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Information and Future Internet Security, Trust and Privacy—3rd Edition

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

Deadline for manuscript submissions: 31 July 2025 | Viewed by 14254

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Prof. Dr. Weizhi Meng

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Guest Editor

School of Computing and Communications, Lancaster University, Lancashire LA1 4YW, UK
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

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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

Information and Future Internet Security, Trust and Privacy in Future Internet (7 articles)
Information and Future Internet Security, Trust and Privacy II in Future Internet (15 articles)

Published Papers (11 papers)

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Research

Jump to: Review

27 pages, 960 KiB

Open AccessArticle

Ephemeral Node Identifiers for Enhanced Flow Privacy

by Gregor Tamati Haywood and Saleem Noel Bhatti

Future Internet 2025, 17(5), 196; https://doi.org/10.3390/fi17050196 - 28 Apr 2025

Viewed by 24

Abstract

The Internet Protocol (IP) uses numerical address values carried in IP packets at the network layer to allow correct forwarding of packets between source and destination. Those address values must be kept visible in all parts of the network. By definition, those addresses must carry enough information to identify the source and destination for the communication. This means that successive flows of IP packets can be correlated—it is possible for an observer of the flows to easily link them to an individual source and so, potentially, to an individual user. To alleviate this privacy concern, it is desirable to have ephemeral address values—values that have a limited lifespan and so make flow correlation more difficult for an attacker. However, the IP address is also used in the end-to-end communication state for transport layer flows so must remain consistent to allow correct operation at the transport layer. We present a solution to this tension in requirements by the use of ephemeral Node Identifier (eNID) values in IP packets as part of the address value. We have implemented our approach as an extension to IPv6 in the FreeBSD14 operating system kernel. We have evaluated the implementation with existing applications over both a testbed network in a controlled environment, as well as with global IPv6 network connectivity. Our results show that eNIDs work with existing applications and over existing IPv6 networks. Our analyses shows that using eNIDs creates a disruption to the correlation of flows and so effectively perturbs linkability. As our approach is a network layer (layer 3) mechanism, it is usable by any transport layer (layer 4) protocol, improving privacy for all applications and all users. Full article

(This article belongs to the Special Issue Information and Future Internet Security, Trust and Privacy—3rd Edition)

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27 pages, 4252 KiB

Open AccessArticle

Facial Privacy Protection with Dynamic Multi-User Access Control for Online Photo Platforms

by Andri Santoso, Samsul Huda, Yuta Kodera and Yasuyuki Nogami

Future Internet 2025, 17(3), 124; https://doi.org/10.3390/fi17030124 - 11 Mar 2025

Viewed by 532

Abstract

In the digital age, sharing moments through photos has become a daily habit. However, every face captured in these photos is vulnerable to unauthorized identification and potential misuse through AI-powered synthetic content generation. Previously, we introduced SnapSafe, a secure system for enabling selective image privacy focusing on facial regions for single-party scenarios. Recognizing that group photos with multiple subjects are a more common scenario, we extend SnapSafe to support multi-user facial privacy protection with dynamic access control designed for online photo platforms. Our approach introduces key splitting for access control, an owner-centric permission system for granting and revoking access to facial regions, and a request-based mechanism allowing subjects to initiate access permissions. These features ensure that facial regions remain protected while maintaining the visibility of non-facial content for general viewing. To ensure reproducibility and isolation, we implemented our solution using Docker containers. Our experimental assessment covered diverse scenarios, categorized as “Single”, “Small”, “Medium”, and “Large”, based on the number of faces in the photos. The results demonstrate the system’s effectiveness across all test scenarios, consistently performing face encryption operations in under 350 ms and achieving average face decryption times below 286 ms across various group sizes. The key-splitting operations maintained a

100 %

success rate across all group configurations, while revocation operations were executed efficiently with server processing times remaining under 16 ms. These results validate the system’s capability in managing facial privacy while maintaining practical usability in online photo sharing contexts. Full article

(This article belongs to the Special Issue Information and Future Internet Security, Trust and Privacy—3rd Edition)

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15 pages, 1933 KiB

Open AccessArticle

Assessing Browser Security: A Detailed Study Based on CVE Metrics

by Oleksii Chalyi, Kęstutis Driaunys and Vytautas Rudžionis

Future Internet 2025, 17(3), 104; https://doi.org/10.3390/fi17030104 - 25 Feb 2025

Viewed by 835

Abstract

This study systematically evaluates the vulnerabilities of modern web browsers using developed indices derived from the CVE database, including I_CVE, I_CVSS, I_R and I_T. These indices incorporate metrics such as vulnerability severity and risks, along with browser popularity, to enable a balanced comparison of browser security. The results highlight significant differences in browser security: while Google Chrome and Samsung Internet exhibited lower threat indices, Mozilla Firefox demonstrated consistently higher scores, indicating greater exposure to risks. These observations a slightly contradict widespread opinion. The findings emphasize the importance of timely software updates in mitigating vulnerabilities, as many incidents were linked to outdated browser versions. This study also introduces a robust methodology for assessing browser threats, providing a framework for future research. Potential applications include developing browser-based penetration testing systems to simulate phishing and data extraction scenarios, offering insights into user-specific risks and broader organizational impacts. By combining theoretical analysis with practical implications, this work contributes to advancing browser security and lays the foundation for future applied research in cybersecurity. Full article

(This article belongs to the Special Issue Information and Future Internet Security, Trust and Privacy—3rd Edition)

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20 pages, 812 KiB

Open AccessArticle

End-to-End Framework for Identifying Vulnerabilities of Operational Technology Protocols and Their Implementations in Industrial IoT

by Matthew Boeding, Michael Hempel and Hamid Sharif

Future Internet 2025, 17(1), 34; https://doi.org/10.3390/fi17010034 - 14 Jan 2025

Viewed by 835

Abstract

The convergence of IT and OT networks has gained significant attention in recent years, facilitated by the increase in distributed computing capabilities, the widespread deployment of Internet of Things devices, and the adoption of Industrial Internet of Things. This convergence has led to a drastic increase in external access capabilities to previously air-gapped industrial systems for process control and monitoring. To meet the need for remote access to system information, protocols designed for the OT space were extended to allow IT networked communications. However, OT protocols often lack the rigor of cybersecurity capabilities that have become a critical characteristic of IT protocols. Furthermore, OT protocol implementations on individual devices can vary in performance, requiring the comprehensive evaluation of a device’s reliability and capabilities before installation into a critical infrastructure production network. In this paper, the authors define a framework for identifying vulnerabilities within these protocols and their on-device implementations, utilizing formal modeling, hardware in the loop-driven network emulation, and fully virtual network scenario simulation. Initially, protocol specifications are modeled to identify any vulnerable states within the protocol, leveraging the Construction and Analysis of Distributed Processes (CADP) software (version 2022-d “Kista”, which was created by Inria, the French Institute for Research in Computer Science and Automation, in France). Device characteristics are then extracted through automated real-time network emulation tests built on the OMNET++ framework, and all measured device characteristics are then used as a virtual device representation for network simulation tests within the OMNET++ software (version 6.0.1., a public-soucre, open-architecture software, initially developed by OpenSim Limited in Budapest, Hungary), to verify the presence of any potential vulnerabilities identified in the formal modeling stage. With this framework, the authors have thus defined an end-to-end process to identify and verify the presence and impact of potential vulnerabilities within a protocol, as shown by the presented results. Furthermore, this framework can test protocol compliance, performance, and security in a controlled environment before deploying devices in live production networks and addressing cybersecurity concerns. Full article

(This article belongs to the Special Issue Information and Future Internet Security, Trust and Privacy—3rd Edition)

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19 pages, 1456 KiB

Open AccessArticle

Ventinel: Automated Detection of Android Vishing Apps Using Optical Character Recognition

by Daegyeom Kim, Sehwan O, Younghoon Ban, Jungsoo Park, Kyungho Joo and Haehyun Cho

Future Internet 2025, 17(1), 24; https://doi.org/10.3390/fi17010024 - 7 Jan 2025

Viewed by 943

Abstract

Vishing, a blend of “voice” and “phishing”, has evolved to include techniques like Call Redirection and Display Overlay Attacks, causing significant financial losses. Existing research has largely focused on user behavior and awareness, leaving gaps in addressing attacks originating from vishing applications. In this work, we present Ventinel, an Android-based defense system designed to detect these attacks without requiring OS modifications. Ventinel employs Optical Character Recognition (OCR) to compare phone numbers during calls, effectively preventing Call Redirection and Display Overlay Attacks. Additionally, it safeguards against Duplicated Contacts Attacks by cross-referencing call logs and SMS records. Ventinel achieves 100% detection accuracy, surpassing commercial applications, and operates with minimal data collection to ensure user privacy. We also describe malicious API behavior and demonstrate that the same behavior is possible for API levels 29 and higher. Furthermore, we analyze the limitations of existing solutions and propose new attack and defense strategies. Full article

(This article belongs to the Special Issue Information and Future Internet Security, Trust and Privacy—3rd Edition)

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25 pages, 4837 KiB

Open AccessArticle

Hierarchical Aggregation for Federated Learning in Heterogeneous IoT Scenarios: Enhancing Privacy and Communication Efficiency

by Chen Qiu, Ziang Wu, Haoda Wang, Qinglin Yang, Yu Wang and Chunhua Su

Future Internet 2025, 17(1), 18; https://doi.org/10.3390/fi17010018 - 5 Jan 2025

Viewed by 1109

Abstract

Federated Learning (FL) is a distributed machine-learning paradigm that enables models to be trained across multiple decentralized devices or servers holding local data without transferring the raw data to a central location. However, applying FL to heterogeneous IoT scenarios comes with several challenges due to the diverse nature of these devices in terms of hardware capabilities, communications, and data heterogeneity. Furthermore, the conventional parameter server-based FL paradigm aggregates the trained parameters of devices directly, which incurs high communication overhead. To this end, this paper designs a hierarchical federated-learning framework for heterogeneous IoT systems, focusing on enhancing communication efficiency and ensuring data security through lightweight encryption. By leveraging hierarchical aggregation, lightweight stream encryption, and adaptive device participation, the proposed framework provides an efficient and robust solution for federated learning in dynamic and resource-constrained IoT environments. The extensive experimental results show that the proposed FL paradigm significantly reduces round time by 20%. Full article

(This article belongs to the Special Issue Information and Future Internet Security, Trust and Privacy—3rd Edition)

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20 pages, 697 KiB

Open AccessArticle

WebTrackingScore: A Combined Web Tracking Risk Score System for Websites

by Álvaro D. Guillén Cava and Antonio Ruiz-Martínez

Future Internet 2025, 17(1), 3; https://doi.org/10.3390/fi17010003 - 25 Dec 2024

Viewed by 915

Abstract

Privacy awareness has increased in recent years. In many countries, websites warn users about their use of cookies and Web browsers provide mechanisms to protect user privacy. However, it is not easy for users to understand tracking risks associated with browsing a given website. To address this, several privacy scanners have emerged to evaluate the privacy practices of websites. However, the scores these scanners provide are often limited to a small number of Web tracking indicators and are thus incomplete. To overcome this limitation, in this paper, we present WebTrackingScore, which provides users with a simple and intuitive indication of the privacy risk associated with visiting a website from a tracking perspective. Its design is based on an in-depth analysis of tracking mechanisms and the behaviour of some of the most frequently visited sites. Based on WebTrackingScore, we have analysed how the most popular websites are classified. Full article

(This article belongs to the Special Issue Information and Future Internet Security, Trust and Privacy—3rd Edition)

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24 pages, 4648 KiB

Open AccessArticle

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

Cited by 1 | Viewed by 2148

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 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—3rd Edition)

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16 pages, 554 KiB

Open AccessArticle

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 1269

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 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—3rd Edition)

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19 pages, 2171 KiB

Open AccessArticle

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 2424

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 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—3rd Edition)

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Review

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29 pages, 1635 KiB

Open AccessReview

A Comparative Survey of Centralised and Decentralised Identity Management Systems: Analysing Scalability, Security, and Feasibility

by Aviral Goel and Yogachandran Rahulamathavan

Future Internet 2025, 17(1), 1; https://doi.org/10.3390/fi17010001 - 24 Dec 2024

Viewed by 2549

Abstract

Traditional identity management (IdM) solutions based on centralised protocols, such as Lightweight Directory Access Protocol (LDAP) and Security Assertion Markup Language (SAML), are where a central authority manages all the processes. This risks a single point of failure and other vulnerabilities. In response, decentralised techniques like blockchain and decentralised identities (DIDs) are being explored. This review paper performs a comparison of popular decentralised identity management (DIM) protocols, such as self-sovereign identity (SSI), against traditional centralised approaches such as LDAP and SAML. These decentralised identity management systems are being developed, keeping users’ identity data as its highest priority. Additionally, this method eliminates the need for a central authority to manage and secure the system. To further explore the potential of decentralised identity management, this study delves into popular blockchain-based decentralised identity management systems such as uPort, Sovrin, EverID, Blockstack, ShoCard, and Hyperledger Indy. We analyse their underlying principles and compare them with the well-established centralised identity management solutions, focusing on key aspects such as scalability, security, and feasibility. However, despite their benefits and several worthy developments in this field, decentralised approaches are still not widely used. Through this study, we investigate both centralised and decentralised methods and review their strengths and weaknesses. By reviewing multiple research papers, this survey aims to provide an understanding and aid in selecting the most suitable identity management system for different use cases. Full article

(This article belongs to the Special Issue Information and Future Internet Security, Trust and Privacy—3rd Edition)

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