Third-party Applications Research Articles

Open-access bacterial population genomics: BIGSdb software, the PubMLST.org website and their applications

The PubMLST.org website hosts a collection of open-access, curated databases that integrate population sequence data with provenance and phenotype information for over 100 different microbial species and genera. Although the PubMLST website was conceived as part of the development of the first multi-locus sequence typing (MLST) scheme in 1998 the software it uses, the Bacterial Isolate Genome Sequence database (BIGSdb, published in 2010), enables PubMLST to include all levels of sequence data, from single gene sequences up to and including complete, finished genomes. Here we describe developments in the BIGSdb software made from publication to June 2018 and show how the platform realises microbial population genomics for a wide range of applications. The system is based on the gene-by-gene analysis of microbial genomes, with each deposited sequence annotated and curated to identify the genes present and systematically catalogue their variation. Originally intended as a means of characterising isolates with typing schemes, the synthesis of sequences and records of genetic variation with provenance and phenotype data permits highly scalable (whole genome sequence data for tens of thousands of isolates) means of addressing a wide range of functional questions, including: the prediction of antimicrobial resistance; likely cross-reactivity with vaccine antigens; and the functional activities of different variants that lead to key phenotypes. There are no limitations to the number of sequences, genetic loci, allelic variants or schemes (combinations of loci) that can be included, enabling each database to represent an expanding catalogue of the genetic variation of the population in question. In addition to providing web-accessible analyses and links to third-party analysis and visualisation tools, the BIGSdb software includes a RESTful application programming interface (API) that enables access to all the underlying data for third-party applications and data analysis pipelines.

Open-access bacterial population genomics: BIGSdb software, the PubMLST.org website and their applications.

The PubMLST.org website hosts a collection of open-access, curated databases that integrate population sequence data with provenance and phenotype information for over 100 different microbial species and genera. Although the PubMLST website was conceived as part of the development of the first multi-locus sequence typing (MLST) scheme in 1998 the software it uses, the Bacterial Isolate Genome Sequence database (BIGSdb, published in 2010), enables PubMLST to include all levels of sequence data, from single gene sequences up to and including complete, finished genomes. Here we describe developments in the BIGSdb software made from publication to June 2018 and show how the platform realises microbial population genomics for a wide range of applications. The system is based on the gene-by-gene analysis of microbial genomes, with each deposited sequence annotated and curated to identify the genes present and systematically catalogue their variation. Originally intended as a means of characterising isolates with typing schemes, the synthesis of sequences and records of genetic variation with provenance and phenotype data permits highly scalable (whole genome sequence data for tens of thousands of isolates) means of addressing a wide range of functional questions, including: the prediction of antimicrobial resistance; likely cross-reactivity with vaccine antigens; and the functional activities of different variants that lead to key phenotypes. There are no limitations to the number of sequences, genetic loci, allelic variants or schemes (combinations of loci) that can be included, enabling each database to represent an expanding catalogue of the genetic variation of the population in question. In addition to providing web-accessible analyses and links to third-party analysis and visualisation tools, the BIGSdb software includes a RESTful application programming interface (API) that enables access to all the underlying data for third-party applications and data analysis pipelines.

Open-Source Network Optimization Software in the Open SDN/NFV Transport Ecosystem

Transport ecosystems that combine software defined networking (SDN) and network function virtualization (NFV) are characterized by an unprecedented network control and resource dynamicity. Manual optimization is unmanageable. In this context, open systems that manage and orchestrate SDN/NFV-enabled networks offer programming frameworks that abstract the low-level particularities in the data-plane forwarding devices and in the hardware appliances that provide the IT resources. Although these open systems present notable complexity, their programming abstractions promote a client layer where third-party applications can provide different functionalities thus enabling optimization-as-a-service business opportunities. In this paper, we cover open-source optimization software initiatives for offline planning and online provisioning and orchestration of SDN/NFV networks. With this goal in mind, we first focus on open software (and framework) initiatives through a set of realistic use cases that require optimization in multi-layer optical transport scenarios and ecosystems that combine transport with IT resources. The importance of a joint optimization of both network and IT domains is emphasized, a new paradigm triggered by SDN/NFV technologies. We discuss the theoretical limits to algorithm performances, and review available open-source frameworks for problem modeling that enable the interaction with solvers. Finally, we focus on the Net2Plan open-source network planning tool, a Java-based software that suitably embraces the multiple features required in the optimization of joint transport network and IT resource SDN/NFV ecosystems. Recent works based on Net2Plan are reviewed to illustrate its suitability for rapid algorithm prototyping, and for interaction with SDN/NFV-enabled networks.

Inferring user interests in microblogging social networks: a survey

With the growing popularity of microblogging services such as Twitter in recent years, an increasing number of users are using these services in their daily lives. The huge volume of information generated by users raises new opportunities in various applications and areas. Inferring user interests plays a significant role in providing personalized recommendations on microblogging services, and also on third-party applications providing social logins via these services, especially in cold-start situations. In this survey, we review user modeling strategies with respect to inferring user interests from previous studies. To this end, we focus on four dimensions of inferring user interest profiles: (1) data collection, (2) representation of user interest profiles, (3) construction and enhancement of user interest profiles, and (4) the evaluation of the constructed profiles. Through this survey, we aim to provide an overview of state-of-the-art user modeling strategies for inferring user interest profiles on microblogging social networks with respect to the four dimensions. For each dimension, we review and summarize previous studies based on specified criteria. Finally, we discuss some challenges and opportunities for future work in this research domain.

CDroid: practically implementation a formal-analyzed CIFC model on Android

Decentralized information flow control (DIFC) operating systems provide mechanisms for applications to handle the secrecy and integrity of their data by themselves. DIFC adapts to the distributed systems well, but not for the centralized authorization systems where an administrator manages all the privileges. For example, Android is full of untrusted third-party applications. A phone user may want to specify what kind of application can deal with what kind of private data by enforcing information flow control. To address this, we proposed a novel formal-described and security-proofed centralized information flow control (CIFC) model. In CIFC, taint tag of private data and capability label of applications are designed to support fine-grained and user-defined information flow control. Differs from DIFC and classic information flow control models, CIFC model controls information flow according to the relation between tag and label rather than the relation between two labels of applications. We use Value-passing Security Process Algebra (VSPA) to clarify the formal semantics of CIFC model. The verification of system equivalence proves that the model guarantees the noninterference security property in virtue of Checker of Persistent Security (CoPS) tool. We also implemented CDroid, a prototype of the CIFC model which can track and control information flow at runtime. CDroid is demonstrated to be an accurate system to achieve the security goal through several function test experiments. Furthermore, CDroid has 5% lead in memory consumption and 17% overhead of runtime performance compared to Android.

Sistem Pengawasan Aktifitas Penggunaan Smartphone Android

Availability the Application Programming Interface (API) for third-party applications on Android devices provides an opportunity to monitor Android devices with each other. This is used to create an application that can facilitate parents in child supervision through Android devices owned. In this study, some features added to the classification of image content on Android devices related to negative content. In this case, researchers using Clarifai API. The result of this research is to produce a system which has feature, give a report of image file contained in target smartphone and can do deletion on the image file, receive browser history report and can directly visit in the application, receive a report of child location and can be directly contacted via this application. This application works well on the Android Lollipop (API Level 22).
 Index Terms— Application Programming Interface(API), Monitoring, Negative Content, Children, Parent.

Analysis of a Third-Party Application for Mobile Forensic Investigation

Analysis of a Third-Party Application for Mobile Forensic Investigation

Cloud-based federated identity for the Internet of Things

The Internet of Things (IoT) has significant security and privacy risks. Recent attacks have shown that not only are many IoT devices at risk of exploit, but those devices can be successfully used to attack wider systems and cause economic damage. Currently, most devices connect to a cloud service that is provided by the manufacturer of the device, offering no choice to move to more secure systems. We outline a proposed model for IoT that allows the identity of users and devices to be federated. Users and devices are issued with secure, random, anonymised identities that are not shared with third parties. We demonstrate how devices can be connected to third-party applications without inherently de-anonymising them. Sensor data and actuator commands are federated through APIs to cloud services. All access to device data and commands is based on explicit consent from users. Each user’s data is handled by a personal cloud instance providing improved security and isolation, as well as providing a trusted intermediary for both devices and cloud services. We demonstrate this model is workable with a prototype system that implements the major features of the model. We present experiment results including performance, energy usage, capacity and cost metrics from the prototype. We compare this work with other related work and outline areas for discussion and future work.

Developing a Third-Party Analytics Application Using Australia's National Personal Health Records System: Case Study.

BackgroundMy Health Record (MyHR) is Australia’s national electronic health record (EHR) system. Poor usability and functionality have resulted in low utility, affecting enrollment and participation rates by both patients and clinicians alike. Similar to apps on mobile phone app stores, innovative third-party applications of MyHR platform data can enhance the usefulness of the platform, but there is a paucity of research into the processes involved in developing third-party applications that integrate and use data from EHR systems.ObjectiveThe research describes the challenges involved in pioneering the development of a patient and clinician Web-based software application for MyHR and insights resulting from this experience.MethodsThis research uses a case study approach, investigating the development and implementation of Actionable Intime Insights (AI2), a third-party application for MyHR, which translates Medicare claims records stored in MyHR into a clinically meaningful timeline visualization of health data for both patients and clinicians. This case study identifies the challenges encountered by the Personal Health Informatics team from Flinders University in the MyHR third-party application development environment.ResultsThe study presents a nuanced understanding of different data types and quality of data in MyHR and the complexities associated with developing secondary-use applications. Regulatory requirements associated with utilization of MyHR data, restrictions on visualizations of data, and processes of testing third-party applications were encountered during the development of the application.ConclusionsThis study identified several processes, technical and regulatory barriers which, if addressed, can make MyHR a thriving ecosystem of health applications. It clearly identifies opportunities and considerations for the Australian Digital Health Agency and other national bodies wishing to encourage the development of new and innovative use cases for national EHRs.

Построение автоматизированной системы на базе платформы 1C: Предприятие с использованием формата JSON

Options of JSON format using to apply it to integrate with third-party applications is discussed in the article. It is offered to use automated systems on platform 1C Enterprise in a parallel mode.

Collateral damage of Facebook third-party applications: a comprehensive study

Third-party applications on Facebook can collect personal data of the users who install them, but also of their friends. This raises serious privacy issues as these friends are not notified by the applications nor by Facebook and they have not given consent. This paper presents a detailed multi-faceted study on the collateral information collection of the applications on Facebook. To investigate the views of the users, we designed a questionnaire and collected the responses of 114 participants. The results show that participants are concerned about the collateral information collection and in particular about the lack of notification and of mechanisms to control the data collection. Based on real data, we compute the likelihood of collateral information collection affecting users: we show that the probability is significant and greater than 80% for popular applications such as TripAdvisor. We also demonstrate that a substantial amount of profile data can be collected by applications, which enables application providers to profile users. To investigate whether collateral information collection is an issue to users’ privacy we analysed the legal framework in light of the General Data Protection Regulation. We provide a detailed analysis of the entities involved and investigate which entity is accountable for the collateral information collection. To provide countermeasures, we propose a privacy dashboard extension that implements privacy scoring computations to enhance transparency toward collateral information collection. Furthermore, we discuss alternative solutions highlighting other countermeasures such as notification and access control mechanisms, cryptographic solutions and application auditing. To the best of our knowledge this is the first work that provides a detailed multi-faceted study of this problem and that analyses the threat of user profiling by application providers.

Secure personal data administration in the social networks: the case of voluntary sharing of personal data on the Facebook

In view of the changes taking place in society, social progress and the achievements of science and technology, the protection of fundamental rights must be strengthened. The aim of the article is to analyse the principles and peculiarities of safe management of the personal data in social networks. In this scientific article, methods of document analysis, scientific literature review, case study and generalization are used. Consumers themselves decide how much and what kind of information to publicize on the Facebook social network. In order to use the third-party applications, users at the time of authorization must confirm that they agree to give access to their personal data otherwise the service will not be provided. Personal data of the Facebook user comprise his/her public profile including user's photo, age, gender, and other public information; a list of friends; e-mail mail; time zone records; birthday; photos; hobbies, etc. Which personal data will be requested from the user depends on the third-party application. Analysis of the legal protection of personal data in the internet social networks reveals that it is limited to the international and European Union legal regulation on protection of the personal data in the online social networks. Users who make publicly available a large amount of personal information on the Facebook social network should decide on the issue if they want to share that information with third parties for the use of their services (applications). This article presents a model for user and third party application interaction, and an analysis of risks and recommendations to ensure the security of personal data of the user.

Mechanisms of neuroprogression and interventions to predict and arrest it

Decentralized information flow control (DIFC) operating systems provide mechanisms for applications to handle the secrecy and integrity of their data by themselves. DIFC adapts to the distributed systems well, but not for the centralized authorization systems where an administrator manages all the privileges. For example, Android is full of untrusted third-party applications. A phone user may want to specify what kind of application can deal with what kind of private data by enforcing information flow control. To address this, we proposed a novel formal-described and security-proofed centralized information flow control (CIFC) model. In CIFC, taint tag of private data and capability label of applications are designed to support fine-grained and user-defined information flow control. Differs from DIFC and classic information flow control models, CIFC model controls information flow according to the relation between tag and label rather than the relation between two labels of applications. We use Value-passing Security Process Algebra (VSPA) to clarify the formal semantics of CIFC model. The verification of system equivalence proves that the model guarantees the noninterference security property in virtue of Checker of Persistent Security (CoPS) tool. We also implemented CDroid, a prototype of the CIFC model which can track and control information flow at runtime. CDroid is demonstrated to be an accurate system to achieve the security goal through several function test experiments. Furthermore, CDroid has 5% lead in memory consumption and 17% overhead of runtime performance compared to Android.

An Empirical Analysis of Android Permission System Based on User Activities

In today’s world there has been an exponential growth among smart-phone users which has led to the unbridled growth of smart-phone apps available in Google play store, app store etc., In case of android application, there are many free applications for which the user need not shell out a penny to use the services. Here the magic word is “free” which entices millions of pliant people into installing those apps and giving unnecessary access to their data and device control. Current studies have shown that over 70% of the apps in market, request to gather data digressive to the most functions of apps that might cause seeping of personal data or inefficient use of mobile resources. Of late, couple of malignant applications gather unobtrusive information of the user through third-party applications by increasing their permissions to high-level on the Android Operating System. Android permission system provides, the user access to the third party apps and in return based on the permissions granted by the user, an app can access the related resource from the user's mobile. A user is bound to grant or deny permits during the installation of the application. For the most part, users don't focus on the asked permissions, or sometimes users do not understand the meaning of the permission and install the app on their device. They allow a way for attackers to perform the malicious task by demanding for more than expected set of permissions. These extra permissions permit the attacker to exploit the device and also retrieve sensitive information from it. In this research paper we describe how permission system security can create an awareness among the users that would assist them in deciding on permission grants. This improved and responsible user activities in Android OS can help the users in utilizing their device securely.

A Police and Insurance Joint Management System Based on High Precision BDS/GPS Positioning.

Car ownership in China reached 194 million vehicles at the end of 2016. The traffic congestion index (TCI) exceeds 2.0 during rush hour in some cities. Inefficient processing for minor traffic accidents is considered to be one of the leading causes for road traffic jams. Meanwhile, the process after an accident is quite troublesome. The main reason is that it is almost always impossible to get the complete chain of evidence when the accident happens. Accordingly, a police and insurance joint management system is developed which is based on high precision BeiDou Navigation Satellite System (BDS)/Global Positioning System (GPS) positioning to process traffic accidents. First of all, an intelligent vehicle rearview mirror terminal is developed. The terminal applies a commonly used consumer electronic device with single frequency navigation. Based on the high precision BDS/GPS positioning algorithm, its accuracy can reach sub-meter level in the urban areas. More specifically, a kernel driver is built to realize the high precision positioning algorithm in an Android HAL layer. Thus the third-party application developers can call the general location Application Programming Interface (API) of the original standard Global Navigation Satellite System (GNSS) to get high precision positioning results. Therefore, the terminal can provide lane level positioning service for car users. Next, a remote traffic accident processing platform is built to provide big data analysis and management. According to the big data analysis of information collected by BDS high precision intelligent sense service, vehicle behaviors can be obtained. The platform can also automatically match and screen the data that uploads after an accident to achieve accurate reproduction of the scene. Thus, it helps traffic police and insurance personnel to complete remote responsibility identification and survey for the accident. Thirdly, a rapid processing flow is established in this article to meet the requirements to quickly handle traffic accidents. The traffic police can remotely identify accident responsibility and the insurance personnel can remotely survey an accident. Moreover, the police and insurance joint management system has been carried out in Wuhan, Central China’s Hubei Province, and Wuxi, Eastern China’s Jiangsu Province. In a word, a system is developed to obtain and analyze multisource data including precise positioning and visual information, and a solution is proposed for efficient processing of traffic accidents.

Performance Measurement Study on Two Video Service Providers in China

This article describes how understanding the potential characteristics of video services is very important, as it can help users or third-party applications to predict performance or to identify service strategies. For this purpose, a measurement system deployed in 11 provinces and cities in China and monitoring two popular Web sites—Youku and Tudou—was designed. Through analyzing the measured records, it is obvious that the performance trend of the two service providers follows diurnal patterns, and it is consistent with users' accessing behavior. These two service providers share the underlying content delivery network to some extent, especially for the same content. The playing quality can also be guaranteed, typically for low-resolution content. Meanwhile, the user terminal's ISP is an important impact factor of service quality. In addition, how to predict the service performance online is also discussed, which is useful in some applications (e.g., video source recommendation systems).

Android Smartphone Remote Monitoring Application Using SMS Service

Android has been updating the system of every version it releases. The addition of Application Programming Interface (API) is done every time Google releases a new Android operating system. The availability of APIs for third-party applications provides opportunities for developers to be able to monitor Android smartphones. Just like Google Device Manager which can instruct Android smartphones over the internet network, however, it still has a deficiency that is if the target smartphone in a state of inactive internet. In this research, the author utilizes SMS media to be able to process instructions and access the system API for monitoring purposes. The results of this research is by using SMS then user can instruct Android smartphone to take photos, get current location, ring, delete smartphone files, set screen protection, and backup contact with higher messaging reliability. This application can run well on Android Lollipop 5.1 (API Level 22) or above because it has enough API to support system functionality.

Systematic Mapping Study on Verification and Validation of Industrial Third-party Iot Applications

The next industrial revolution commonly known as Industry 4.0 represents the idea of interconnected manufacturing, where intelligent devices, systems and processes exchange information, resources and artifacts to optimize the complete value-added chain and to reduce costs and time-to- market. Industrial software ecosystems are a good example how the latest digitalization trends are applied in the industry domain and how with the help of industrial IoT applications the production process can be optimized. However, the use of third- party applications exposes to a risk the systems and devices part of the manufacturing process. To address these risks a set of quality measures must be carried out in the ecosystem. This paper presents the results of a systematic mapping study carried out in the area of verification and validation of industrial IoT third-party applications. The goal of the study is to structure the scientific landscape and to provide an up-to-date snapshot of the current state of the research field.

TRAMP Real-Time Application Mobility Platform

As a step towards mobile and ubiquitous computing, the TRAMP Real-time Application Mobility Platform (TRAMP) enables secure and user-friendly migration of multimedia application components. The motivating factors are device and user mobiliy, i.e., to let the user determine where application components should execute at all times. In order to organize and locate roaming devices, a decentralized peer-to-peer overlay is developed. To provide location transparency for application developers and enable efficient data sharing among application components, an API is provided that hides whether shared memory or latency optimized network distribution is used to share data. The problem of open TCP connections to third-party applications is solved with a proxy-based approach. Multimedia applications are especially sensitive to service interruptions that can be caused by migration, and a new approach for check-pointing, state transfer, and resuming an application with minimal freeze time is therefore introduced. The evaluation of TRAMP shows that this optimization for low freeze time has significant effect. For example, migrating the Skype video-conferencing application with TRAMP reduces the average freeze time from 41.1 seconds with legacy approaches to 213 milliseconds. Further results from the empirical evaluation of TRAMP demonstrate that it has no negative impact on the Quality of Experience.

Organization of simulation experiments in the design of distributed computer systems with redundant data transmission

Subject of Research.We study the ways of multipath distribution of copies of requests (packets) through the network and their redundant servicing by servers of a given cluster. The alternatives under consideration differ in the way of path selection for a packet in the network having routes with joint switching nodes (static or dynamic) and in the condition under which those copies exit early from the system as a result of their losses in the communication channels, the emergence of bit errors, the overflow of transmitting and receiving buffers of the network and computing equipment, or the combination of these reasons. Method. We consider the efficiency of redundant transmissions, defined as the probability of faultless and timely delivery of at least one redundant copy to the cluster and dependent on the intensity of the flow of incoming requests. Based on the alternatives described, a set of simulation models with parameters representing the requirements for the system under simulation is created with AnyLogic 7 simulation environment. The results of simulation experiments are being written to the Microsoft SQL Server 2008 database, undergo transformations, and then are exported into the application program developed in this study. Main Results. Organization of simulation experiments involving accumulating and processing of their results with the tools of the chosen database management system is proposed. After being handled, those results are used to form the basis for analysis of the obtained dependencies with third-party software applications, such as Microsoft Excel or the one implemented in this work, to determine the scope of efficiency of redundant transmissions and to automate the search for the optimal order of redundancy. The simulation results that confirm the efficiency of multipath distribution of copies of requests are presented. Practical Relevance.The proposed models and tools enable one to justify the choice and optimize project solutions to the problem of improving functional reliability of distributed computer systems with redundant transmission and servicing of requests.