Internet Of Things Cloud Systems Research Articles

Secure pharmaceutical supply chain using blockchain in IoT cloud systems

Supply Chain Management (SCM) systems require time sequencing, coordination and tracking the movement of goods and processes. Internet of Things (IoT) and Blockchain technologies are useful to develop a secure automated SCM. IoT devices with in-built sensors and actuators help to keep track of the state, location, temperature or other parameters of an entity, and control the automation of routine as well as hazardous tasks. Blockchain technology supports time-stamping, authentication, process coordination, non-repudiation, commercial transactions, and also provides security for transactions and storage. The pharmaceutical SCM demands accurate, immediate and secure control system. Additionally, the supply chain process data from IoTs is stored and processed in Cloud by Analytics applications, for business planning and improvement. An efficient and secure IoT-Cloud-Blockchain based system for both SCM automation and analytics has been proposed in this work. It leverages a hierarchical IoT, Mist, Edge, Fog, Cloud computing (IMEFC) architecture to enhance Communication-Response-Compute-Security-Storage (CRCSS) in the system. Blockchain technology provides security for the SCM transactions and data. The efficiency of the Blockchain is measured in terms of upload time, download time and transaction fees for Bitcoin, Ethereum and Filecoin platforms. The Filecoin blockchain platform is quicker and cost-effective for larger file sizes, compared to Ethereum and Bitcoin, making it suitable for Pharmaceutical SCM systems.

Enabling internet of things in road traffic forecasting with deep learning models

Integration of the latest technological advancements such as Internet of Things (IoT) and Computational Intelligence (CI) techniques is an active research area for various industrial applications. The rapid urbanization and exponential growth of vehicles has led to crowded traffic in cities. The deployment of IoT infrastructures for building smart and intelligent traffic management system greatly improves the quality and comfort of city dwellers. This work aims at building a cost effective IoT enabled traffic forecasting system using deep learning techniques. The case study experimentation is done in a real time traffic environment. The main contributions of this work include: (i) deploying road side sensor station built with ultrasonic sensor and Arduino Uno controller for obtaining traffic flow data (ii) building an IoT cloud system based on open source Thingspeak cloud platform for monitoring real time traffic (iii) performing short term traffic forecast using Recurrent Neural Network (RNN) models such as Long Short Term Memory (LSTM) and Gated Recurrent Unit (GRU). The performance of the prediction model is compared with the traditional statistical methods such as Autoregressive Integrated Moving Average (ARIMA), Seasonal ARIMA (SARIMA) and Convolutional Neural Network (CNN). The results show good performance metrics with RMSE of 5.8, 7.9, 10.2 for LSTM model and 6.7, 8.6, 10.9 for GRU model for three different scenarios such as whole day, morning congested hour and evening congested hour datasets.

Defending N-Version Programming Service Components against Co-Resident Attacks in IoT Cloud Systems

The real innovation of Internet of Things (IoT) can be spurred only when being combined with cloud computing, a paradigm that allows numerous users to simultaneously access configurable resources and services. However, serious vulnerability concerns have arisen from the virtual machine co-resident architecture of the IoT cloud. Specifically, co-resident attacks can be launched, where an attacker can access and corrupt a user's sensitive data/software by co-locating their virtual machines on the same physical server. Various solutions have been suggested in literature to mitigate negative effects of the co-resident attacks in the cloud environment. However, to the best of our knowledge no work has been performed for studying co-resident attacks in cloud systems with <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">N</i> -version programming (NVP), a popular redundancy technique for enhancing survivability of critical cloud service components. This paper makes original contributions by modeling IoT cloud system services implementing the NVP component redundancy, and evaluating the corruption probability of the NVP service component. Further, users’ policies on choosing the optimal number of service component versions are investigated through formulating and solving a new set of optimization problems with the objective to minimize the expected cost of losses of a cloud service provider. As demonstrated through examples, these policies can effectively help defend the NVP service component against the co-resident attacks in the cloud system.

An Affordable, Scalable, Open Architecture, IoT Eco-system for the Academic Community

Aim: Today, Internet of Things (IoT) applications are extended from smart homes to ehealth, cyber security, data analytics, logistics and management of assets. There are many upcoming IOT solutions and platforms like ThingWorx, Xively, and Yaler. However, the existing eco-systems are not vibrant because of the high entry-level barrier and low potential for any stakeholder. Especially, the academic community requires a comprehensible way to create IoT services, develop their skillsets and build applications around them. In this regard, this work presents an affordable and scalable IoT eco-system with an easily programmable hardware platform, a private web server on the cloud and a user-friendly mobile application. Background: Home automation controls the devices and appliances in the home environment to increase the comfort and convenience. To design a typical immune home automation system, we need to incorporate different sensors, wireless networking and a central node that can collect data and act as a gateway for the internet connection. Objective: Delivering an IoT solution involves the use of multiple technologies that cut across traditional engineering stream boundaries - sensors, microcontrollers, wireless networking, network protocols, web programming, and mobile app development. The open challenge is to put the entire ecosystem together either through new development or through configuartion of existing components. Methods: In this work, we incorporated a suitable hardware platform that can be easily programmed. The platform is open so that new sensors and actuators can be added as per requirement. The existing web services are used to post and retrieve data from the cloud. In addition, mobile apps can be developed to make data available to the user. Results: A custom-built GISMO based IoT cloud system is developed with sensors and nodes to form an infrastructure. The framework will assure standard design that establishes a functional link between hardware, software and web applications. A private web service using HTTP server and MQTT broker is designed with access from anywhere with a public IP. The web services are coded in PHP and since it is an in-house development, the addition of new services and maintenance of existing services are easy. Conclusion: The IoT eco-system developed provides a platform for a quick out-of-the-box implementation of an IoT project. Other sensors such as a PIR sensor, an RTC module, an ultrasonic sensor, a soil moisture sensor have been interfaced to the GISMO module using the IOs brought out onto the expansion header. The GISMO thus can serve as a generic hardware platform for sensor/actuator interface in the IoT scheme. The eco-system can be replicated in other institutes and can serve as a base to implement applications like sensor-to-cloud interface, cloud-to-actuator interface, cloud-based alerts and notifications, HTTP and MQTT protocols usage.

IoT Cloud Security Review

Recent years have seen the rapid development and integration of the Internet of Things (IoT) and cloud computing. The market is providing various consumer-oriented smart IoT devices; the mainstream cloud service providers are building their software stacks to support IoT services. With this emerging trend even growing, the security of such smart IoT cloud systems has drawn much research attention in recent years. To better understand the emerging consumer-oriented smart IoT cloud systems for practical engineers and new researchers, this article presents a review of the most recent research efforts on existing, real, already deployed consumer-oriented IoT cloud applications in the past five years using typical case studies. Specifically, we first present a general model for the IoT cloud ecosystem. Then, using the model, we review and summarize recent, representative research works on emerging smart IoT cloud system security using 10 detailed case studies, with the aim that the case studies together provide insights into the insecurity of current emerging IoT cloud systems. We further present a systematic approach to conduct a security analysis for IoT cloud systems. Based on the proposed security analysis approach, we review and suggest potential security risk mitigation methods to protect IoT cloud systems. We also discuss future research challenges for the IoT cloud security area.

IEEE Access Special Section Editorial: Security and Privacy in Emerging Decentralized Communication Environments

Due to the COVID-19 epidemic, face-to-face team working has changed into distanced work from home. Modern, decentralized digital communication environments are changing with the availability of new technologies and the development of new real-world applications, which lead to novel challenges in security and privacy protection. 5G/6G mobile applications, the smart Internet of Things (IoT) devices, big data applications, and cloud systems are developing to better meet new requirements. Mobile–cloud architecture is emerging as 5G /6G mobile IoT devices are generating large volumes of data which need cloud infrastructure to process. Many IoT systems and cloud systems are decentralized, and new security and privacy protection solutions are emerging in decentralized networks. The increasing interdependence of IT solutions accepted by society has led to a sharp increase in data. As a result, the chances of data leakage or privacy infringement also increase, along with the need for new solutions for digital security and privacy protection.

Integration of IoT and chatbot for aquaculture with natural language processing

The development of internet of things (IoT) technology is very fast lately. One sector that can be implemented by IoT technology is the aquaculture sector. One important factor in the success of aquaculture is a good and controlled water quality condition. But the problem for the traditional aquaculture farmers is to monitor and increase the water quality quickly and efficiently. To resolve the above-mentioned problem, this paper proposes a real-time monitoring system for aquaculture and supported with chatbot assistant to facilitate the user. This system was composed of IoT system, cloud system, and chatbot system. The proposed system consists of 7 main modules: smart sensors, smart aeration system, local network system, cloud computing system, client visualization data, chatbot system, and solar powered system. The smart aeration system consists of NodeMCU, relay, and aerator. The smart sensors consist of several sensors such as dissolved oxygen, pH, temperature, and water level sensor. Natural language processing is implemented to build the chatbot system. By combining text mining processing with naive Bayes algorithm, the result shows the very good performance with high precision and recall for each class to monitor the quality of water in aquaculture sector.

Principles for Engineering IoT Cloud Systems

Engineering Internet of Things (IoT) and cloud services to provide a coherent software layer for continuous deployment, provision, and execution of applications for various domains is complex. The authors consider whether IoT cloud systems could provide a uniform layer to enable continuous execution of complex applications consisting of diverse types of software components, although these systems are built by integrating and blending IoT infrastructures with cloud-based datacenters. The authors analyze requirements and perspectives for engineering such IoT cloud systems and discuss the main engineering principles that should be supported. They then highlight seven main principles, covering different development and operation phases of IoT cloud systems. To show the importance and feasibility of these principles, they present some of their recent work in providing concepts and tools for IoT cloud systems.