Data Access Services Research Articles

A novel blockchain-based privacy-preserving framework for online social networks

ABSTRACT Online social networks (OSNs) are nowadays an important field of applications thanks to the recent surge in online interaction. However, the illegal disclosure of user's private data can cause damaging consequences and even threaten the safety of users' life. The privacy issues of OSNs have become a matter of great concern for many people. In recent years, there are some research works to address this privacy issue, yet they do not always focus on providing the normal social network services for users, such as data sharing, data retrieval and data access services. Therefore, it is a challenge to ensure the security of sensitive data while providing efficient and privacy-preserving social network services for users. In this paper, we propose a novel blockchain-based privacy-preserving framework for online social networks, called BPP. Combined blockchain and public-key cryptography technique, the BPP framework can achieve secure data sharing, data retrieving, and data accessing with fairness and without worrying about potential damage to users' interest. Specifically, based on blockchain and public key encryption with keyword search technique, a secure, fair and efficient keyword search algorithm is proposed, with which the BBP framework realises privacy preservation of user's query and then obtain accurate query results with assurance and without needing for any further verification operation in online social network. Finally, we implement a prototype of our framework and deploy it to a locally simulated network. The extensive experiments and security analysis demonstrate the security, efficacy and efficiency of our proposed framework.

Auditable and Times limitable Secure Data Access Control for Cloud-based Industrial Internet of Things

Recently, the rapid development of Internet of things (IoT) and cloud computing technologies have greatly facilitated various industrial applications and Industrial IoT (IIoT). The widely deployed IIoT devices and large capacity of cloud significantly benefit for and bring convenience to various industrial sectors. However, there exist a large number of concerns about data security in IIoT, especially when a majority of sensitive IIoT data is shared in cloud. Although as one of the most promising technique, Ciphertext-Policy Attribute-Based Encryption (CP-ABE) can provide fine-grained access control for IIoT data shared in cloud, there are still many drawbacks which impede the direct adoption of conventional CP-ABE. On the one hand, unlimited IIoT data access times may disable data access service of cloud and bring serious consequences. On the other hand, the access policies of ciphertexts usually consist of much sensitive information and cause privacy exposure. Moreover, the high computation overhead also extremely hinders resource-limited users in IIoT applications. To solve these problems, we propose TAHP-CP-ABE, a k-times and auditable hidden-policy CP-ABE scheme which is suitable for resource-limited users and privacy-aware access policies with data access times limitation in IIoT applications. Specifically, TAHP-CP-ABE preserves the privacy of access policies by hiding only attribute values and realizes limited access times as well as efficient IIoT ciphertexts decryption with decryption test and outsourced decryption. The security analysis and experimental results indicate that TAHP-CP-ABE is secure, efficient and practical.

Radio Wave Propagation and WSN Deployment in Complex Utility Tunnel Environments.

The significant growth of wireless communications systems in the last years has led to the adoption of a wide range of applications not only for the general public but, also, including utilities and administrative authorities. In this context, the notable expansion of new services for smart cities requires, in some specific cases, the construction of underground tunnels in order to enable the maintenance and operation works of utilities, as well as to reduce the visual impact within the city center. One of the main challenges is that, inherently, underground service tunnels lack coverage from exterior wireless communication systems, which can be potentially dangerous for maintenance personnel working within the tunnels. Accordingly, wireless coverage should be deployed within the underground installation in order to guarantee real-time connectivity for safety maintenance, remote surveillance or monitoring operations. In this work, wireless channel characterization for complex urban tunnel environments was analyzed based on the assessment of LoRaWAN and ZigBee technologies operating at 868 MHz. For that purpose, a real urban utility tunnel was modeled and simulated by means of an in-house three-dimensional ray-launching (3D-RL) code. The utility tunnel scenario is a complex and singular environment in terms of radio wave propagation due to the limited dimensions and metallic elements within it, such as service trays, user pathways or handrails, which were considered in the simulations. The simulated 3D-RL algorithm was calibrated and verified with experimental measurements, after which, the simulation and measurement results showed good agreement. Besides, a complete wireless sensor network (WSN) deployment within the tunnels was presented, providing remote cloud data access applications and services, allowing infrastructure security and safety work conditions. The obtained results provided an adequate radio planning approach for the deployment of wireless systems in complex urban utility scenarios, with optimal coverage and enhanced quality of service.

A Canopen-Based Gateway and Energy Monitoring System for Electric Bicycles

The limitation of battery capacity is a cause of range anxiety that reduces the wide use of electric bicycles (e-bikes). Therefore, many works have developed systems that provide assistance to cyclists to deal with the range anxiety problem. However, these systems may have limited applications since they can only work with the e-bike manufacturers’ hardware and communication protocols. This paper proposes an energy monitoring system (EMS) for e-bikes, which is based on EnergyBus, a standardized hardware and communication protocol for e-bikes. EnergyBus standard is based on controller area network (CAN) bus and CANopen protocols. EMS comprises a gateway connected to EnergyBus of e-bike and an EMS application installed on a smart device that connects to the gateway via Bluetooth. The gateway provides CAN bus monitoring and CANopen device data access services to the smart device. These services are modeled to determine gateway parameters to ensure the efficient performance of the gateway and to keep the working status of the monitored e-bike safe. The EMS application provides the cyclist information about battery status, rider efforts, and other related information such as distance and speed. Experimental results show that the proposed gateway can monitor data in real-time and ensure monitored system safety.

In the News

Welcome to the June 2020 issue of C&RL News. Every two years, ACRL’s Research Planning and Review Committee produces their “Top trends in academic libraries.” The 2020 edition discusses change management; evolving integrated library systems; learning analytics; machine learning and AI; the state of open access and research data services; social justice, critical librarianship, and critical digital pedagogy; streaming media; and student wellbeing. Many thanks to the committee for pulling together this important survey of the current landscape of academic and research librarianship.

EUMETSAT – Effective Search and Access APIs for EO Data to Knowledge Value Chains

The EUMETSAT Data Services Roadmap included the implementation of an EO OnLine Data Access (OLDA) service offering search, discovery, visualization and access of EO products. conterra/N52 (part of a consortium led by CGI) have developed OpenSearch-EO- and REST-based Web API´s to browse, search and discover the products which are stored in a cloud-based storage system. The data is indexed for searching based on extended ISO/OGC metadata.

Chaotic assessment of the key performance indicators for a GSM Network congestion in an election period in Nigeria

This paper investigates the chaos-based assessment of the Key performance Indicators (KPIs) for the Cellular network congestion during and after 2011 People Democratic Party (PDP) presidential primary election in Eagle Square within Abuja and its environs. Chaotic quantifiers such as average mutual information, Lyapunov exponents and specific attenuation were employed to study the congestion rate or dynamical state of the network. The chaotic assessment of the Wideband Code Division Multiplexing Access (WCDMA) data services provided by MTN network using KPIs are reported. The data retrieved from the three Base Transceiver Stations (BTSs) were used to analyse the performance of the network. The results revealed the state of dynamical behaviour of the congestion during the study period.
 Keywords: Key performance Indicators (KPIs); Wideband Code Division Multiplexing Access (WCDMA); Global System of Mobile communication (GSM); Base Transceiver Station (BTS); Chaotic Quantifiers

EDAS (EGNOS Data Access Service) Differential GNSS Corrections: A Reliable Free-of-Charge Alternative for Precision Farming in Europe

Abstract EDAS (EGNOS Data Access Service) is the EGNOS internet broadcast service, which provides free of charge access to the data collected and generated by the EGNOS infrastructure. EDAS disseminates over the Internet, both in real time and via an FTP archive, the raw data of the GPS, GLONASS (no commitment on GLONASS data is provided (1)) and EGNOS GEO satellites collected by the receivers located at the EGNOS reference stations, which are mainly distributed over Europe and North Africa. The EDAS services offer several types of GNSS data in various protocols and formats, such as DGNSS corrections. This paper reports on the results of some in-field tests conducted by ESSP and Topcon Agriculture to confirm the suitability of EDAS DGNSS corrections for precision farming in Europe. The European Commission (EC) is the owner of EGNOS system (including EDAS) and has delegated the exploitation of EGNOS to the European GNSS Agency (GSA). EDAS service provision is performed by ESSP, as EGNOS Services Provider, under contract with the GSA, the EGNOS program manager. In the ENC 2018 article “EDAS (EGNOS Data Access Service): Differential GPS corrections performance test with state-of-the-art precision agriculture system”, ESSP and Topcon Agriculture presented the results of the first in-field test conducted in a dynamic and real-life environment in the summer of 2017. The test results indicated that the EDAS DGNSS corrections could enable a reliable pass-to-pass accuracy performance for a wide range of precision agriculture applications and become an attractive solution for cereal farms, when the farm is located in the vicinity of an EGNOS reference station. In particular, Topcon Agriculture acknowledged that the observed performance was sufficient to support the following precision agriculture applications: spraying and spreading of any crop type, tilling and harvesting of cereal. Then, ESSP and Topcon Agriculture engaged in additional testing activities to further characterise the EDAS DGPS performance in different scenarios (i.e. at various European locations and with a variety of distances between the designated farm and the target EGNOS reference station). In each test, multiple runs with the rover tractors have been performed over the reference patterns predefined in the Topcon guidance systems. Data recorded during the tests has been analysed in detail, looking at the key performance indicators (e.g. cross track error and pass-to-pass performance) that characterize the EDAS DGPS performance for precision agriculture applications. Different techniques for the computation of the pass-to-pass accuracy performance have been used, including a procedure to measure live in the field and a post-processing alternative. The diversity of scenarios available allows drawing conclusions on the applicability of EDAS DGPS corrections (in terms of maximum distance from the target EGNOS station) for precision agriculture and also understanding the impact of operationally relevant aspects such as the quality of the mobile internet coverage (highly variable across Europe). The EDAS system and its architecture, the main types of data disseminated through EDAS services and the online information available to the EDAS users are introduced in this paper. In particular, the EDAS Ntrip service is described in detail, since it provides the differential corrections to the GPS and GLONASS satellites at the EGNOS reference stations in RTCM format, which are the basis for the present study. The article also reports on the results of the latest tests, which have been performed using Topcon receivers, vehicles and auto-steering systems. In all cases, two different Topcon guidance systems on board tractors were running simultaneously to assess the EDAS DGPS positioning performance with respect to a the reference provided by a top-performing RTK-based Topcon solution. The objective of this paper is to draw conclusions on the use of EDAS DGPS corrections as a reliable free-of-charge alternative for precision farming in Europe (especially for cereal farms), based on the available performance results from the testing campaign and the feedback from the involved precision agriculture experts.

Privacy Preservation of Healthcare Data in Hybrid Cloud using a Hybrid Meta-Heuristics Based Sanitization Technique

Over the recent years, the expansion of cloud computing services enable hospitals and institutions to transit their healthcare data to the cloud, thus it provides the worldwide data access and on-demand high quality services at a cheaper rate. Despite the benefits of healthcare cloud services, the associated privacy issues are widely concerned by individuals and governments. Privacy risks rise when outsourcing personal healthcare records to cloud due to the sensitive nature of health information and the social and legal implications for its disclosure. Over the recent years, a privacy-preserving data mining (PPDM) technique has become a critical issue for the problems. Our goal is to design a privacy-preserving outsourcing framework under the hybrid cloud model. In this work we propose a Hybrid Ant Colony Optimization and Gravitational Search Algorithm (ACOGSA) to express the problem of hiding sensitive data through transaction deletion. Thus, it reduces the side effects of the hybrid cloud. Substantive experiments will be carried to compare the performance of the designed algorithm with the state-of-the-art approaches in terms of the side effects and database similarity (integrity). Over the past to sanitize the databases used for hiding sensitive information, a few heuristic approaches have been proposed. The method used for the comparison involves GA, PSO, ACO, and Firefly framework.

Privacy Preservation of Healthcare Data in Hybrid Cloud Using a Hybrid Meta-Heuristics Based Sanitization Technique

Over the recent years, the expansion of cloud computing services enable hospitals and institutions to transit their healthcare data to the cloud, thus it provides the worldwide data access and on-demand high quality services at a cheaper rate. Despite the benefits of healthcare cloud services, the associated privacy issues are widely concerned by individuals and governments. Privacy risks rise when outsourcing personal healthcare records to cloud due to the sensitive nature of health information and the social and legal implications for its disclosure. Over the recent years, a privacy-preserving data mining (PPDM) technique has become a critical issue for the problems. Our goal is to design a privacy-preserving outsourcing framework under the hybrid cloud model. In this work we propose a Hybrid Ant Colony Optimization and Gravitational Search Algorithm (ACOGSA) to express the problem of hiding sensitive data through transaction deletion. Thus, it reduces the side effects of the hybrid cloud. Substantive experiments will be carried to compare the performance of the designed algorithm with the state-of-the-art approaches in terms of the side effects and database similarity (integrity). Over the past to sanitize the databases used for hiding sensitive information, a few heuristic approaches have been proposed. The method used for the comparison involves GA, PSO, ACO, and Firefly framework.

The European Nucleotide Archive in 2019.

The European Nucleotide Archive (ENA, https://www.ebi.ac.uk/ena) at the European Molecular Biology Laboratory’s European Bioinformatics Institute provides open and freely available data deposition and access services across the spectrum of nucleotide sequence data types. Making the world’s public sequencing datasets available to the scientific community, the ENA represents a globally comprehensive nucleotide sequence resource. Here, we outline ENA services and content in 2019 and provide an insight into selected key areas of development in this period.

Real world evidence for European health policy-making: making the case for interoperability

Abstract Background The foundations of evidence-based health policy-making are transitioning from the use of partial evidence yielded elsewhere and the application of heuristic rules, to the development of learning systems based on the reuse of routine data collected by the same institutions that have to implement those policies. Supporting that transition, the scientific production of real-world evidence (RWE) is becoming pivotal, particularly in international policy-making. However, leveraging the immense wealth of data curated in European public institutions, requires the development of a new world-class research infrastructure and a supporting interoperability framework (IOF). Methods Based on the European Interoperability Framework (EIF) legal, organizational, semantic, and technical issues are being assessed. While legal, organizational and technical topics are analyzed from the perspective of the type of infrastructure, centralized or federated, to be developed, semantic interoperability is explored using three case studies on the linkage of different real world data sources: for characterizing resilient populations, studying the burden of dementia, and the effectiveness of stroke care pathways. Results Preliminary assessments advocate for the development of a federated infrastructure where data remain in house and research questions, data access and interoperability services are shared according to the capacity of each specific partner in the federation. Interoperability services for such an infrastructure should cover: a) the development and maintenance of a common data model to assure semantic interoperability, b) the development of self-contained distributed analytical pipelines; and c) the implementation of a training program aimed at increasing the capacity of each RI hub. Conclusions An interoperable federated research infrastructure is required to leverage the potential of real world data for European health policy-making. InfAct is paving the way.

Paving the Way to Increased Interoperability of Earth Observations Data Cubes

Earth observations data cubes (EODCs) are a paradigm transforming the way users interact with large spatio-temporal Earth observation (EO) data. It enhances connections between data, applications and users facilitating management, access and use of analysis ready data (ARD). The ambition is allowing users to harness big EO data at a minimum cost and effort. This significant interest is illustrated by various implementations that exist. The novelty of the approach results in different innovative solutions and the lack of commonly agreed definition of EODC. Consequently, their interoperability has been recognized as a major challenge for the global change and Earth system science domains. The objective of this paper is preventing EODC from becoming silos of information; to present how interoperability can be enabled using widely-adopted geospatial standards; and to contribute to the debate of enhanced interoperability of EODC. We demonstrate how standards can be used, profiled and enriched to pave the way to increased interoperability of EODC and can help delivering and leveraging the power of EO data building, efficient discovery, access and processing services.

Advancement and Design of Robotic Manipulator Control Structures on Cyber Physical Production System

Generally, the cyber-physical production system (CPPs) is a device that is meticulous or monitored by computer-based algorithms, firmly integrated with an Internet and its users. This system has carried with it an increasing utilization of robotics in common producing environments. One of the most important significant guidelines in the development of communication technologies and computer science and information is characterized by Cyber Physical Systems (CPSs) which are structures of collaborating computational articles which are in demanding connection with the adjacent physical world and its ongoing processes, giving and using, at the same time, data access and data process services accessible on the internet. The methodology to meet this demand is to be democratizing robotics by creating cheaper high customizable robots which can be instigated by small, medium and high enterprises. To overcome this problem, this research stares at using rapid prototyping methods for the growth of customizable robotic manipulators which can be carried out in the cyber physical production system. This study therefore contributes an approach of scheming connected and rapid prototype robotic manipulators and this methodology considers both hardware and software development mandatory for executing a robotic manipulator. Besides generative design, an evolutionary and artificial intelligence based approach is used to plan the link components between the robot joints. This component has been recognized as the ideal to be intended with this approach as its benefits most of the reproductive design approach joined with rapid prototyping. This paper also discovers a robotic manipulator control structures based on Ethernet control skills for implementation within a Cyber physical production system.

Cloud Computing : An Overview

Cloud computing is a technology that allows user to use computation, storage and data access services. Cloud computing is about moving services, computation and data for cost and business advantage. It is a location-transparent, centralized facility. These services are provided on the basis of cast. By making data available in the cloud, it can be more easily accessed often at much lower cost, increasing its value by enabling opportunities for enhanced collaboration, integration, and analysis on a shared common platform. This paper explores the definition, nature and potential of cloud computing and research questions related to cloud computing.

Disaster-and-Evacuation-Aware Backup Datacenter Placement Based on Multi-Objective Optimization

Backup datacenters provide massive data storage and access services, and their failure may result in huge economic losses. So their location selection requires low damage risk and high evacuation capability simultaneously. But previous works on backup datacenter placement have not jointly considered these two factors from the viewpoint of traffic engineering and might result in the unnecessary loss in case of disaster. In this paper, with the global view of network resources in the software defined network scenarios, we propose a new disaster-and-evacuation-aware backup datacenter placement strategy. To reduce backup loss risk and apply rapid post-disaster evacuation, we jointly consider expected disaster loss and evacuation latency and formulate a new disaster-and-evacuation-aware facility location problem (NP-hard) which is multi-objective. To obtain the solution according to the disaster situation assessment, we propose a disaster-and-evacuation-aware multi-objective optimization algorithm. We optimize multiple objectives owning different coefficients in different disaster situations. We introduce location-output-capability, backup-evacuation-latency, Pareto-recommendation-degree, and node-damage-loss to guide solution searching. We prune the external set according to fitness-deviation-ratio to improve convergence speed and computation efficiency of the algorithm. Through extensive simulations, we demonstrate that our algorithm is efficient and promising with less expected disaster loss and higher evacuation capability simultaneously.

A Spectrum Sharing Paradigm for GSO Satellite System and Radio Astronomy System

Geostationary orbit (GSO) satellite communication systems (SCSs) play an important role in nowadays satellite communication. Orbiting in the Clarke Belt, the GSO satellites provide voice, video, Internet access, and other data services to the users all over the world. The GSO SCSs are seeking for more spectrum resource to satisfy the growing demand of high downlink data rate, while the radio astronomy system (RAS) is suffering the inevitable radio-frequency interference (RFI) from the downlink of these GSO satellites. To solve the conflict between the GSO SCSs and the RAS in the spectrum allocation, we propose a spectrum sharing paradigm for the GSO SCS and the RAS with three potential RFI reduction methods. Depending on the radio astronomical observation (RAO) tasks of different observatories, the corresponding appropriate RFI reduction method combination can be chosen. Our analyses show that the proposed paradigm can guarantee most of the telescopes with the sample loss rate lower than 2% in both protected and unprotected RAS bands, while the SCS can obtain up to 13.88% extra average downlink throughput.

Towards FAIRer Biological Knowledge Networks Using a Hybrid Linked Data and Graph Database Approach.

The speed and accuracy of new scientific discoveries – be it by humans or artificial intelligence – depends on the quality of the underlying data and on the technology to connect, search and share the data efficiently. In recent years, we have seen the rise of graph databases and semi-formal data models such as knowledge graphs to facilitate software approaches to scientific discovery. These approaches extend work based on formalised models, such as the Semantic Web. In this paper, we present our developments to connect, search and share data about genome-scale knowledge networks (GSKN). We have developed a simple application ontology based on OWL/RDF with mappings to standard schemas. We are employing the ontology to power data access services like resolvable URIs, SPARQL endpoints, JSON-LD web APIs and Neo4j-based knowledge graphs. We demonstrate how the proposed ontology and graph databases considerably improve search and access to interoperable and reusable biological knowledge (i.e. the FAIRness data principles).

Common ELIXIR Service for Researcher Authentication and Authorisation.

A common Authentication and Authorisation Infrastructure (AAI) that would allow single sign-on to services has been identified as a key enabler for European bioinformatics. ELIXIR AAI is an ELIXIR service portfolio for authenticating researchers to ELIXIR services and assisting these services on user privileges during research usage. It relieves the scientific service providers from managing the user identities and authorisation themselves, enables the researcher to have a single set of credentials to all ELIXIR services and supports meeting the requirements imposed by the data protection laws. ELIXIR AAI was launched in late 2016 and is part of the ELIXIR Compute platform portfolio. By the end of 2017 the number of users reached 1000, while the number of relying scientific services was 36. This paper presents the requirements and design of the ELIXIR AAI and the policies related to its use, and how it can be used for serving some example services, such as document management, social media, data discovery, human data access, cloud compute and training services.

Channel Condition Aware Detection in Statistical Signal Transmission

Heterogeneous network (HetNet) plays an important role in the upcoming 5G communications. A HetNet in futuristic communications is envisaged to provide full access data services, such that users will always have the best service with their available radio resources. To realize a full access HetNet, statistical signal transmission (SST) can be an important enabling technique. SST exploits statistical features of ordinary signals as a data transmission scheme to carry information data. Due to its inherent unique properties, SST signal is more robust than ordinary signals in conventional quasi-static channels. However, detection of SST signals in fast time-varying channels will face challenges. Motivated by this fact, this paper aims to analyze the impact of fast time-varying channels to SST, and reveals negative effects of burst of deep fading channel-state (BDFC) and feature dissipation with out-of-phase (FDOP). Accordingly, we design an automatic re-transmission scheme and a fragmental feature capturing method to mitigate the aforementioned issues, respectively. Based on these studies, we propose a channel condition aware detection scheme for SST, aiming to enhance SST detection performance in fast time-varying channels. Numerical results show that with the proposed scheme, a maximum gain of more than 10 dB can be obtained under either BDFC or FDOP condition. Furthermore, it is also demonstrated that the proposed scheme is robust with imperfect channel coherence time information, which is attractive for practical applications.