internet 2024, 16(8), 259; https://doi.org/10.3390/fi16080259 - 23 Jul 2024
Viewed by 677
Abstract
We propose a detection system incorporating a weighted voting mechanism that reflects the vote’s reliability based on the accuracy of each detector’s examination, which overcomes the problem of cooperative detection. Collaborative malware detection is an effective strategy against zero-day attacks compared to one [...] Read more.
We propose a detection system incorporating a weighted voting mechanism that reflects the vote’s reliability based on the accuracy of each detector’s examination, which overcomes the problem of cooperative detection. Collaborative malware detection is an effective strategy against zero-day attacks compared to one using only a single detector because the strategy might pick up attacks that a single detector overlooked. However, cooperative detection is still ineffective if most anti-virus engines lack sufficient intelligence to detect zero-day malware. Most collaborative methods rely on majority voting, which prioritizes the quantity of votes rather than the quality of those votes. Therefore, our study investigated the zero-day malware detection accuracy of the collaborative system that optimally rates their weight of votes based on their malware categories of expertise of each anti-virus engine. We implemented the prototype system with the VirusTotal API and evaluated the system using real malware registered in MalwareBazaar. To evaluate the effectiveness of zero-day malware detection, we measured recall using the inspection results on the same day the malware was registered in the MalwareBazaar repository. Through experiments, we confirmed that the proposed system can suppress the false negatives of uniformly weighted voting and improve detection accuracy against new types of malware. Full article
(This article belongs to the Special Issue Information and Future Internet Security, Trust and Privacy—Volume III)
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19 pages, 2171 KiB  
Article
Digital Identity in the EU: Promoting eIDAS Solutions Based on Biometrics
by Pietro Ruiu, Salvatore Saiu and Enrico Grosso
Future Internet 2024, 16(7), 228; https://doi.org/10.3390/fi16070228 - 28 Jun 2024
Viewed by 1299
Abstract
Today, more than ever before, technological progress is evolving rapidly, and in the absence of adequate regulatory frameworks, the big players in the digital market (the so-called Big Techs) are exploiting personal data (name, address, telephone numbers) and private data (political opinions, religious [...] Read more.
Today, more than ever before, technological progress is evolving rapidly, and in the absence of adequate regulatory frameworks, the big players in the digital market (the so-called Big Techs) are exploiting personal data (name, address, telephone numbers) and private data (political opinions, religious beliefs, financial information, or health status) in an uncontrolled manner. A crucial role in this scenario is played by the weakness of international regulatory frameworks due to the slow response time of legislators who are incapable, from a regulatory point of view, of keeping pace with technological evolution and responding to the new requirements coming from the social context, which is increasingly characterized by the pervasive presence of new technologies, such as smartphones and wearable devices. At the European level, the General Data Protection Regulation (GDPR) and the Regulation on Electronic Identification, Authentication and Trust Services (eIDAS) have marked a significant turning point in the regulatory landscape. However, the mechanisms proposed present clear security issues, particularly in light of emerging concepts such as digital identity. Moreover, despite the centrality of biometric issues within the European regulatory framework and the practical introduction of biometric data within electronic national identity (eID) cards, there are still no efforts to use biometric features for the identification and authentication of a person in a digital context. This paper clarifies and precisely defines the potential impact of biometric-based digital identity and hypothesizes its practical use for accessing network-based services and applications commonly used in daily life. Using the Italian eID card as a model, an authentication scheme leveraging biometric data is proposed, ensuring full compliance with GDPR and eIDAS regulations. The findings suggest that such a scheme can significantly improve the security and reliability of electronic identification systems, promoting broader adoption of eIDAS solutions. Full article
(This article belongs to the Special Issue Information and Future Internet Security, Trust and Privacy—Volume III)
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