Future Internet

19 pages, 1060 KiB

Open AccessArticle

Protecting Function Privacy and Input Privacy in the Publicly Verifiable Outsourcing Computation of Polynomial Functions

by Beibei Song, Dehua Zhou, Jiahe Wu, Xiaowei Yuan, Yiming Zhu and Chuansheng Wang

Future Internet 2023, 15(4), 152; https://doi.org/10.3390/fi15040152 - 21 Apr 2023

Cited by 1 | Viewed by 1833

Abstract

With the prevalence of cloud computing, the outsourcing of computation has gained significant attention. Clients with limited computing power often outsource complex computing tasks to the cloud to save on computing resources and costs. In outsourcing the computation of functions, a function owner [...] Read more.

With the prevalence of cloud computing, the outsourcing of computation has gained significant attention. Clients with limited computing power often outsource complex computing tasks to the cloud to save on computing resources and costs. In outsourcing the computation of functions, a function owner delegates a cloud server to perform the function’s computation on the input received from the user. There are three primary security concerns associated with this process: protecting function privacy for the function owner, protecting input privacy for the user and guaranteeing that the cloud server performs the computation correctly. Existing works have only addressed privately verifiable outsourcing computation with privacy or publicly verifiable outsourcing computation without input privacy or function privacy. By using the technologies of homomorphic encryption, proxy re-encryption and verifiable computation, we propose the first publicly verifiable outsourcing computation scheme that achieves both input privacy and function privacy for matrix functions, which can be extended to arbitrary multivariate polynomial functions. We additionally provide a faster privately verifiable method. Moreover, the function owner retains control over the function. Full article

(This article belongs to the Special Issue Information and Future Internet Security, Trust and Privacy II)

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2 pages, 152 KiB

Open AccessEditorial

Distributed Systems for Emerging Computing: Platform and Application

by Xu Wang, Bin Shi and Yili Fang

Future Internet 2023, 15(4), 151; https://doi.org/10.3390/fi15040151 - 20 Apr 2023

Viewed by 1813

Abstract

In recent years, the new computing paradigms such as serverless computing, edge computing and blockchain-based computing have attracted much attention in both academia and industrial communities. Distributed systems and applications play fundamental roles in connecting the underlying computers, network and devices for collaboration, [...] Read more.

In recent years, the new computing paradigms such as serverless computing, edge computing and blockchain-based computing have attracted much attention in both academia and industrial communities. Distributed systems and applications play fundamental roles in connecting the underlying computers, network and devices for collaboration, as well as providing new services for users. However, due to the increasing complexity of the large-scale and dynamic heterogeneous resource, and the new requirements and features, these distributed systems and applications will face many challenges in terms of their efficiency, flexibility and algorithms. This editorial discusses the state-of-the-art advancements in distributed systems and applications for the emerging computing. Full article

(This article belongs to the Special Issue Distributed Systems for Emerging Computing: Platform and Application)

21 pages, 2275 KiB

Open AccessArticle

Target-Oriented Data Annotation for Emotion and Sentiment Analysis in Tourism Related Social Media Data

by Alireza Alaei, Ying Wang, Vinh Bui and Bela Stantic

Future Internet 2023, 15(4), 150; https://doi.org/10.3390/fi15040150 - 19 Apr 2023

Cited by 7 | Viewed by 2349

Abstract

Social media have been a valuable data source for studying people’s opinions, intentions, and behaviours. Such a data source incorporating advanced big data analysis methods, such as machine-operated emotion and sentiment analysis, will open unprecedented opportunities for innovative data-driven destination monitoring and management. [...] Read more.

Social media have been a valuable data source for studying people’s opinions, intentions, and behaviours. Such a data source incorporating advanced big data analysis methods, such as machine-operated emotion and sentiment analysis, will open unprecedented opportunities for innovative data-driven destination monitoring and management. However, a big challenge any machine-operated text analysis method faces is the ambiguity of the natural languages, which may cause an expression to have different meanings in different contexts. In this work, we address the ambiguity challenge by proposing a context-aware dictionary-based target-oriented emotion and sentiment analysis method that incorporates inputs from both humans and machines to introduce an alternative approach to measuring emotions and sentiment in limited tourism-related data. The study makes a methodological contribution by creating a target dictionary specifically for tourism sentiment analysis. To demonstrate the performance of the proposed method, a case of target-oriented emotion and sentiment analysis of posts from Twitter for the Gold Coast of Australia as a tourist destination was considered. The results suggest that Twitter data cover a broad range of destination attributes and can be a valuable source for comprehensive monitoring of tourist experiences at a destination. Full article

(This article belongs to the Special Issue Big Data Analytics, Privacy and Visualization)

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13 pages, 442 KiB

Open AccessArticle

Applying Patient Segmentation Using Primary Care Electronic Medical Records to Develop a Virtual Peer-to-Peer Intervention for Patients with Type 2 Diabetes

by Alessia Paglialonga, Rebecca Theal, Bruce Knox, Robert Kyba, David Barber, Aziz Guergachi and Karim Keshavjee

Future Internet 2023, 15(4), 149; https://doi.org/10.3390/fi15040149 - 14 Apr 2023

Cited by 1 | Viewed by 1991

Abstract

The aim of this study was to design a virtual peer-to-peer intervention for patients with type 2 diabetes (T2D) by grouping patients from specific segments using data from primary care electronic medical records (EMRs). Two opposing segments were identified: patients living with diabetes [...] Read more.

The aim of this study was to design a virtual peer-to-peer intervention for patients with type 2 diabetes (T2D) by grouping patients from specific segments using data from primary care electronic medical records (EMRs). Two opposing segments were identified: patients living with diabetes who tend to take several medications (“medication” segment: ~32%) and patients who do not take any diabetes-specific medications (“lifestyle” segment: ~15%). The remaining patients were from two intermediate segments and exhibited medication-taking behavior that placed them midway between the medication and lifestyle segments. Patients were grouped into six workshops (two workshops in each group: medication, lifestyle, and mixed group), including individuals with good and bad control of their disease. Measures of attitudes, learning, and motivation were addressed during and after the workshops. Results showed that patients in the lifestyle segment were more interested in T2D lifestyle control strategies, more satisfied with their in-workshop learning experience, and more motivated to set a goal than those in the medication segment. These results suggest that the proposed intervention may be more viable for patients in the lifestyle segment and that EMR data may be used to tailor behavioral interventions to specific patient groups. Future research is needed to investigate different segmentation approaches (e.g., using data related to smoking, drinking, diet, and physical activity) that could help tailor the intervention more effectively. Full article

(This article belongs to the Special Issue Challenges and Opportunities in Electronic Medical Record (EMR))

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18 pages, 2926 KiB

Open AccessArticle

A Multipath Data-Scheduling Strategy Based on Path Correlation for Information-Centric Networking

by Yong Xu, Hong Ni and Xiaoyong Zhu

Future Internet 2023, 15(4), 148; https://doi.org/10.3390/fi15040148 - 11 Apr 2023

Viewed by 1998

Abstract

Information-Centric Networking (ICN) has revolutionized the manner of content acquisition by shifting the communication mode from host-centric to information-centric. Considering the existing, large amount of IP infrastructure in current networks, the new ICN architecture is proposed to be compatible with existing networks in [...] Read more.

Information-Centric Networking (ICN) has revolutionized the manner of content acquisition by shifting the communication mode from host-centric to information-centric. Considering the existing, large amount of IP infrastructure in current networks, the new ICN architecture is proposed to be compatible with existing networks in order to reduce deployment cost. However, due to compatibility with IP networks, ICN data packets must be transmitted through the default path provided by IP routing regulations, which also limits the transmission efficiency and reliability of ICN. In order to address this issue, this paper introduces a multipath transmission method applied in ICN which takes full advantage of the functions and characteristics of ICN and builds multiple end-to-end relay paths by using the ICN routers as relay nodes. We then propose a relay-node-selection algorithm based on path correlation to minimize the impact of overlapping links. Moreover, we comprehensively calculate the path state value by combining the round-trip time and packet loss rate and propose a multipath data-scheduling algorithm based on the path state value. Simulation experiments show that the proposed method can maintain high bandwidth utilization while reducing the number of out-of-order packets. Full article

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24 pages, 3393 KiB

Open AccessArticle

A Multiverse Graph to Help Scientific Reasoning from Web Usage: Interpretable Patterns of Assessor Shifts in GRAPHYP

by Renaud Fabre, Otmane Azeroual, Joachim Schöpfel, Patrice Bellot and Daniel Egret

Future Internet 2023, 15(4), 147; https://doi.org/10.3390/fi15040147 - 10 Apr 2023

Cited by 1 | Viewed by 2922

Abstract

The digital support for scientific reasoning presents contrasting results. Bibliometric services are improving, but not academic assessment; no service for scholars relies on logs of web usage to base query strategies for relevance judgments (or assessor shifts). Our Scientific Knowledge Graph GRAPHYP innovates [...] Read more.

The digital support for scientific reasoning presents contrasting results. Bibliometric services are improving, but not academic assessment; no service for scholars relies on logs of web usage to base query strategies for relevance judgments (or assessor shifts). Our Scientific Knowledge Graph GRAPHYP innovates with interpretable patterns of web usage, providing scientific reasoning with conceptual fingerprints and helping identify eligible hypotheses. In a previous article, we showed how usage log data, in the form of ‘documentary tracks’, help determine distinct cognitive communities (called adversarial cliques) within sub-graphs. A typology of these documentary tracks through a triplet of measurements from logs (intensity, variety and attention) describes the potential approaches to a (research) question. GRAPHYP assists interpretation as a classifier, with possibilistic graphical modeling. This paper shows what this approach can bring to scientific reasoning; it involves visualizing complete interpretable pathways, in a multi-hop assessor shift, which users can then explore toward the ‘best possible solution’—the one that is most consistent with their hypotheses. Applying the Leibnizian paradigm of scientific reasoning, GRAPHYP highlights infinitesimal learning pathways, as a ‘multiverse’ geometric graph in modeling possible search strategies answering research questions. Full article

(This article belongs to the Special Issue Information Retrieval on the Semantic Web)

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20 pages, 679 KiB

Open AccessArticle

A Systematic Survey of Multi-Factor Authentication for Cloud Infrastructure

by Soumya Prakash Otta, Subhrakanta Panda, Maanak Gupta and Chittaranjan Hota

Future Internet 2023, 15(4), 146; https://doi.org/10.3390/fi15040146 - 10 Apr 2023

Cited by 13 | Viewed by 6875

Abstract

The unauthorized usage of various services and resources in cloud computing is something that must be protected against. Authentication and access control are the most significant concerns in cloud computing. Several researchers in this field suggest numerous approaches to enhance cloud authentication towards [...] Read more.

The unauthorized usage of various services and resources in cloud computing is something that must be protected against. Authentication and access control are the most significant concerns in cloud computing. Several researchers in this field suggest numerous approaches to enhance cloud authentication towards robustness. User names and associated passwords have been a common practice for long as Single Factor Authentication. However, advancements in the speed of computing and the usage of simple methods, starting from the Brute Force technique to the implementation of advanced and efficient crytographic algorithms, have posed several threats and vulnerabilities for authentication systems, leading to the degradation of their effectiveness. Multi-factor authentication has emerged as a robust means of securing the cloud using simultaneous and multiple means of authentication factors. This employs multiple levels of cascaded authentication checks. This paper covers an extensive and systematic survey of various factors towards their adoption and suitability for authentication for multi-factor authentication mechanisms. The inference drawn from the survey is in terms of arriving at a unique authentication factor that does not require any additional, specialized hardware or software for multi-factor authentication. Such authentication also uses the distinct biometric characteristics of the concerned user in the process. This arrangement augments the secured and robust user authentication process. The mechanism is also assessed as an effective means against impersonation attacks. Full article

(This article belongs to the Special Issue Cybersecurity in the Era of AI)

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19 pages, 1185 KiB

Open AccessArticle

Consumer’s Attitude towards Display Google Ads

by Mohammad Al Khasawneh, Abdel-Aziz Ahmad Sharabati, Shafig Al-Haddad, Rania Al-Daher, Sarah Hammouri and Sima Shaqman

Future Internet 2023, 15(4), 145; https://doi.org/10.3390/fi15040145 - 7 Apr 2023

Cited by 1 | Viewed by 4607

Abstract

The context of Display Google ads and its components has significant importance to previous studies. However, the full understanding of the variables that influence both Display Google ads avoidance and intention to click has not been thoroughly acknowledged. Thus, this study aims to [...] Read more.

The context of Display Google ads and its components has significant importance to previous studies. However, the full understanding of the variables that influence both Display Google ads avoidance and intention to click has not been thoroughly acknowledged. Thus, this study aims to outline an entire understanding of the different variables that lead Display Google ads to be avoided or clicked on. A detailed review of previous studies has been completed to illustrate a thorough image of Display Google ads. Accordingly, this study developed a theoretical model combining four variables (Display Google ads’ Prior Experience, Originality, Relevance, and Credibility) that lead to affecting Display Google ads’ Avoidance and Intention to Click, with one mediator (Consumer’s Attitude). A quantitative methodology has been employed, in which an online survey has been used to collect data, which were collected from 358 respondents, then coded against AMOS. The data analysis results show that three independent variables positively impact the intention to click; however, credibility has the highest value, then relevance and originality, consequently., while Display Google ads prior experience had no impact on the intention to click. Finally, the research concluded different practical and theoretical implications, and future potential research, and limitations. Full article

(This article belongs to the Topic Social Computing and Social Network Analysis)

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18 pages, 432 KiB

Open AccessEditor’s ChoiceReview

Opportunities for Early Detection and Prediction of Ransomware Attacks against Industrial Control Systems

by Mazen Gazzan and Frederick T. Sheldon

Future Internet 2023, 15(4), 144; https://doi.org/10.3390/fi15040144 - 7 Apr 2023

Cited by 17 | Viewed by 5342

Abstract

Industrial control systems (ICS) and supervisory control and data acquisition (SCADA) systems, which control critical infrastructure such as power plants and water treatment facilities, have unique characteristics that make them vulnerable to ransomware attacks. These systems are often outdated and run on proprietary [...] Read more.

Industrial control systems (ICS) and supervisory control and data acquisition (SCADA) systems, which control critical infrastructure such as power plants and water treatment facilities, have unique characteristics that make them vulnerable to ransomware attacks. These systems are often outdated and run on proprietary software, making them difficult to protect with traditional cybersecurity measures. The limited visibility into these systems and the lack of effective threat intelligence pose significant challenges to the early detection and prediction of ransomware attacks. Ransomware attacks on ICS and SCADA systems have become a growing concern in recent years. These attacks can cause significant disruptions to critical infrastructure and result in significant financial losses. Despite the increasing threat, the prediction of ransomware attacks on ICS remains a significant challenge for the cybersecurity community. This is due to the unique characteristics of these systems, including the use of proprietary software and limited visibility into their operations. In this review paper, we will examine the challenges associated with predicting ransomware attacks on industrial systems and the existing approaches for mitigating these risks. We will also discuss the need for a multi-disciplinary approach that involves a close collaboration between the cybersecurity and ICS communities. We aim to provide a comprehensive overview of the current state of ransomware prediction on industrial systems and to identify opportunities for future research and development in this area. Full article

(This article belongs to the Special Issue Cyber Security Challenges in the New Smart Worlds)

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17 pages, 551 KiB

Open AccessArticle

Implementing GDPR-Compliant Surveys Using Blockchain

by Ricardo Martins Gonçalves, Miguel Mira da Silva and Paulo Rupino da Cunha

Future Internet 2023, 15(4), 143; https://doi.org/10.3390/fi15040143 - 7 Apr 2023

Cited by 6 | Viewed by 2387

Abstract

The immutability of data stored in a blockchain is a crucial pillar of trust in this technology, which has led to its increasing adoption in various use cases. However, there are situations where the inability to change or delete data may be illegal. [...] Read more.

The immutability of data stored in a blockchain is a crucial pillar of trust in this technology, which has led to its increasing adoption in various use cases. However, there are situations where the inability to change or delete data may be illegal. European Union’s General Data Protection Regulation (GDPR)—applying to any company processing personal data from European citizens—explicitly entitles individuals to the right to rectification and the right to be forgotten. In this paper, we describe the design of a system to deploy and process survey data in a GDPR-compliant manner. It combines an Hyperledger Fabric blockchain to ensure that data cannot be tampered with and InterPlanetary File Systems (IPFS) for storage. With the proposed arrangement, we reap several security benefits enabled by blockchain’s immutability without running afoul of the regulations. Furthermore, the proof-of-concept is generic and can easily be adapted to various domains. Full article

(This article belongs to the Special Issue Blockchain Security and Privacy II)

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15 pages, 5002 KiB

Open AccessEditor’s ChoiceArticle

Future of Drug Discovery: The Synergy of Edge Computing, Internet of Medical Things, and Deep Learning

by Mohammad (Behdad) Jamshidi, Omid Moztarzadeh, Alireza Jamshidi, Ahmed Abdelgawad, Ayman S. El-Baz and Lukas Hauer

Future Internet 2023, 15(4), 142; https://doi.org/10.3390/fi15040142 - 7 Apr 2023

Cited by 20 | Viewed by 4815

Abstract

The global spread of COVID-19 highlights the urgency of quickly finding drugs and vaccines and suggests that similar challenges will arise in the future. This underscores the need for ongoing efforts to overcome the obstacles involved in the development of potential treatments. Although [...] Read more.

The global spread of COVID-19 highlights the urgency of quickly finding drugs and vaccines and suggests that similar challenges will arise in the future. This underscores the need for ongoing efforts to overcome the obstacles involved in the development of potential treatments. Although some progress has been made in the use of Artificial Intelligence (AI) in drug discovery, virologists, pharmaceutical companies, and investors seek more long-term solutions and greater investment in emerging technologies. One potential solution to aid in the drug-development process is to combine the capabilities of the Internet of Medical Things (IoMT), edge computing (EC), and deep learning (DL). Some practical frameworks and techniques utilizing EC, IoMT, and DL have been proposed for the monitoring and tracking of infected individuals or high-risk areas. However, these technologies have not been widely utilized in drug clinical trials. Given the time-consuming nature of traditional drug- and vaccine-development methods, there is a need for a new AI-based platform that can revolutionize the industry. One approach involves utilizing smartphones equipped with medical sensors to collect and transmit real-time physiological and healthcare information on clinical-trial participants to the nearest edge nodes (EN). This allows the verification of a vast amount of medical data for a large number of individuals in a short time frame, without the restrictions of latency, bandwidth, or security constraints. The collected information can be monitored by physicians and researchers to assess a vaccine’s performance. Full article

(This article belongs to the Special Issue Internet of Things and Internet of Everything: Current Trends, Challenges, and New Perspectives)

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29 pages, 4192 KiB

Open AccessArticle

Post-Digital Learning for Rural Development: A Case Study of Open Biotec MOOCs in Colombia

by Carlos Ocampo-López, Oscar Muñoz-Blandón, Leidy Rendón-Castrillón and Margarita Ramírez-Carmona

Future Internet 2023, 15(4), 141; https://doi.org/10.3390/fi15040141 - 6 Apr 2023

Cited by 1 | Viewed by 3002

Abstract

This research presents an experience of post-digital learning of biotechnology in rural areas in Colombia by implementing a massive open online course (MOOC) for biotechnology education called Open Biotec. The objective was to improve Colombian rural development by creating learning communities around [...] Read more.

This research presents an experience of post-digital learning of biotechnology in rural areas in Colombia by implementing a massive open online course (MOOC) for biotechnology education called Open Biotec. The objective was to improve Colombian rural development by creating learning communities around five topics: waste management, environmental biotechnology, bioprocesses, alternative energies, and bio-entrepreneurship. The study utilized various methods, including a socioeconomic diagnosis of a subregion of the department of Antioquia, Colombia, and the creation of MOOCs using the Action Research methodology. The pilot test of the training route in biotechnology involved the progressive development of the MOOC courses that comprise it. Around 918 students from rural areas were trained, and statistical analysis showed that the average grade of the students increased significantly from 6.13 to 7.53 and the median from 6.15 to 8.00. The study results demonstrate how the learning experience designed in the Open Biotec MOOC increases the degree of knowledge of students in this field of biotechnology, offering an opportunity to establish sustainable learning communities with participation and collaborative action mediated by virtual tools. The study concludes that rural education in Colombia could be strengthened with a training strategy for rural communities supported by MOOCs focused on the responsible use of local biodiversity from a biotechnological perspective. Full article

(This article belongs to the Special Issue Smart Objects and Technologies for Social Good II)

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12 pages, 1586 KiB

Open AccessArticle

Emerging Technologies and Their Link to Digital Competence in Teaching

by Miguel Ángel García-Delgado, Sonia Rodríguez-Cano, Vanesa Delgado-Benito and María Lozano-Álvarez

Future Internet 2023, 15(4), 140; https://doi.org/10.3390/fi15040140 - 5 Apr 2023

Cited by 1 | Viewed by 2460

Abstract

The new educational reality requires teachers to have a series of skills and competences that allow them to improve the teaching–learning process and therefore the quality of teaching, integrating technology and emerging technologies. In order to assess the competence level of teachers, a [...] Read more.

The new educational reality requires teachers to have a series of skills and competences that allow them to improve the teaching–learning process and therefore the quality of teaching, integrating technology and emerging technologies. In order to assess the competence level of teachers, a descriptive study was designed, in which 101 teachers from different stages and geographical locations in Spain took part and were administered the DigCompEdu Check-in questionnaire. The results show average levels of teachers’ digital competence (B1 and B2, particularly), and an incipient use of emerging technologies by teachers, with less than 50% of the sample not using these technologies in their daily classroom activities, although those who show a higher level of digital competence are also those who integrate them more in their daily work. The results correspond with similar studies, corroborating the average level of teachers’ digital skills. Full article

(This article belongs to the Special Issue Virtual Reality and Metaverse: Impact on the Digital Transformation of Society)

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32 pages, 4198 KiB

Open AccessArticle

Towards a Reference Architecture for Cargo Ports

by Virginia M. Romero and Eduardo B. Fernandez

Future Internet 2023, 15(4), 139; https://doi.org/10.3390/fi15040139 - 4 Apr 2023

Cited by 1 | Viewed by 3074

Abstract

Cyber-Physical Systems (CPS) are physical systems whose operations are coordinated, monitored, and controlled by computing and communication functions. These systems are typically heterogeneous, including Internet of Things and information technology subsystems, and can present a myriad of implementation details, making them very complex [...] Read more.

Cyber-Physical Systems (CPS) are physical systems whose operations are coordinated, monitored, and controlled by computing and communication functions. These systems are typically heterogeneous, including Internet of Things and information technology subsystems, and can present a myriad of implementation details, making them very complex systems. An important type of CPS is a maritime container terminal (cargo port), which is a facility where cargo containers are transported between ships and land vehicles for onward transportation and vice versa. A cargo port performs four basic functions: receiving, storing, staging, and loading for both import and export containers. We present here process patterns that describe the functional aspects of cargo ports and a pattern that describes their structural properties (patterns are encapsulated solutions to recurrent problems). These patterns describe semantic aspects found in any cargo port and can be adapted to describe other CPSs. We decompose these process patterns into use cases that describe their interactions with the system. We then integrate the process patterns with structural patterns to assemble a partial reference architecture (RA) that shows the interactions of all the patterns while also indicating the typical stakeholders found in all ports. We validate the proposed reference architecture, highlighting its theoretical and practical value. Software and system designers of cargo ports need to start from a conceptual and abstract view that is subsequently refined to add more details. The use of reference architectures and patterns is an effective way to organize and describe the functional and non-functional aspects of a system, as well as to unify the design of all its aspects. This is, until now, the only published RA for cargo ports, and it can be a useful guideline for the designers of any type of cargo port. Full article

(This article belongs to the Special Issue Internet of Things and Internet of Everything: Current Trends, Challenges, and New Perspectives)

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18 pages, 1560 KiB

Open AccessArticle

Performance Evaluation of a Lane Correction Module Stress Test: A Field Test of Tesla Model 3

by Jonathan Lancelot, Bhaskar P. Rimal and Edward M. Dennis

Future Internet 2023, 15(4), 138; https://doi.org/10.3390/fi15040138 - 31 Mar 2023

Cited by 3 | Viewed by 2965

Abstract

This paper is designed to explicate and analyze data acquired from experimental field tests of a Tesla Model 3 lane correction module within the vehicle’s Autopilot Suite, a component of Tesla OS. The initial problem was discovered during a nominal drive of the [...] Read more.

This paper is designed to explicate and analyze data acquired from experimental field tests of a Tesla Model 3 lane correction module within the vehicle’s Autopilot Suite, a component of Tesla OS. The initial problem was discovered during a nominal drive of the Tesla Model 3, where after a random number of lane correction events, the lane correction module shuts down, issues a visual disable warning on the touchscreen, and control of the vehicle is given to the driver until the next drive. That development was considered problematic, as the driver can be caught off guard or may be medically disabled and unable to respond. During a controlled stress test, a more severe issue was discovered. After a random number of lane correction events, the lane correction module shuts down without warning, then stays activated after the test driver corrects the vehicle’s trajectory. This is considered a fatal error in the system and adds a dangerous element to an otherwise standard feature in a modern automotive vehicle. The results established that the number of events needed to trigger a fatal error without warning is unpredictable. Our results also demonstrate that the system is inconsistent. Full article

(This article belongs to the Special Issue Internet of Things and Cyber-Physical Systems II)

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14 pages, 3008 KiB

Open AccessArticle

Contrastive Refinement for Dense Retrieval Inference in the Open-Domain Question Answering Task

by Qiuhong Zhai, Wenhao Zhu, Xiaoyu Zhang and Chenyun Liu

Future Internet 2023, 15(4), 137; https://doi.org/10.3390/fi15040137 - 31 Mar 2023

Cited by 2 | Viewed by 1651

Abstract

In recent years, dense retrieval has emerged as the primary method for open-domain question-answering (OpenQA). However, previous research often focused on the query side, neglecting the importance of the passage side. We believe that both the query and passage sides are equally important [...] Read more.

In recent years, dense retrieval has emerged as the primary method for open-domain question-answering (OpenQA). However, previous research often focused on the query side, neglecting the importance of the passage side. We believe that both the query and passage sides are equally important and should be considered for improved OpenQA performance. In this paper, we propose a contrastive pseudo-labeled data constructed around passages and queries separately. We employ an improved pseudo-relevance feedback (PRF) algorithm with a knowledge-filtering strategy to enrich the semantic information in dense representations. Additionally, we proposed an Auto Text Representation Optimization Model (AOpt) to iteratively update the dense representations. Experimental results demonstrate that our methods effectively optimize dense representations, making them more distinguishable in dense retrieval, thus improving the OpenQA system’s overall performance. Full article

(This article belongs to the Special Issue Natural Language Processing (NLP) and Information Retrieval (IR) in Internet of Things)

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14 pages, 3911 KiB

Open AccessArticle

Effective IoT Congestion Control Algorithm

by Husam H. Hasan and Zainab T. Alisa

Future Internet 2023, 15(4), 136; https://doi.org/10.3390/fi15040136 - 31 Mar 2023

Cited by 6 | Viewed by 2434

Abstract

The Internet of Things (IoT) connects devices via the Internet. Network congestion is one of the key problems that has been identified by researchers in the IoT field. When there is a huge number of IoT devices connected to the internet, this creates [...] Read more.

The Internet of Things (IoT) connects devices via the Internet. Network congestion is one of the key problems that has been identified by researchers in the IoT field. When there is a huge number of IoT devices connected to the internet, this creates network congestion. Transfer control protocol is a transport layer protocol that provides a reliable end-to-end connection between two devices. Many Congestion Control Algorithms have been proposed to solve network congestion. However, there is no perfect solution to this problem. This paper proposes an effective loss-based Congestion Control Algorithm to effectively adapt the congestion window in the IoT environment. It uses simple experiment scenarios to test the algorithm for wired and wireless channels and observes important performance metrics: link utilization, inter-protocol fairness, intra-protocol fairness and throughput. The results are impressive, and the proposed algorithm is shown to outperform other standard algorithms. Full article

(This article belongs to the Special Issue Future Communication Networks for the Internet of Things (IoT))

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23 pages, 1750 KiB

Open AccessArticle

Transforming IoT Events to Meaningful Business Events on the Edge: Implementation for Smart Farming Application

by Dimitris Gkoulis, Cleopatra Bardaki, George Kousiouris and Mara Nikolaidou

Future Internet 2023, 15(4), 135; https://doi.org/10.3390/fi15040135 - 31 Mar 2023

Cited by 1 | Viewed by 1885

Abstract

This paper focuses on Internet of Things (IoT) architectures and knowledge generation out of streams of events as the primary elements concerning the creation of user-centric IoT services. We provide a general, symmetrical IoT architecture, which enables two-way bidirectional communication between things and [...] Read more.

This paper focuses on Internet of Things (IoT) architectures and knowledge generation out of streams of events as the primary elements concerning the creation of user-centric IoT services. We provide a general, symmetrical IoT architecture, which enables two-way bidirectional communication between things and users within an application domain. We focus on two main components of the architecture (i.e., Event Engine and Process Engine) that handle event transformation by implementing parametric Complex Event Processing (CEP). More specifically, we describe and implement the transformation cycle of events starting from raw IoT data to their processing and transformation of events for calculating information that we need in an IoT-enabled application context. The implementation includes a library of composite transformations grouping the gradual and sequential steps for transforming basic IoT events into business events, which include ingestion, event splitting, and calculation of measurements’ average value. The appropriateness and possibility of inclusion and integration of the implementation in an IoT environment are demonstrated by providing our implementation for a smart farming application domain with four scenarios that each reflect a user’s requirements. Further, we discuss the quality properties of each scenario. Ultimately, we propose an IoT architecture and, specifically, a parametric CEP model and implementation for future researchers and practitioners who aspire to build IoT applications. Full article

(This article belongs to the Special Issue Smart Objects and Technologies for Social Good II)

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17 pages, 9851 KiB

Open AccessArticle

A Comparative Study of Single and Multi-Stage Forecasting Algorithms for the Prediction of Electricity Consumption Using a UK-National Health Service (NHS) Hospital Dataset

by Ahmad Taha, Basel Barakat, Mohammad M. A. Taha, Mahmoud A. Shawky, Chun Sing Lai, Sajjad Hussain, Muhammad Zainul Abideen and Qammer H. Abbasi

Future Internet 2023, 15(4), 134; https://doi.org/10.3390/fi15040134 - 31 Mar 2023

Viewed by 1951

Abstract

Accurately looking into the future was a significantly major challenge prior to the era of big data, but with rapid advancements in the Internet of Things (IoT), Artificial Intelligence (AI), and the data availability around us, this has become relatively easier. Nevertheless, in [...] Read more.

Accurately looking into the future was a significantly major challenge prior to the era of big data, but with rapid advancements in the Internet of Things (IoT), Artificial Intelligence (AI), and the data availability around us, this has become relatively easier. Nevertheless, in order to ensure high-accuracy forecasting, it is crucial to consider suitable algorithms and the impact of the extracted features. This paper presents a framework to evaluate a total of nine forecasting algorithms categorised into single and multistage models, constructed from the Prophet, Support Vector Regression (SVR), Long Short-Term Memory (LSTM), and the Least Absolute Shrinkage and Selection Operator (LASSO) approaches, applied to an electricity demand dataset from an NHS hospital. The aim is to see such techniques widely used in accurately predicting energy consumption, limiting the negative impacts of future waste on energy, and making a contribution towards the 2050 net zero carbon target. The proposed method accounts for patterns in demand and temperature to accurately forecast consumption. The Coefficient of Determination (

R^{2}

), Mean Absolute Error (MAE), and Root Mean Square Error (RMSE) were used to evaluate the algorithms’ performance. The results show the superiority of the Long Short-Term Memory (LSTM) model and the multistage Facebook Prophet model, with

R^{2}

values of

87.20 %

and

68.06 %

, respectively. Full article

(This article belongs to the Special Issue Smart Objects and Technologies for Social Good II)

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18 pages, 2258 KiB

Open AccessArticle

SSQLi: A Black-Box Adversarial Attack Method for SQL Injection Based on Reinforcement Learning

by Yuting Guan, Junjiang He, Tao Li, Hui Zhao and Baoqiang Ma

Future Internet 2023, 15(4), 133; https://doi.org/10.3390/fi15040133 - 30 Mar 2023

Cited by 7 | Viewed by 4039

Abstract

SQL injection is a highly detrimental web attack technique that can result in significant data leakage and compromise system integrity. To counteract the harm caused by such attacks, researchers have devoted much attention to the examination of SQL injection detection techniques, which have [...] Read more.

SQL injection is a highly detrimental web attack technique that can result in significant data leakage and compromise system integrity. To counteract the harm caused by such attacks, researchers have devoted much attention to the examination of SQL injection detection techniques, which have progressed from traditional signature-based detection methods to machine- and deep-learning-based detection models. These detection techniques have demonstrated promising results on existing datasets; however, most studies have overlooked the impact of adversarial attacks, particularly black-box adversarial attacks, on detection methods. This study addressed the shortcomings of current SQL injection detection techniques and proposed a reinforcement-learning-based black-box adversarial attack method. The proposal included an innovative vector transformation approach for the original SQL injection payload, a comprehensive attack-rule matrix, and a reinforcement-learning-based method for the adaptive generation of adversarial examples. Our approach was evaluated on existing web application firewalls (WAF) and detection models based on machine- and deep-learning methods, and the generated adversarial examples successfully bypassed the detection method at a rate of up to 97.39%. Furthermore, there was a substantial decrease in the detection accuracy of the model after multiple attacks had been carried out on the detection model via the adversarial examples. Full article

(This article belongs to the Special Issue Cybersecurity in the Era of AI)

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18 pages, 4321 KiB

Open AccessArticle

Study of Coded ALOHA with Multi-User Detection under Heavy-Tailed and Correlated Arrivals

by María E. Sousa-Vieira and Manuel Fernández-Veiga

Future Internet 2023, 15(4), 132; https://doi.org/10.3390/fi15040132 - 30 Mar 2023

Cited by 1 | Viewed by 1546

Abstract

In this paper, we study via simulation the performance of irregular repetition slotted ALOHA under multi-packet detection and different patterns of the load process. On the one hand, we model the arrival process with a version of the M/G/∞ process able to [...] Read more.

In this paper, we study via simulation the performance of irregular repetition slotted ALOHA under multi-packet detection and different patterns of the load process. On the one hand, we model the arrival process with a version of the M/G/∞ process able to exhibit a correlation structure decaying slowly in time. Given the independence among frames in frame-synchronous coded-slotted ALOHA (CSA), this variation should only take effect on frame-asynchronous CSA. On the other hand, we vary the marginal distribution of the arrival process using discrete versions of the Lognormal and Pareto distributions, with the objective of investigating the influence of the right tail. In this case, both techniques should be affected by the change, albeit to a different degree. Our results confirm these hypotheses and show that these factors must be taken into account when designing and analyzing these systems. In frameless operations, both the shape of the packet arrivals tail distribution and the existence of short-range and long-range correlations strongly impact the packet loss ratio and the average delay. Nevertheless, these effects emerge only weakly in the case of frame-aligned operations, because this enforces the system to introduce a delay in the newly arrived packets (until the beginning of the next frame), and implies that the backlog of accumulated packets is the key quantity for calculating the performance. Full article

(This article belongs to the Collection 5G/6G Networks for the Internet of Things: Communication Technologies and Challenges)

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18 pages, 995 KiB

Open AccessEditor’s ChoiceReview

Influential Factors in the Design and Development of a Sustainable Web3/Metaverse and Its Applications

by Reza Aria, Norm Archer, Moein Khanlari and Bharat Shah

Future Internet 2023, 15(4), 131; https://doi.org/10.3390/fi15040131 - 30 Mar 2023

Cited by 15 | Viewed by 6182

Abstract

This paper summarizes the work of many different authors, industries, and countries by introducing important and influential factors that will help in the development, successful adoption, and sustainable use of the Web3/metaverse and its applications. We introduce a few important factors derived from [...] Read more.

This paper summarizes the work of many different authors, industries, and countries by introducing important and influential factors that will help in the development, successful adoption, and sustainable use of the Web3/metaverse and its applications. We introduce a few important factors derived from the current state-of-the-art literature, including four essential elements including (1) appropriate decentralization, (2) good user experience, (3) appropriate translation and synchronization to the real world, and (4) a viable economy, which are required for appropriate implementation of a metaverse and its applications. The future of Web3 is all about decentralization, and blockchain can play a significant part in the development of the Metaverse. This paper also sheds light on some of the most relevant open issues and challenges currently facing the Web3/metaverse and its applications, with the hope that this discourse will help to encourage the development of appropriate solutions. Full article

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24 pages, 795 KiB

Open AccessArticle

Resampling Imbalanced Network Intrusion Datasets to Identify Rare Attacks

by Sikha Bagui, Dustin Mink, Subhash Bagui, Sakthivel Subramaniam and Daniel Wallace

Future Internet 2023, 15(4), 130; https://doi.org/10.3390/fi15040130 - 29 Mar 2023

Cited by 7 | Viewed by 3145

Abstract

This study, focusing on identifying rare attacks in imbalanced network intrusion datasets, explored the effect of using different ratios of oversampled to undersampled data for binary classification. Two designs were compared: random undersampling before splitting the training and testing data and random undersampling [...] Read more.

This study, focusing on identifying rare attacks in imbalanced network intrusion datasets, explored the effect of using different ratios of oversampled to undersampled data for binary classification. Two designs were compared: random undersampling before splitting the training and testing data and random undersampling after splitting the training and testing data. This study also examines how oversampling/undersampling ratios affect random forest classification rates in datasets with minority dataor rare attacks. The results suggest that random undersampling before splitting gives better classification rates; however, random undersampling after oversampling with BSMOTE allows for the use of lower ratios of oversampled data. Full article

(This article belongs to the Section Cybersecurity)

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21 pages, 2663 KiB

Open AccessArticle

Addressing ZSM Security Issues with Blockchain Technology

by Michael Xevgenis, Dimitrios G. Kogias, Panagiotis A. Karkazis and Helen C. Leligou

Future Internet 2023, 15(4), 129; https://doi.org/10.3390/fi15040129 - 28 Mar 2023

Cited by 4 | Viewed by 2102

Abstract

Undoubtedly, we are witnessing a new era of computer networks that aspire to support modern demanding applications by providing the highest Quality of Experience (QoE) to the end user. Next Generations Networks (NGNs) ensure that characteristics such as ultra-low latency, high availability and [...] Read more.

Undoubtedly, we are witnessing a new era of computer networks that aspire to support modern demanding applications by providing the highest Quality of Experience (QoE) to the end user. Next Generations Networks (NGNs) ensure that characteristics such as ultra-low latency, high availability and wide service coverage can be met across the network regardless of the network infrastructure ownership. To accomplish that, beyond the necessary improvements in the radio propagation field, changes have been made in the core network functions which are now characterized as programmable, and software defined. Software Defined Networks (SDNs) and Network Function Virtualization (NFV) are the keystones of the NGNs flexibility. The high expectations of NGNs’ performance and the continuous changes in the network conditions lead to the development of new network management frameworks that add elasticity and dynamicity and minimize human intervention. ETSI (the European Standards Organization) presents the Zero-touch Service Management (ZSM) framework that uses hyped technologies such as Artificial Intelligence (AI) and Machine Learning (ML) to achieve full end-to-end automation of the network services’ management across one or many different domains. Focusing on multi-domain network service management, there are several security issues identified by the standardization team which mostly derive from the lack of trust among network providers. In the present research, we explore the suitability of blockchain technology adoption for facing these security issues. Blockchain technology inherently addresses security in trustless environments such as the infrastructures defined by the ZSM team. Our contribution is three-fold: (a) we define the architecture of a multi-domain network infrastructure that adopts the ZSM approach and integrates blockchain functionality, (b) we explore the adoption of different blockchain and distributed ledger technologies (DLT) approaches to address ZSM security needs and (c) we provide guidelines to prospective solution designers/implementers on the detailed requirements that this solution has to meet to maximize the offered value. Full article

(This article belongs to the Special Issue Security and Privacy in Blockchains and the IoT II)

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14 pages, 1300 KiB

Open AccessArticle

A Network Intrusion Detection Method Incorporating Bayesian Attack Graph and Incremental Learning Part

by Kongpei Wu, Huiqin Qu and Conggui Huang

Future Internet 2023, 15(4), 128; https://doi.org/10.3390/fi15040128 - 28 Mar 2023

Cited by 1 | Viewed by 1884

Abstract

For the current stage of complex and changing network environments and correlated and synchronized vulnerability attacks, this study first fuses attack graph technology and Bayesian networks and constructs Bayesian attack graphs toportray the correlation relationships between vulnerabilities and discovering attackers’ intentions. Meanwhile, improving [...] Read more.

For the current stage of complex and changing network environments and correlated and synchronized vulnerability attacks, this study first fuses attack graph technology and Bayesian networks and constructs Bayesian attack graphs toportray the correlation relationships between vulnerabilities and discovering attackers’ intentions. Meanwhile, improving the Bayesian attack graph is difficult because it is difficult to achieve active updates and adapt to the changing network environment and other problems. The study proposed a detection method that integrated the Bayesian attack graph and the XGBoost incremental learning (IL) approach. Experiments showed that the IL model had an accuracy of 0.951, an accuracy of 0.999, a recall of 0.815, an F1 value of 0.898, and an Area Under Curve (AUC) value of 0.907. The prediction ability of this method was better than that of the base model. Bayesian attack graphs fused with IL can detect attacks in the network more efficiently and accurately, so the probability of each node in the network system being attacked can be updated in real time. Full article

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31 pages, 1127 KiB

Open AccessArticle

A Highly Interactive Honeypot-Based Approach to Network Threat Management

by Xingyuan Yang, Jie Yuan, Hao Yang, Ya Kong, Hao Zhang and Jinyu Zhao

Future Internet 2023, 15(4), 127; https://doi.org/10.3390/fi15040127 - 28 Mar 2023

Cited by 9 | Viewed by 8530

Abstract

In this paper, considering the problem that the common defensive means in the current cyber confrontation often fall into disadvantage, honeypot technology is adopted to turn reactive into proactive to deal with the increasingly serious cyberspace security problem. We address the issue of [...] Read more.

In this paper, considering the problem that the common defensive means in the current cyber confrontation often fall into disadvantage, honeypot technology is adopted to turn reactive into proactive to deal with the increasingly serious cyberspace security problem. We address the issue of common defensive measures in current cyber confrontations that frequently lead to disadvantages. To tackle the progressively severe cyberspace security problem, we propose the adoption of honeypot technology to shift from a reactive to a proactive approach. This system uses honeypot technology for active defense, tempting attackers into a predetermined sandbox to observe the attacker’s behavior and attack methods to better protect equipment and information security. During the research, it was found that due to the singularity of traditional honeypots and the limitations of low-interactivity honeypots, the application of honeypot technology has difficulty in achieving the desired protective effect. Therefore, the system adopts a highly interactive honeypot and a modular design idea to distinguish the honeypot environment from the central node of data processing, so that the honeypot can obtain more sufficient information and the honeypot technology can be used more easily. By managing honeypots at the central node, i.e., adding, deleting, and modifying honeypots and other operations, it is easy to maintain and upgrade the system, while reducing the difficulty of using honeypots. The high-interactivity honeypot technology not only attracts attackers into pre-set sandboxes to observe their behavior and attack methods, but also performs a variety of advanced functions, such as network threat analysis, virtualization, vulnerability perception, tracing reinforcement, and camouflage detection. We have conducted a large number of experimental comparisons and proven that our method has significant advantages compared to traditional honeypot technology and provides detailed data support. Our research provides new ideas and effective methods for network security protection. Full article

(This article belongs to the Section Cybersecurity)

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13 pages, 7114 KiB

Open AccessArticle

View Synthesis with Scene Recognition for Cross-View Image Localization

by Uddom Lee, Peng Jiang, Hongyi Wu and Chunsheng Xin

Future Internet 2023, 15(4), 126; https://doi.org/10.3390/fi15040126 - 28 Mar 2023

Cited by 1 | Viewed by 2058

Abstract

Image-based localization has been widely used for autonomous vehicles, robotics, augmented reality, etc., and this is carried out by matching a query image taken from a cell phone or vehicle dashcam to a large scale of geo-tagged reference images, such as satellite/aerial images [...] Read more.

Image-based localization has been widely used for autonomous vehicles, robotics, augmented reality, etc., and this is carried out by matching a query image taken from a cell phone or vehicle dashcam to a large scale of geo-tagged reference images, such as satellite/aerial images or Google Street Views. However, the problem remains challenging due to the inconsistency between the query images and the large-scale reference datasets regarding various light and weather conditions. To tackle this issue, this work proposes a novel view synthesis framework equipped with deep generative models, which can merge the unique features from the outdated reference dataset with features from the images containing seasonal changes. Our design features a unique scheme to ensure that the synthesized images contain the important features from both reference and patch images, covering seasonable features and minimizing the gap for the image-based localization tasks. The performance evaluation shows that the proposed framework can synthesize the views in various weather and lighting conditions. Full article

(This article belongs to the Special Issue Securing Big Data Analytics for Cyber-Physical Systems)

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17 pages, 7576 KiB

Open AccessArticle

Banging Interaction: A Ubimus-Design Strategy for the Musical Internet

by Damián Keller, Azeema Yaseen, Joseph Timoney, Sutirtha Chakraborty and Victor Lazzarini

Future Internet 2023, 15(4), 125; https://doi.org/10.3390/fi15040125 - 27 Mar 2023

Cited by 2 | Viewed by 1696

Abstract

We introduce a new perspective for musical interaction tailored to a specific class of sonic resources: impact sounds. Our work is informed by the field of ubiquitous music (ubimus) and engages with the demands of artistic practices. Through a series of deployments of [...] Read more.

We introduce a new perspective for musical interaction tailored to a specific class of sonic resources: impact sounds. Our work is informed by the field of ubiquitous music (ubimus) and engages with the demands of artistic practices. Through a series of deployments of a low-cost and highly flexible network-based prototype, the Dynamic Drum Collective, we exemplify the limitations and specific contributions of banging interaction. Three components of this new design strategy—adaptive interaction, mid-air techniques and timbre-led design—target the development of creative-action metaphors that make use of resources available in everyday settings. The techniques involving the use of sonic gridworks yielded positive outcomes. The subjects tended to choose sonic materials that—when combined with their actions on the prototype—approached a full rendition of the proposed soundtrack. The results of the study highlighted the subjects’ reliance on visual feedback as a non-exclusive strategy to handle both temporal organization and collaboration. The results show a methodological shift from device-centric and instrumental-centric methods to designs that target the dynamic relational properties of ubimus ecosystems. Full article

(This article belongs to the Special Issue Advances Techniques in Computer Vision and Multimedia)

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23 pages, 20433 KiB

Open AccessArticle

Developing a Virtual World for an Open-House Event: A Metaverse Approach

by Keattikorn Samarnggoon, Supara Grudpan, Noppon Wongta and Konlawat Klaynak

Future Internet 2023, 15(4), 124; https://doi.org/10.3390/fi15040124 - 27 Mar 2023

Cited by 4 | Viewed by 2895

Abstract

The concept of a metaverse, a virtual world that offers immersive experiences, has gained widespread interest in recent years. Despite the hype, there is still a gap in its practical application, especially in the realm of education. This study presents the design and [...] Read more.

The concept of a metaverse, a virtual world that offers immersive experiences, has gained widespread interest in recent years. Despite the hype, there is still a gap in its practical application, especially in the realm of education. This study presents the design and implementation of a metaverse tailored to the needs of education. The goal of this paper is to demonstrate the feasibility of such a system and evaluate its effectiveness. It is crucial to understand the architecture and implementation of a metaverse to effectively customise it for educational purposes. To assess user experience, a field study was conducted, collecting data through questionnaires and qualitative feedback. The results show that users were pleased with the features, player experience, and ease of use. Full article

(This article belongs to the Section Big Data and Augmented Intelligence)

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18 pages, 1071 KiB

Open AccessArticle

Insights into How Vietnamese Retailers Utilize Social Media to Facilitate Knowledge Creation through the Process of Value Co-Creation

by Peter R. J. Trim, Yang-Im Lee and An Vu

Future Internet 2023, 15(4), 123; https://doi.org/10.3390/fi15040123 - 26 Mar 2023

Cited by 1 | Viewed by 2882

Abstract

Social media usage is a direct result of Internet connectivity and is gaining increased prominence in business-to-consumer (B2C), business-to-business (B2B), and consumer-to-business (C2B) relationship building, which is allowing marketers to devise and implement digital marketing strategies that are perceived as enhancing a customer’s [...] Read more.

Social media usage is a direct result of Internet connectivity and is gaining increased prominence in business-to-consumer (B2C), business-to-business (B2B), and consumer-to-business (C2B) relationship building, which is allowing marketers to devise and implement digital marketing strategies that are perceived as enhancing a customer’s well-being. Through the process of utilizing social media (SM) to share information with consumers, marketers are affording themselves with the concept of value co-creation and ensuring that the development of knowledge is given priority. To explain how this happens in an emerging economy, in-depth personal interviews were undertaken with the owners of five retail fashion companies in Vietnam. The findings indicate that fashion retail companies in Vietnam are deploying digital marketing strategies that deliver perceived enhanced value to consumers through the process of value co-creation. This highlights the advantage of using SM in relation to increasing retail staff’s ability to convert information into usable resources such as intelligence and knowledge. By achieving knowledge conversion, retail staff fulfill the role of ‘knowledge broker’ and ‘knowledge connector’, and identify how organizational intervention, such as new operating structures, can help to deliver perceived enhanced value to customers. Full article

(This article belongs to the Section Big Data and Augmented Intelligence)

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Future Internet, Volume 15, Issue 4 (April 2023) – 35 articles

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