Future Internet

30 pages, 621 KiB

Open AccessArticle

A Local Feature Engineering Strategy to Improve Network Anomaly Detection

by Salvatore Carta, Alessandro Sebastian Podda, Diego Reforgiato Recupero and Roberto Saia

Future Internet 2020, 12(10), 177; https://doi.org/10.3390/fi12100177 - 21 Oct 2020

Cited by 33 | Viewed by 4448

The dramatic increase in devices and services that has characterized modern societies in recent decades, boosted by the exponential growth of ever faster network connections and the predominant use of wireless connection technologies, has materialized a very crucial challenge in terms of security. [...] Read more.

The dramatic increase in devices and services that has characterized modern societies in recent decades, boosted by the exponential growth of ever faster network connections and the predominant use of wireless connection technologies, has materialized a very crucial challenge in terms of security. The anomaly-based intrusion detection systems, which for a long time have represented some of the most efficient solutions to detect intrusion attempts on a network, have to face this new and more complicated scenario. Well-known problems, such as the difficulty of distinguishing legitimate activities from illegitimate ones due to their similar characteristics and their high degree of heterogeneity, today have become even more complex, considering the increase in the network activity. After providing an extensive overview of the scenario under consideration, this work proposes a Local Feature Engineering (LFE) strategy aimed to face such problems through the adoption of a data preprocessing strategy that reduces the number of possible network event patterns, increasing at the same time their characterization. Unlike the canonical feature engineering approaches, which take into account the entire dataset, it operates locally in the feature space of each single event. The experiments conducted on real-world data showed that this strategy, which is based on the introduction of new features and the discretization of their values, improves the performance of the canonical state-of-the-art solutions. Full article

(This article belongs to the Special Issue Wireless Internet, Multimedia, and Artificial Intelligence: New Applications and Infrastructures)

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16 pages, 2833 KiB

Open AccessArticle

Visualization, Interaction and Analysis of Heterogeneous Textbook Resources

by Christian Scheel, Francesca Fallucchi and Ernesto William De Luca

Future Internet 2020, 12(10), 176; https://doi.org/10.3390/fi12100176 - 21 Oct 2020

Cited by 2 | Viewed by 2319

Abstract

Historically grown research projects, run by researchers with limited understanding of data sustainability, data reusability and standards, often lead to data silos. While the data are very valuable it can not be used by any service except the tool it was prepared for. [...] Read more.

Historically grown research projects, run by researchers with limited understanding of data sustainability, data reusability and standards, often lead to data silos. While the data are very valuable it can not be used by any service except the tool it was prepared for. Over the years, the number of such data graveyards will increase because new projects will always be designed from scratch. In this work we propose a Component Metadata Infrastructure (CMDI)-based approach for data rescue and data reuse, where data are retroactively joined into one repository minimizing the implementation effort of future research projects. Full article

(This article belongs to the Special Issue Data Science and Knowledge Discovery)

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13 pages, 1881 KiB

Open AccessArticle

Secure Communication for Uplink Cellular Networks Assisted with Full-Duplex Device-to-Device User

by Xin Song, Lin Xia, Siyang Xu and Yue Wang

Future Internet 2020, 12(10), 175; https://doi.org/10.3390/fi12100175 - 18 Oct 2020

Cited by 3 | Viewed by 2025

Abstract

In this paper, the secure communication based on the full-duplex (FD) device-to-device (D2D) in cellular networks is proposed. For the proposed scheme, the novel model is established, in which a D2D user is played as a relay operating in FD mode to assist [...] Read more.

In this paper, the secure communication based on the full-duplex (FD) device-to-device (D2D) in cellular networks is proposed. For the proposed scheme, the novel model is established, in which a D2D user is played as a relay operating in FD mode to assist in the secure transmission of uplink information. Considering that the D2D user as a relay is untrusted, D2D link rate maximization is formulated with the constraint of secrecy rate, which ensures the security of uplink cellular networks. To cope with the optimization problem, the optimal power allocation factors of the cellular user (CU) and the D2D user are jointly optimized. Firstly, by using the monotonicity of the objective function, the optimal solution of the power allocation factor at the D2D user can be obtained. Subsequently, the closed-form expression of the optimal power allocation factor at the CU is derived and verified that the solution is the global minimum point. Simulation results verify that the proposed scheme has better output performance than the conventional scheme. Full article

(This article belongs to the Section Cybersecurity)

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23 pages, 5216 KiB

Open AccessArticle

Research Trend on the Use of IT in Digital Addiction: An Investigation Using a Systematic Literature Review

by Flourensia Sapty Rahayu, Lukito Edi Nugroho, Ridi Ferdiana and Djoko Budiyanto Setyohadi

Future Internet 2020, 12(10), 174; https://doi.org/10.3390/fi12100174 - 18 Oct 2020

Cited by 6 | Viewed by 5908

Abstract

Despite the negative role of IT in digital addiction development, IT may have a positive role in dealing with digital addiction. The present study undertakes a systematic literature review to explore the state of play and the trend regarding the use of IT [...] Read more.

Despite the negative role of IT in digital addiction development, IT may have a positive role in dealing with digital addiction. The present study undertakes a systematic literature review to explore the state of play and the trend regarding the use of IT in digital addiction research. Using predefined keywords, the Scopus database was searched for relevant literature published from 2017 to 2020. The initial search found 1655 papers. Six stages of study selection were completed using a set of inclusion and exclusion criteria. The study selection and quality assessment process were applied, then 15 papers were selected for further review. The results show that addiction detection using IT is the most researched topic in digital addiction research. The most commonly used IT in the selected studies are AI methods and biosignal recording systems. Various approaches in detection, prevention, and intervention are suggested in the selected studies. The advantages and limitations of each approach are discussed. Based on these results, some future research directions are suggested. Full article

(This article belongs to the Special Issue The Future Internet of Medical Things)

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22 pages, 2123 KiB

Open AccessArticle

Immigration as a Divisive Topic: Clusters and Content Diffusion in the Italian Twitter Debate

by Salvatore Vilella, Mirko Lai, Daniela Paolotti and Giancarlo Ruffo

Future Internet 2020, 12(10), 173; https://doi.org/10.3390/fi12100173 - 15 Oct 2020

Cited by 16 | Viewed by 4292

Abstract

In this work, we apply network science to analyse almost 6 M tweets about the debate around immigration in Italy, collected between 2018 and 2019, when many related events captured media outlets’ attention. Our aim was to better understand the dynamics underlying the [...] Read more.

In this work, we apply network science to analyse almost 6 M tweets about the debate around immigration in Italy, collected between 2018 and 2019, when many related events captured media outlets’ attention. Our aim was to better understand the dynamics underlying the interactions on social media on such a delicate and divisive topic, which are the actors that are leading the discussion, and whose messages have the highest chance to reach out the majority of the accounts that are following the debate. The debate on Twitter is represented with networks; we provide a characterisation of the main clusters by looking at the highest in-degree nodes in each one and by analysing the text of the tweets of all the users. We find a strongly segregated network which shows an explicit interplay with the Italian political and social landscape, that however seems to be disconnected from the actual geographical distribution and relocation of migrants. In addition, quite surprisingly, the influencers and political leaders that apparently lead the debate, do not necessarily belong to the clusters that include the majority of nodes: we find evidence of the existence of a ‘silent majority’ that is more connected to accounts who expose a more positive stance toward migrants, while leaders whose stance is negative attract apparently more attention. Finally, we see that the community structure clearly affects the diffusion of content (URLs) by identifying the presence of both local and global trends of diffusion, and that communities tend to display segregation regardless of their political and cultural background. In particular, we observe that messages that spread widely in the two largest clusters, whose most popular members are also notoriously at the opposite sides of the political spectrum, have a very low chance to get visibility into other clusters. Full article

(This article belongs to the Special Issue Network analysis and computational social science: theory, methods, applications, future perspectives)

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15 pages, 4823 KiB

Open AccessArticle

An Efficient Resource Scheduling Strategy for V2X Microservice Deployment in Edge Servers

by Yanjun Shi, Yijia Guo, Lingling Lv and Keshuai Zhang

Future Internet 2020, 12(10), 172; https://doi.org/10.3390/fi12100172 - 15 Oct 2020

Cited by 1 | Viewed by 2630

Abstract

The fast development of connected vehicles with support for various V2X (vehicle-to-everything) applications carries high demand for quality of edge services, which concerns microservice deployment and edge computing. We herein propose an efficient resource scheduling strategy to containerize microservice deployment for better performance. [...] Read more.

The fast development of connected vehicles with support for various V2X (vehicle-to-everything) applications carries high demand for quality of edge services, which concerns microservice deployment and edge computing. We herein propose an efficient resource scheduling strategy to containerize microservice deployment for better performance. Firstly, we quantify three crucial factors (resource utilization, resource utilization balancing, and microservice dependencies) in resource scheduling. Then, we propose a multi-objective model to achieve equilibrium in these factors and a multiple fitness genetic algorithm (MFGA) for the balance between resource utilization, resource utilization balancing, and calling distance, where a container dynamic migration strategy in the crossover and mutation process of the algorithm is provided. The simulated results from Container-CloudSim showed the effectiveness of our MFGA. Full article

(This article belongs to the Special Issue Selected Papers from the International Conference on Communications, Signal Processing and Their Applications (ICCSPA ’20))

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31 pages, 2263 KiB

Open AccessArticle

NFV-Enabled Efficient Renewable and Non-Renewable Energy Management: Requirements and Algorithms

by Christian Tipantuña and Xavier Hesselbach

Future Internet 2020, 12(10), 171; https://doi.org/10.3390/fi12100171 - 14 Oct 2020

Cited by 8 | Viewed by 3383

Abstract

The increasing worldwide energy demand, the CO₂ emissions generated due to the production and use of energy, climate change, and the depletion of natural resources are important concerns that require new solutions for energy generation and management. In order to ensure energy [...] Read more.

The increasing worldwide energy demand, the CO₂ emissions generated due to the production and use of energy, climate change, and the depletion of natural resources are important concerns that require new solutions for energy generation and management. In order to ensure energy sustainability, measures, including the use of renewable energy sources, the deployment of adaptive energy consumption schemes, and consumer participation, are currently envisioned as feasible alternatives. Accordingly, this paper presents the requirements and algorithmic solutions for efficient management of energy consumption, which aims to optimize the use of available energy, whether or not it is 100% renewable, by minimizing the waste of energy. The proposal works within a Demand-Response environment, uses Network Functions Virtualization as an enabling technology, and leverages the massive connectivity of the Internet of Things provided by modern communications technologies. The energy consumption optimization problem is formulated as an Integer Linear Program. It is optimally solved while using a brute-force search strategy, defined as OptTs, to detect all concerns that are related to the problem. Given the

NP

-hard nature of the problem and the non-polynomial complexity of OptTs, some heuristic solutions are analyzed. Subsequently, a heuristic strategy, described as FastTs based on a pre-partitioning method, is implemented. The simulation results validate our proposed energy management solution. Exact and heuristic strategies, when deployed in the Network Functions Virtualization domain, demonstrate improvements in the way that energy is consumed, thereby offering an increase in service processing. The evaluation results also show that FastTs produces high-quality solutions that are close to those of OptTs while executing 230×–5000× faster. Full article

(This article belongs to the Special Issue Feature Papers for Future Internet—Internet of Things Section)

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14 pages, 1239 KiB

Open AccessArticle

Autonomous Navigation of a Solar-Powered UAV for Secure Communication in Urban Environments with Eavesdropping Avoidance

by Hailong Huang and Andrey V. Savkin

Future Internet 2020, 12(10), 170; https://doi.org/10.3390/fi12100170 - 10 Oct 2020

Cited by 9 | Viewed by 3397

Abstract

This paper considers the navigation of a solar-powered unmanned aerial vehicle (UAV) for securing the communication with an intended ground node in the presence of eavesdroppers in urban environments. To complete this task, the UAV needs to not only fly safely in the [...] Read more.

This paper considers the navigation of a solar-powered unmanned aerial vehicle (UAV) for securing the communication with an intended ground node in the presence of eavesdroppers in urban environments. To complete this task, the UAV needs to not only fly safely in the complex urban environment, but also take into account the communication performance with the intended node and eavesdroppers. To this end, we formulate a multi-objective optimization problem to plan the UAV path. This problem jointly considers the maximization of the residual energy of the solar-powered UAV at the end of the mission, the maximization of the time period in which the UAV can securely communicate with the intended node and the minimization of the time to reach the destination. We pay attention to the impact of the buildings in the urban environments, which may block the transmitted signals and also create some shadow region where the UAV cannot harvest energy. A Rapidly-exploring Random Tree (RRT) based path planning scheme is presented. This scheme captures the nonlinear UAV motion model, and is computationally efficient considering the randomness nature. From the generated tree, a set of possible paths can be found. We evaluate the security of the wireless communication, compute the overall energy consumption as well as the harvested amount for each path and calculate the time to complete the flight. Compared to a general RRT scheme, the proposed method enables a large time window for the UAV to securely transmit data. Full article

(This article belongs to the Special Issue Wireless Internet, Multimedia, and Artificial Intelligence: New Applications and Infrastructures)

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10 pages, 1790 KiB

Open AccessArticle

An Approach to Changing Competence Assessment for Human Resources in Expert Networks

by Mikhail Petrov

Future Internet 2020, 12(10), 169; https://doi.org/10.3390/fi12100169 - 3 Oct 2020

Cited by 1 | Viewed by 2613

Abstract

An expert network is a community of professionals in a specific field, united by an information system, in which different tasks are solved. One of the main tasks in expert networks is the selection of specialists with specified competencies for joint problem solving. [...] Read more.

An expert network is a community of professionals in a specific field, united by an information system, in which different tasks are solved. One of the main tasks in expert networks is the selection of specialists with specified competencies for joint problem solving. The main characteristic of an expert network member is a set of competencies, which includes both functional aspects and personal qualities. For this reason, the procedure for selecting specialists and ranking them is critical. Such a procedure uses specialists’ competence assessments from the expert network. If these assessments are out of date, the project results can be unsuccessful. This article proposes an approach aimed at automating the assessment of the specialists’ competencies based on the projects results. This approach consists of a reference model and an algorithm of competence assessment change for human resources. The paper also includes an algorithm evaluation on generated data. Full article

(This article belongs to the Section Techno-Social Smart Systems)

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37 pages, 2393 KiB

Open AccessReview

Phishing Attacks Survey: Types, Vectors, and Technical Approaches

by Rana Alabdan

Future Internet 2020, 12(10), 168; https://doi.org/10.3390/fi12100168 - 30 Sep 2020

Cited by 108 | Viewed by 27982

Abstract

Phishing attacks, which have existed for several decades and continue to be a major problem today, constitute a severe threat in the cyber world. Attackers are adopting multiple new and creative methods through which to conduct phishing attacks, which are growing rapidly. Therefore, [...] Read more.

Phishing attacks, which have existed for several decades and continue to be a major problem today, constitute a severe threat in the cyber world. Attackers are adopting multiple new and creative methods through which to conduct phishing attacks, which are growing rapidly. Therefore, there is a need to conduct a comprehensive review of past and current phishing approaches. In this paper, a review of the approaches used during phishing attacks is presented. This paper comprises a literature review, followed by a comprehensive examination of the characteristics of the existing classic, modern, and cutting-edge phishing attack techniques. The aims of this paper are to build awareness of phishing techniques, educate individuals about these attacks, and encourage the use of phishing prevention techniques, in addition to encouraging discourse among the professional community about this topic. Full article

(This article belongs to the Special Issue Security and Privacy in Social Networks and Solutions)

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16 pages, 1611 KiB

Open AccessArticle

Comparison of Machine Learning and Deep Learning Models for Network Intrusion Detection Systems

by Niraj Thapa, Zhipeng Liu, Dukka B. KC, Balakrishna Gokaraju and Kaushik Roy

Future Internet 2020, 12(10), 167; https://doi.org/10.3390/fi12100167 - 30 Sep 2020

Cited by 60 | Viewed by 9115

Abstract

The development of robust anomaly-based network detection systems, which are preferred over static signal-based network intrusion, is vital for cybersecurity. The development of a flexible and dynamic security system is required to tackle the new attacks. Current intrusion detection systems (IDSs) suffer to [...] Read more.

The development of robust anomaly-based network detection systems, which are preferred over static signal-based network intrusion, is vital for cybersecurity. The development of a flexible and dynamic security system is required to tackle the new attacks. Current intrusion detection systems (IDSs) suffer to attain both the high detection rate and low false alarm rate. To address this issue, in this paper, we propose an IDS using different machine learning (ML) and deep learning (DL) models. This paper presents a comparative analysis of different ML models and DL models on Coburg intrusion detection datasets (CIDDSs). First, we compare different ML- and DL-based models on the CIDDS dataset. Second, we propose an ensemble model that combines the best ML and DL models to achieve high-performance metrics. Finally, we benchmarked our best models with the CIC-IDS2017 dataset and compared them with state-of-the-art models. While the popular IDS datasets like KDD99 and NSL-KDD fail to represent the recent attacks and suffer from network biases, CIDDS, used in this research, encompasses labeled flow-based data in a simulated office environment with both updated attacks and normal usage. Furthermore, both accuracy and interpretability must be considered while implementing AI models. Both ML and DL models achieved an accuracy of 99% on the CIDDS dataset with a high detection rate, low false alarm rate, and relatively low training costs. Feature importance was also studied using the Classification and regression tree (CART) model. Our models performed well in 10-fold cross-validation and independent testing. CART and convolutional neural network (CNN) with embedding achieved slightly better performance on the CIC-IDS2017 dataset compared to previous models. Together, these results suggest that both ML and DL methods are robust and complementary techniques as an effective network intrusion detection system. Full article

(This article belongs to the Collection Computer Vision, Deep Learning and Machine Learning with Applications)

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17 pages, 2205 KiB

Open AccessArticle

A Survey of Defensive Measures for Digital Persecution in the Global South

by Louis Edward Papa and Thaier Hayajneh

Future Internet 2020, 12(10), 166; https://doi.org/10.3390/fi12100166 - 29 Sep 2020

Cited by 1 | Viewed by 2519

Abstract

This paper examines the phenomenon of digital persecution in the Global South and evaluates tools that defend against it. First, the paper explains the nature of persecution and its digital incarnation. It then provides a contextual overview of real-world instances of digital persecution [...] Read more.

This paper examines the phenomenon of digital persecution in the Global South and evaluates tools that defend against it. First, the paper explains the nature of persecution and its digital incarnation. It then provides a contextual overview of real-world instances of digital persecution in seven Global South countries. The possible defensive technologies against censorship and surveillance are discussed. The article goes on to discuss barriers to technology adoption in the Global South, explains the security implication of these difficulties, and examines the role that human computer interaction (HCI) metrics could play in overcoming these challenges. Finally, the paper surveys the viability of sixteen security tools in a Global South context. The survey results were mixed, with 37.5% of the reviewed tools being deemed to be inviable for use in the Global South to defend against persecution. Prescriptive recommendations are provided for creating security tools that are universal, simple, and effective. Full article

(This article belongs to the Special Issue Digital Society Challenges in Developing Countries)

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16 pages, 781 KiB

Open AccessArticle

Tourist Behaviour Analysis Based on Digital Pattern of Life—An Approach and Case Study

by Sergei Mikhailov and Alexey Kashevnik

Future Internet 2020, 12(10), 165; https://doi.org/10.3390/fi12100165 - 28 Sep 2020

Cited by 8 | Viewed by 4773

Abstract

The tourism industry has been rapidly growing over the last years and IT technologies have had a great affect on tourists as well. Tourist behaviour analysis has been the subject of different research studies in recent years. This paper presents the digital pattern [...] Read more.

The tourism industry has been rapidly growing over the last years and IT technologies have had a great affect on tourists as well. Tourist behaviour analysis has been the subject of different research studies in recent years. This paper presents the digital pattern of life concept which simplifies the tourist behaviour models’ construction and usage. The digital pattern of life defines the general concepts of tourist behaviour, connects the tourist and the digital world and allows us to track behaviour changes over time. A literature review of the current state of the research in selected fields is performed for identifying the existing problems. The case studies of behaviour analysis based on classification, clustering and time series events behaviour models are shown. An ontological approach and artificial neural networks are used during behaviour model construction, training and evaluation. The gathered results can be used by smart tourism service developers and business stakeholders. Full article

(This article belongs to the Section Techno-Social Smart Systems)

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28 pages, 1806 KiB

Open AccessArticle

Policy-Engineering Optimization with Visual Representation and Separation-of-Duty Constraints in Attribute-Based Access Control

by Wei Sun, Hui Su and Huacheng Xie

Future Internet 2020, 12(10), 164; https://doi.org/10.3390/fi12100164 - 27 Sep 2020

Cited by 9 | Viewed by 2507

Abstract

Recently, attribute-based access control (ABAC) has received increasingly more attention and has emerged as the desired access control mechanism for many organizations because of its flexibility and scalability for authorization management, as well as its security policies, such as separation-of-duty constraints and mutually [...] Read more.

Recently, attribute-based access control (ABAC) has received increasingly more attention and has emerged as the desired access control mechanism for many organizations because of its flexibility and scalability for authorization management, as well as its security policies, such as separation-of-duty constraints and mutually exclusive constraints. Policy-engineering technology is an effective approach for the construction of ABAC systems. However, most conventional methods lack interpretability, and their constructing processes are complex. Furthermore, they do not consider the separation-of-duty constraints. To address these issues in ABAC, this paper proposes a novel method called policy engineering optimization with visual representation and separation of duty constraints (PEO_VR&SOD). First, to enhance interpretability while mining a minimal set of rules, we use the visual technique with Hamming distance to reduce the policy mining scale and present a policy mining algorithm. Second, to verify whether the separation of duty constraints can be satisfied in a constructed policy engineering system, we use the method of SAT-based model counting to reduce the constraints and construct mutually exclusive constraints to implicitly enforce the given separation of duty constraints. The experiments demonstrate the efficiency and effectiveness of the proposed method and show encouraging results. Full article

(This article belongs to the Section Cybersecurity)

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15 pages, 3080 KiB

Open AccessArticle

Digital Twin Conceptual Model within the Context of Internet of Things

by A. R. Al-Ali, Ragini Gupta, Tasneem Zaman Batool, Taha Landolsi, Fadi Aloul and Ahmad Al Nabulsi

Future Internet 2020, 12(10), 163; https://doi.org/10.3390/fi12100163 - 26 Sep 2020

Cited by 74 | Viewed by 10659

Abstract

As the Internet of Things (IoT) is gaining ground and becoming increasingly popular in smart city applications such as smart energy, smart buildings, smart factories, smart transportation, smart farming, and smart healthcare, the digital twin concept is evolving as complementary to its counter [...] Read more.

As the Internet of Things (IoT) is gaining ground and becoming increasingly popular in smart city applications such as smart energy, smart buildings, smart factories, smart transportation, smart farming, and smart healthcare, the digital twin concept is evolving as complementary to its counter physical part. While an object is on the move, its operational and surrounding environmental parameters are collected by an edge computing device for local decision. A virtual replica of such object (digital twin) is based in the cloud computing platform and hosts the real-time physical object data, 2D and 3D models, historical data, and bill of materials (BOM) for further processing, analytics, and visualization. This paper proposes an end-to-end digital twin conceptual model that represents its complementary physical object from the ground to the cloud. The paper presents the proposed digital twin model’s multi-layers, namely, physical, communication, virtual space, data analytic and visualization, and application as well as the overlapping security layer. The hardware and software technologies that are used in building such a model will be explained in detail. A use case will be presented to show how the layers collect, exchange, and process the physical object data from the ground to the cloud. Full article

(This article belongs to the Special Issue Feature Papers for Future Internet—Internet of Things Section)

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16 pages, 2647 KiB

Open AccessArticle

An Internet of Things Model for Improving Process Management on University Campus

by William Villegas-Ch, Xavier Palacios-Pacheco and Milton Román-Cañizares

Future Internet 2020, 12(10), 162; https://doi.org/10.3390/fi12100162 - 25 Sep 2020

Cited by 9 | Viewed by 4103

Abstract

Currently, there are several emerging technologies that seek to improve quality of life. To achieve this, it is important to establish the various technologies’ fields of action and to determine which technology meets the conditions established by the environment in which it is [...] Read more.

Currently, there are several emerging technologies that seek to improve quality of life. To achieve this, it is important to establish the various technologies’ fields of action and to determine which technology meets the conditions established by the environment in which it is designed to operate in order to satisfy the needs of society. One type of environment is the university campus. This particular environment is conducive to the development and testing of technological innovations that might later be replicated in larger environments such as smart cities. The technology that has experienced the greatest development and introduction of applications is the Internet of Things. The wide variety of available devices and the wide reach of the Internet have become ideal parameters for the application of the Internet of Things in areas that previously required the work of people. The Internet of Things is seen as an assistant to, or a substitute for, processes that are generally routine and which require the effort of one or more people. This work focuses specifically on processes to improve administrative management in a university through the use of the Internet of Things. Full article

(This article belongs to the Special Issue Feature Papers for Future Internet—Internet of Things Section)

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16 pages, 1310 KiB

Open AccessArticle

The Value of Simple Heuristics for Virtualized Network Function Placement

by Zahra Jahedi and Thomas Kunz

Future Internet 2020, 12(10), 161; https://doi.org/10.3390/fi12100161 - 25 Sep 2020

Cited by 1 | Viewed by 2226

Abstract

Network Function Virtualization (NFV) can lower the CAPEX and/or OPEX for service providers and allow for quick deployment of services. Along with the advantages come some challenges. The main challenge in the use of Virtualized Network Functions (VNF) is the VNFs’ placement in [...] Read more.

Network Function Virtualization (NFV) can lower the CAPEX and/or OPEX for service providers and allow for quick deployment of services. Along with the advantages come some challenges. The main challenge in the use of Virtualized Network Functions (VNF) is the VNFs’ placement in the network. There is a wide range of mathematical models proposed to place the Network Functions (NF) optimally. However, the critical problem of mathematical models is that they are NP-hard, and consequently not applicable to larger networks. In wireless networks, we are considering the scarcity of Bandwidth (BW) as another constraint that is due to the presence of interference. While there exist many efforts in designing a heuristic model that can provide solutions in a timely manner, the primary focus with such heuristics was almost always whether they provide results almost as good as optimal solution. Consequently, the heuristics themselves become quite non-trivial, and solving the placement problem for larger networks still takes a significant amount of time. In this paper, in contrast, we focus on designing a simple and scalable heuristic. We propose four heuristics, which are gradually becoming more complex. We compare their performance with each other, a related heuristic proposed in the literature, and a mathematical optimization model. Our results demonstrate that while more complex placement heuristics do not improve the performance of the algorithm in terms of the number of accepted placement requests, they take longer to solve and therefore are not applicable to larger networks.In contrast, a very simple heuristic can find near-optimal solutions much faster than the other more complicated heuristics while keeping the number of accepted requests close to the results achieved with an NP-hard optimization model. Full article

(This article belongs to the Special Issue Machine Learning Advances Applied to Wireless Multi-hop IoT Networks)

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27 pages, 4282 KiB

Open AccessReview

Two-Factor Authentication Scheme for Mobile Money: A Review of Threat Models and Countermeasures

by Guma Ali, Mussa Ally Dida and Anael Elikana Sam

Future Internet 2020, 12(10), 160; https://doi.org/10.3390/fi12100160 - 24 Sep 2020

Cited by 32 | Viewed by 11774

Abstract

The proliferation of digital financial innovations like mobile money has led to the rise in mobile subscriptions and transactions. It has also increased the security challenges associated with the current two-factor authentication (2FA) scheme for mobile money due to the high demand. This [...] Read more.

The proliferation of digital financial innovations like mobile money has led to the rise in mobile subscriptions and transactions. It has also increased the security challenges associated with the current two-factor authentication (2FA) scheme for mobile money due to the high demand. This review paper aims to determine the threat models in the 2FA scheme for mobile money. It also intends to identify the countermeasures to overcome the threat models. A comprehensive literature search was conducted from the Google Scholar and other leading scientific databases such as IEEE Xplore, MDPI, Emerald Insight, Hindawi, ACM, Elsevier, Springer, and Specific and International Journals, where 97 papers were reviewed that focused on the topic. Descriptive research papers and studies related to the theme were selected. Three reviewers extracted information independently on authentication, mobile money system architecture, mobile money access, the authentication scheme for mobile money, various attacks on the mobile money system (MMS), threat models in the 2FA scheme for mobile money, and countermeasures. Through literature analysis, it was found that the threat models in the 2FA scheme for mobile money were categorised into five, namely, attacks against privacy, attacks against authentication, attacks against confidentiality, attacks against integrity, and attacks against availability. The countermeasures include use of cryptographic functions (e.g., asymmetric encryption function, symmetric encryption function, and hash function) and personal identification (e.g., number-based and biometric-based countermeasures). This review study reveals that the current 2FA scheme for mobile money has security gaps that need to be addressed since it only uses a personal identification number (PIN) and a subscriber identity module (SIM) to authenticate users, which are susceptible to attacks. This work, therefore, will help mobile money service providers (MMSPs), decision-makers, and governments that wish to improve their current 2FA scheme for mobile money. Full article

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Future Internet, Volume 12, Issue 10 (October 2020) – 18 articles

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