Сryptocurrency and Internet of Things: Problems of Implementation and Realization

IoT (Internet of Things) requires the implementation of digital encryption of information, transaction support and recording of all events for security. It can provide cryptocurrencies protocols with adding an additional possibility of payments. This opportunity is not so much demanded at the hardware level as in the software implementation. We have discovered that IoT devices are widely used for illegal purposes for trusts or network consolidated attacks, and virtually no legal and useful ways of using their hardware-distributed capabilities. Standardization and compatibility in IOT network should become the main tools for the possibility of introducing new solutions, testing their utility, performance and safety. The standardization of a new approach to interactive protocols in the IOT network and the Internet with a finance approach is now inevitable. We need new IEEE standards for cryptocurrencies and IoT functioning. They must include standards for protocol functioning, transaction validation and saving, privacy and security support. Cryptocurrencies and IoT interaction diagram were proposed. The IoT network devices technology will be in the future instance of the smart class of digital-physical systems, which also encompasses technologies such as smart homes, intelligent transportation systems, smart cities etc. The financial aspect for purchasing software, services, solutions and sales of the resulting benefits will complement this network with additional capabilities. The development of standards for the financial level of functioning is also necessary.IoT (Internet of Things) requires the implementation of digital encryption of information, transaction support and recording of all events for security. It can provide cryptocurrencies protocols with adding an additional possibility of payments. This opportunity is not so much demanded at the hardware level as in the software implementation. We have discovered that IoT devices are widely used for illegal purposes for trusts or network consolidated attacks, and virtually no legal and useful ways of using their hardware-distributed capabilities. Standardization and compatibility in IOT network should become the main tools for the possibility of introducing new solutions, testing their utility, performance and safety. The standardization of a new approach to interactive protocols in the IOT network and the Internet with a finance approach is now inevitable. We need new IEEE standards for cryptocurrencies and IoT functioning. They must include standards for protocol functioning, transaction validation and saving, privacy and security support. Cryptocurrencies and IoT interaction diagram were proposed. The IoT network devices technology will be in the future instance of the smart class of digital-physical systems, which also encompasses technologies such as smart homes, intelligent transportation systems, smart cities etc. The financial aspect for purchasing software, services, solutions and sales of the resulting benefits will complement this network with additional capabilities. The development of standards for the financial level of functioning is also necessary

CLOCIS:Cloud-based conformance testing framework for IoT devices in the future internet

In recent years, the Internet of Things (IoT) has not only become ubiquitous in daily life but has also emerged as a pivotal technology across various sectors, including smart factories and smart cities. Consequently, there is a pressing need to ensure the consistent and uninterrupted delivery of IoT services. Conformance testing has thus become an integral aspect of IoT technologies. However, traditional methods of IoT conformance testing fall short of addressing the evolving requirements put forth by both industry and academia. Historically, IoT testing has necessitated a visit to a testing laboratory, implying that both the testing systems and testers must be co-located. Furthermore, there is a notable absence of a comprehensive method for testing an array of IoT standards, especially given their inherent heterogeneity. With a surge in the development of diverse IoT standards, crafting an appropriate testing environment poses challenges. To address these concerns, this article introduces a method for remote IoT conformance testing, underpinned by a novel conceptual architecture termed CLOCIS. This architecture encompasses an extensible approach tailored for a myriad of IoT standards. Moreover, we elucidate the methods and procedures integral to testing IoT devices. CLOCIS, predicated on this conceptual framework, is actualized, and to attest to its viability, we undertake IoT conformance testing and present the results. When leveraging CLOCIS, small and medium-sized enterprises (SMEs) and entities in the throes of IoT service development stand to benefit from a reduced time to market and cost-efficient testing procedures. Additionally, this innovation holds promise for IoT standardization communities, enabling them to champion their standards with renewed vigor

Adversarial samples on android malware detection systems for IoT systems

Many IoT (Internet of Things) systems run Android systems or Android-like systems. With the continuous development of machine learning algorithms, the learning-based Android malware detection system for IoT devices has gradually increased. However, these learning-based detection models are often vulnerable to adversarial samples. An automated testing framework is needed to help these learning-based malware detection systems for IoT devices perform security analysis. The current methods of generating adversarial samples mostly require training parameters of models and most of the methods are aimed at image data. To solve this problem, we propose a testing framework for learning-based Android malware detection systems (TLAMD) for IoT Devices. The key challenge is how to construct a suitable fitness function to generate an effective adversarial sample without affecting the features of the application. By introducing genetic algorithms and some technical improvements, our test framework can generate adversarial samples for the IoT Android application with a success rate of nearly 100% and can perform black-box testing on the system.This research was funded by the National Natural Science Foundation of China under Grant No. 61672170, No. 61871313 and No. 61572115, in part by the National Key R&D Plan under Grant CNS 2016QY06X1205.Scopu

Adversarial Samples on Android Malware Detection Systems for IoT Systems

Many IoT(Internet of Things) systems run Android systems or Android-like systems. With the continuous development of machine learning algorithms, the learning-based Android malware detection system for IoT devices has gradually increased. However, these learning-based detection models are often vulnerable to adversarial samples. An automated testing framework is needed to help these learning-based malware detection systems for IoT devices perform security analysis. The current methods of generating adversarial samples mostly require training parameters of models and most of the methods are aimed at image data. To solve this problem, we propose a \textbf{t}esting framework for \textbf{l}earning-based \textbf{A}ndroid \textbf{m}alware \textbf{d}etection systems(TLAMD) for IoT Devices. The key challenge is how to construct a suitable fitness function to generate an effective adversarial sample without affecting the features of the application. By introducing genetic algorithms and some technical improvements, our test framework can generate adversarial samples for the IoT Android Application with a success rate of nearly 100\% and can perform black-box testing on the system

Towards Energy Consumption and Carbon Footprint Testing for AI-driven IoT Services

Energy consumption and carbon emissions are expected to be crucial factors for Internet of Things (IoT) applications. Both the scale and the geo-distribution keep increasing, while Artificial Intelligence (AI) further penetrates the "edge" in order to satisfy the need for highly-responsive and intelligent services. To date, several edge/fog emulators are catering for IoT testing by supporting the deployment and execution of AI-driven IoT services in consolidated test environments. These tools enable the configuration of infrastructures so that they closely resemble edge devices and IoT networks. However, energy consumption and carbon emissions estimations during the testing of AI services are still missing from the current state of IoT testing suites. This study highlights important questions that developers of AI-driven IoT services are in need of answers, along with a set of observations and challenges, aiming to help researchers designing IoT testing and benchmarking suites to cater to user needs.Comment: Presented at the 2nd International Workshop on Testing Distributed Internet of Things Systems (TDIS 2022

Designing the Health-related Internet of Things: Ethical Principles and Guidelines

The conjunction of wireless computing, ubiquitous Internet access, and the miniaturisation of sensors have opened the door for technological applications that can monitor health and well-being outside of formal healthcare systems. The health-related Internet of Things (H-IoT) increasingly plays a key role in health management by providing real-time tele-monitoring of patients, testing of treatments, actuation of medical devices, and fitness and well-being monitoring. Given its numerous applications and proposed benefits, adoption by medical and social care institutions and consumers may be rapid. However, a host of ethical concerns are also raised that must be addressed. The inherent sensitivity of health-related data being generated and latent risks of Internet-enabled devices pose serious challenges. Users, already in a vulnerable position as patients, face a seemingly impossible task to retain control over their data due to the scale, scope and complexity of systems that create, aggregate, and analyse personal health data. In response, the H-IoT must be designed to be technologically robust and scientifically reliable, while also remaining ethically responsible, trustworthy, and respectful of user rights and interests. To assist developers of the H-IoT, this paper describes nine principles and nine guidelines for ethical design of H-IoT devices and data protocols

Unit testing methods for Internet of Things Mbed OS operating system

Abstract. Embedded operating systems for Internet of Things are responsible for managing hardware and software in these systems. From the vast number of IoT operating system projects available, some projects are backed by large companies or institutes and some are developed completely by the open source community. IoT operating system testing focuses on the key features of IoT such as networking and limited resources. In this thesis, problems in Mbed OS operating system testing methods are identified and a unit testing solution is implemented. The implemented unit testing framework allows developers to write and run unit tests. The framework is also integrated into Mbed OS continuous integration to increase test coverage. This thesis shows how functional testing and unit testing are the most common types of testing in open source embedded operating system projects. Mbed OS unit testing framework results shows how running tests on PC platforms is faster than running tests on IoT devices. This framework also enables developers to write unit tests more freely and improve Mbed OS development process. The implemented unit testing framework solved issues in Mbed OS testing but more in depth research is needed to improve testing methods further.Yksikkötestausmenetelmät esineiden internet Mbed OS käyttöjärjestelmälle. Tiivistelmä. Esineiden internettiin tarkoitetut sulautetut käyttöjärjestelmät ovat tarvittavia laitteiston ja sovellusten hallintaan IoT järjestelmissä. Saatavilla olevien IoT käyttöjärjestelmien joukosta osa on suurten yritysten tai instituutioiden tukemia, ja osa on täysin vapaan lähdekoodin yhteisön kehittämiä. IoT käyttöjärjestelmän testaus keskittyy esineiden internetin avainominaisuuksiin kuten verkkotietoliikenteeseen ja rajallisiin resursseihin. Työssä tunnistetaan Mbed OS käyttöjärjestelmän testausmenetelmien ongelmia ja kehitetään yksikkötestaustyökalu. Kehitetty yksikkötestausympäristö mahdollistaa kehittäjille yksikkötestien kirjoittamisen ja ajamisen. Testaustyökalu yhdistetään myös Mbed OS jatkuvan integraation prosessiin testauskattavuuden parantamiseksi. Työssä katsotaan kuinka funktionaaliset testit ja yksikkötestit ovat yleisimmät testityypit avoimen lähdekoodin sulautetuissa käyttöjärjestelmäprojekteissa. Mbed OS yksikkötestaustyökalu näyttää kuinka testien ajaminen PC ympäristössä on nopeampaa kuin IoT laitteissa. Tämä työkalu myös mahdollistaa kehittäjien kirjoittaa yksikkötestejä vapaammin ja siten parantaa kehitysprosessia. Kehitetty yksikkötestaustyökalu ratkaisi Mbed OS testauksen ongelmia, mutta syventävää tutkimusta tarvitaan enemmän testausmenetelmien parantamiseksi edelleen

Underpinning Quality Assurance: Identifying Core Testing Strategies for Multiple Layers of Internet-of-Things-Based Applications

The Internet of Things (IoT) constitutes a digitally integrated network of intelligent devices equipped with sensors, software, and communication capabilities, facilitating data exchange among a multitude of digital systems via the Internet. Despite its pivotal role in the software development life-cycle (SDLC) for ensuring software quality in terms of both functional and non-functional aspects, testing within this intricate software–hardware ecosystem has been somewhat overlooked. To address this, various testing techniques are applied for real-time minimization of failure rates in IoT applications. However, the execution of a comprehensive test suite for specific IoT software remains a complex undertaking. This paper proposes a holistic framework aimed at aiding quality assurance engineers in delineating essential testing methods across different testing levels within the IoT. This delineation is crucial for effective quality assurance, ultimately reducing failure rates in real-time scenarios. Furthermore, the paper offers a mapping of these identified tests to each layer within the layered framework of the IoT. This comprehensive approach seeks to enhance the reliability and performance of IoT-based applications

Review of specific features and challenges in the current Internet of Things systems impacting their security and reliability

The current development of the Internet of Things (IoT) technology poses significant challenges to researchers and industry practitioners. Among these challenges, security and reliability particularly deserve attention. In this paper, we provide a consolidated analysis of the root causes of these challenges, their relations, and their possible impacts on IoT systems’ general quality characteristics. Further understanding of these challenges is useful for IoT quality engineers when defining testing strategies for their systems and researchers to consider when discussing possible research directions. In this study, twenty specific features of current IoT systems are discussed, divided into five main categories: (1) Economic, managerial and organisational aspects, (2) Infrastructural challenges, (3) Security and privacy challenges, (4) Complexity challenges and (5) Interoperability problems