Future Internet, Volume 12, Issue 4 (April 2020) – 16 articles

The English language is the most dominant language in the Western world and its influence can be noticed in every aspect of human communication. It’s increasing diffusion, especially since the turn of the century, is hard to measure with conventional means. The present research studies the use of language in websites of European Union (EU) member states, in order to collect data about the prevalence of the English language in the different countries and regions of the European Union. To achieve a realistic representation of today’s landscape of the European Web, this study uses a vast population of websites and a representative sampling size and methodology. By analyzing and processing the findings from over 100,000 websites from every country in the EU, a solid foundation is set that is used to explore the dominance of the English language in the European World Wide Web in general. This is the first study that examines the presence of English content in the websites of all EU member countries and provides statistical evidence regarding the ratio of English content availability for each country. Conclusively, the results of the research demonstrate that the English language is available on more than one quarter of all websites of non-English speaking EU member states. Moreover, it is available in the vast majority of multilingual and bilingual websites, while at the same time being the only language that is available in a number of monolingual websites. In addition, it is shown preference over the national language in a significant number of cases. A moderate negative correlation is found between a member state’s population and the availability of English in these countries’ websites and the same holds true for a member state’s Gross Domestic Product (GDP). Both these correlations indicate that smaller countries tend to provide more content in English in order to establish a stronger presence in the international environment. Taking into account the role of language in the expression of national identity, this study provides data and insights which may contribute to the discussion about the changes underway in the national identity of EU member states. Full article

Integrated learning can be used to combine weak classifiers in order to improve the effect of emotional classification. Existing methods of emotional classification on micro-blogs seldom consider utilizing integrated learning. Personality can significantly influence user expressions but is seldom accounted for in emotional classification. In this study, a micro-blog emotion classification method is proposed based on a personality and bagging algorithm (PBAL). Introduce text personality analysis and use rule-based personality classification methods to divide five personality types. The micro-blog text is first classified using five personality basic emotion classifiers and a general emotion classifier. A long short-term memory language model is then used to train an emotion classifier for each set, which are then integrated together. Experimental results show that compared with traditional sentiment classifiers, PBAL has higher accuracy and recall. The F value has increased by 9%. Full article

Fuzz testing is a simple automated software testing approach that discovers software vulnerabilities at a high level of performance by using randomly generated seeds. However, it is restrained by coverage and thus, there are chances of finding bugs entrenched in the deep execution paths of the program. To eliminate these limitations in mutational fuzzers, patching-based fuzzers and hybrid fuzzers have been proposed as groundbreaking advancements which combine two software testing approaches. Despite those methods having demonstrated high performance across different benchmarks such as DARPA CGC programs, they still present deficiencies in their ability to analyze deeper code branches and in bypassing the roadblocks checks (magic bytes, checksums) in real-world programs. In this research, we design DeepDiver, a novel transformational hybrid fuzzing tool that explores deeply hidden software vulnerabilities. Our approach tackles limitations exhibited by existing hybrid fuzzing frameworks, by negating roadblock checks (RC) in the program. By negating the RCs, the hybrid fuzzer can explore new execution paths to trigger bugs that are hidden in the abysmal depths of the binary. We combine AFL++ and concolic execution engine and leveraged the trace analyzer approach to construct the tree for each input to detect RCs. To demonstrate the efficiency of DeepDiver, we tested it with the LAVA-M dataset and eight large real-world programs. Overall, DeepDiver outperformed existing software testing tools, including the patching-based fuzzer and state-of-the-art hybrid fuzzing techniques. On average, DeepDiver discovered vulnerabilities 32.2% and 41.6% faster than QSYM and AFLFast respectively, and it accomplished in-depth code coverage. Full article

Today, the Internet of Things (IoT) is mainly associated with vertically integrated systems that often are closed and fragmented in their applicability. To build a better IoT ecosystem, the open IoT platform has become a popular term in the recent years. However, this term is usually used in an intuitive way without clarifying the openness aspects of the platforms. The goal of this paper is to characterize the openness types of IoT platforms and investigate what makes them open. We conducted a systematic mapping study by retrieving data from 718 papers. As a result of applying the inclusion and exclusion criteria, 221 papers were selected for review. We discovered 46 IoT platforms that have been characterized as open, whereas 25 platforms are referred as open by some studies rather than the platforms themselves. We found that the most widely accepted and used open IoT platforms are NodeMCU and ThingSpeak that together hold a share of more than 70% of the declared open IoT platforms in the selected papers. The openness of an IoT platform is interpreted into different openness types. Our study results show that the most common openness type encountered in open IoT platforms is open-source, but also open standards, open APIs, open data and open layers are used in the literature. Finally, we propose a new perspective on how to define openness in the context of IoT platforms by providing several insights from the different stakeholder viewpoints. Full article

Website users have increasingly high expectations regarding website quality, starting from performance and ending up with the content. This article provides a list and characteristics of selected website quality indices and testing applications that are available free of charge. Aggregated website quality indices were characterised based on a review of various source materials, including the academic literature and Internet materials. Aggregated website quality indices are usually developed with a less specialised user (customer) searching for descriptive information in mind. Their presentation is focused on aesthetic sensations. Most frequently, their values are expressed in points or percent. Many of these indices appear to be of little substantive value, as they present approximate, estimated values. These indices, however, are of great marketing value instead. Specific (“single”) indices are of a specialised nature. They are more difficult to interpret and address the subtle aspects of website and web application functioning. They offer great value to designers and software developers. They indicate critical spots which affect the website quality. Most of them are expressed precisely, often up to two or three decimal places, in specific units. Algorithmic tests for website quality, whose results are presented using indices, enable a reduction in the cost intensiveness of tests as well as an increase in their number and frequency, as the tests are repetitive and their number is not limited. What is more, they allow the results to be compared. Full article

Data publishing is a challenging task for privacy preservation constraints. To ensure privacy, many anonymization techniques have been proposed. They differ in terms of the mathematical properties they verify and in terms of the functional objectives expected. Disassociation is one of the techniques that aim at anonymizing of set-valued datasets (e.g., discrete locations, search and shopping items) while guaranteeing the confidentiality property known as $k^m$ -anonymity. Disassociation separates the items of an itemset in vertical chunks to create ambiguity in the original associations. In a previous work, we defined a new ant-based clustering algorithm for the disassociation technique to preserve some items associated together, called utility rules, throughout the anonymization process, for accurate analysis. In this paper, we examine the disassociated dataset in terms of knowledge extraction. To make data analysis easy on top of the anonymized dataset, we define neighbor datasets or in other terms datasets that are the result of a probabilistic re-association process. To assess the neighborhood notion set-valued datasets are formalized into trees and a tree edit distance (TED) is directly applied between these neighbors. Finally, we prove the faithfulness of the neighbors to knowledge extraction for future analysis, in the experiments. Full article

Recently, IoT technology, low power networking technology for IoT, and geopositioning systems are very useful tools for future applications. One of the applications is the logistics system, especially for the point to point delivery. The current parcel delivery system is delivered through the logistics hub despite latent economic disadvantages in terms of delivery time and delivery distance. The major disadvantage of current hub and spoke delivery system is that individual parcels must go to the logistics hub first even if the origin and destination are nearby or within a distance that can be delivered through the hub. These sorts of delivery are inefficient and increase total expense of delivery in terms of delivery time and delivery costs. We designed a new delivery system of point to point delivery using IoT technology and end-to-end IoT platform based on ThingPlug and LoRa technology for fast delivery and less cost of delivery. We designed an IoT device that can be part of parcels or attached to parcels, which have various functionalities including the capability to understand current delivery routes with the use of geopositioning systems. In addition, we addressed the difficulties with issues such as linking IoT device into IoT platforms and designing IoT device functionalities. We also showed methods to improve the efficiency of IoT based parcel delivery systems. The proposed system may improve economics of parcel delivery system by reducing travel distance for delivery and dissipation of delivery time. Full article

The latest manifestation of “all connected world" is the Internet of Things (IoT), and Internet of Vehicles (IoV) is one of the key examples of IoT these days. In Social IoV (SIoV), each vehicle is treated as a social object where it establishes and manages its own Social Network (SN). Incidentally, most of the SIoV research in the literature is related to proximity-based connectivity and interactions. In this paper, we bring people in the loop by incorporating their SNs. While emphasizing a recommendation scenario, in which vehicles may require recommendations from SNs of their owners (in addition to their own SIoV), we proposed an agent-based model of information sharing (for context-based recommendations) on a hypothetical population of smart vehicles. Some important hypotheses were tested using a realistic simulation setting. The simulation results reveal that a recommendation using weak ties is more valuable than a recommendation using strong ties in pure SIoV. The simulation results also demonstrate that recommendations using the most-connected person in the social network are not more valuable than recommendation using a random person in the social network. The model presented in this paper can be used to design a multi-scale recommendation system, which uses SIoV and a typical SN in combination. Full article

The present article describes the behavioral model of blockchain services; their reliability is confirmed on the basis of experimental data. The authors identify the main technical characteristics and features associated with data transmission through the network. The authors determine the network scheme, working with blockchain transactions and the dependence of network characteristics on application parameters. They analyze the application of this model for the detection of the blockchain service and the possibility of the existing security mechanisms of this technology being evaded. Furthermore, the article offers recommendations for hiding the blockchain traffic profile to significantly complicate its identification in the data network. Full article

This paper presents SemSim^e, a method based on semantic similarity for searching over a set of digital resources previously annotated by means of concepts from a weighted reference ontology. SemSim^e is an enhancement of SemSim and, with respect to the latter, it uses a frequency approach for weighting the ontology, and refines both the user request and the digital resources with the addition of rating scores. Such scores are High, Medium, and Low, and in the user request indicate the preferences assigned by the user to each of the concepts representing the searching criteria, whereas in the annotation of the digital resources they represent the levels of quality associated with each concept in describing the resources. The SemSim^e has been evaluated and the results of the experiment show that it performs better than SemSim and an evolution of it, referred to as $SemSi{m}_{RV}$ . Full article

Android malware has become the topmost threat for the ubiquitous and useful Android ecosystem. Multiple solutions leveraging big data and machine-learning capabilities to detect Android malware are being constantly developed. Too often, these solutions are either limited to research output or remain isolated and incapable of reaching end users or malware researchers. An earlier work named PACE (Platform for Android Malware Classification and Performance Evaluation), was introduced as a unified solution to offer open and easy implementation access to several machine-learning-based Android malware detection techniques, that makes most of the research reproducible in this domain. The benefits of PACE are offered through three interfaces: Representational State Transfer (REST) Application Programming Interface (API), Web Interface, and Android Debug Bridge (ADB) interface. These multiple interfaces enable users with different expertise such as IT administrators, security practitioners, malware researchers, etc. to use their offered services. In this paper, we propose PACER (Platform for Android Malware Classification, Performance Evaluation, and Threat Reporting), which extends PACE by adding threat intelligence and reporting functionality for the end-user device through the ADB interface. A prototype of the proposed platform is introduced, and our vision is that it will help malware analysts and end users to tackle challenges and reduce the amount of manual work. Full article

Safeguarding both safety and cybersecurity is paramount to the smooth and trustworthy operation of contemporary cyber physical systems, many of which support critical functions and services. As safety and security have been known to be interdependent, they need to be jointly considered in such systems. As a result, various approaches have been proposed to address safety and cybersecurity co-engineering in cyber physical systems. This paper provides a comprehensive survey of safety and cybersecurity co-engineering methods, and discusses relevant open issues and research challenges. Despite the extent of the existing literature, several aspects of the subject still remain to be fully addressed. Full article

Modern datacenters are reinforcing the computational power and energy efficiency by assimilating field programmable gate arrays (FPGAs). The sustainability of this large-scale integration depends on enabling multi-tenant FPGAs. This requisite amplifies the importance of communication architecture and virtualization method with the required features in order to meet the high-end objective. Consequently, in the last decade, academia and industry proposed several virtualization techniques and hardware architectures for addressing resource management, scheduling, adoptability, segregation, scalability, performance-overhead, availability, programmability, time-to-market, security, and mainly, multitenancy. This paper provides an extensive survey covering three important aspects—discussion on non-standard terms used in existing literature, network-on-chip evaluation choices as a mean to explore the communication architecture, and virtualization methods under latest classification. The purpose is to emphasize the importance of choosing appropriate communication architecture, virtualization technique and standard language to evolve the multi-tenant FPGAs in datacenters. None of the previous surveys encapsulated these aspects in one writing. Open problems are indicated for scientific community as well. Full article

The amalgamation of Vehicular Ad hoc Network (VANET) with the Internet of Things (IoT) leads to the concept of the Internet of Vehicles (IoV). IoV forms a solid backbone for Intelligent Transportation Systems (ITS), which paves the way for technologies that better explain about traffic efficiency and their management applications. IoV architecture is seen as a big player in different areas such as the automobile industry, research organizations, smart cities and intelligent transportation for various commercial and scientific applications. However, as VANET is vulnerable to various types of security attacks, the IoV structure should ensure security and efficient performance for vehicular communications. To address these issues, in this article, an authentication-based protocol (A-MAC) for smart vehicular communication is proposed along with a novel framework towards an IoV architecture model. The scheme requires hash operations and uses cryptographic concepts to transfer messages between vehicles to maintain the required security. Performance evaluation helps analyzing its strength in withstanding various types of security attacks. Simulation results demonstrate that A-MAC outshines other protocols in terms of communication cost, execution time, storage cost, and overhead. Full article

The effective response to the proliferation and growing diversity and sophistication of cyber threats requires a broad spectrum of competencies, human, technological and financial resources that are in the powers of very few countries. The European Union is addressing this challenge through an initiative to establish one or more cybersecurity competence networks. A number of existing technologies can support collaboration in networked organisations; however, network governance remains a challenge. The study presented in this article aimed to identify and prioritise network governance issues. Towards that purpose, qualitative and quantitative methods were applied in the analysis of norms and regulations, statutory documents of existing networks, academic sources and interviews with representatives of funding organisations and potential major customers. The comprehensiveness and complementarity of these primary sources allowed to identify 33 categories of governance issues and group them in four tiers, indicative of the respective priority level. The results of the study are currently used to inform and orient the development of alternative models for governance of a cybersecurity network and a set of criteria for their evaluation. They will support informed decision-making on the most appropriate governance model of a future networked organisation, evolving from a project consortium. Full article

Fog computing (FC) is used to reduce the energy consumption and latency for the heterogeneous communication approaches in the smart cities’ applications of the Internet of Everything (IoE). Fog computing nodes are connected through wired or wireless medium. The goal of smart city applications is to develop the transaction relationship of real-time response applications. There are various frameworks in real-world to support the IoE in smart-cities but they face the issues like security, platform Independence, multi-application assistance, and resource management. This article is motivated from the Blockchain and Fog computing technologies and presents a secured architecture Blockchain and Fog-based Architecture Network (BFAN) for IoE applications in the smart cities. The proposed architecture secures sensitive data with encryption, authentication, and Blockchain. It assists the System-developers and Architects to deploy the applications in smart city paradigm. The goal of the proposed architecture is to reduce the latency and energy, and ensure improved security features through Blockchain technology. The simulation results demonstrate that the proposed architecture performs better than the existing frameworks for smart-cities. Full article