ABSTRACT Supply chain processes are essential for managing the distribution of goods from suppliers to consumers. In light of the globalization of the economy, the distances involved in delivery have significantly increased, often spanning thousands of kilometers across various countries and continents, utilizing multiple modes of transportation, including land, maritime, and air. The primary objective of the supply chain process is to ensure the quality and safety of goods during transit, thereby mitigating the risks of damage, deterioration, and spoilage. This requires real‐time monitoring of various environmental conditions, such as temperature and humidity, to which goods are subjected. This paper tackles the critical challenge of monitoring real‐time conditions in goods transportation by innovatively designing and implementing an Internet of Things (IoT) system, together with a set of customized evaluation metrics. Unlike conventional approaches, our work introduces a practical and scalable prototype that takes advantage of readily available low‐cost technologies: temperature and light sensors integrated with a Raspberry Pi. This device continuously collects and transmits environmental data to a database server. Metrics will be defined to evaluate the quality of the goods. In addition, a dedicated web application will be developed that enables the complete analysis and visualization of the collected data. By establishing a quantifiable framework and providing a cost‐effective end‐to‐end monitoring solution, our study fills a significant gap in the current cold chain logistics landscape.

ABSTRACT Cloud migration is the process of moving data, files, and applications to a cloud computing environment. With the success of cloud computing, cloud migration is becoming fashionable. However, different cloud service providers have their own migration processes as currently, no standard cloud‐based software migration procedure exists to guide how to move digital resources to the cloud. Moreover, there are serious security risks associated with cloud migration processes that threaten business processes that have not been systematically analyzed. In addition, no formal models and security metrics exist to evaluate and analyze these risks. Therefore, it is necessary to develop a generic approach with real customer use cases. In this study, firstly, we will develop a general cloud‐based software migration procedure to help organizations migrate their digital resources to cloud platforms. Secondly, we will develop a risk assessment model for analyzing migration processes. Thirdly, on the basis of this risk assessment model, we use stochastic colored Petri nets to describe the dynamic behavior of the model, thus the concurrency, synchronization, mutual exclusion, and conflicts can be analyzed to assess the risks of migration automatically. Fourthly, security metrics will be defined to quantitatively evaluate the risks and vulnerabilities of the organizations. We believe that this study can help chief information officers identify which risk will have more opportunity to occur during the migration processes and make informed decisions about software migration and security.

The cost and lack of flexibility of health care systems represent a major obstacle for the elderly and poor citizens. The current technologies are reserved for hospitals and large clinics in the developed countries have high costs and maintenance. Therefore, it is necessary to bring health monitoring closer to the patients and healthcare providers in a cost-effective way. This study aims to build a platform that is ready to expand to use all the sensors to predict illnesses and conditions in hospitals and homes. The system is based on two Arduino Uno microcontroller units (MCU), environmental sensors, health sensors (MySignals), and Arduino IDE. Fuzzy Logic is used to push and pull data from the cloud to mobile and web visualization plus an alert system. This study tested 15 sensors in both health and ambient environments the integration of both groups of sensors can produce more accurate predictions. In addition, metrics will be used to decide the range of readings that are industry-specific for each sensor.

Supply chain processes are used for controlling the delivery of goods from suppliers to consumers. With the globalization of the economy, delivery distances are on the increase and might involve thousands of kilometers across countries and even continents and different means of transport including land, water, and air transport. The task of the supply chain process is to guarantee the quality and safety of the goods at transportation time to prevent potential damage, deterioration, and decay. This requires real-time monitoring and observance of several conditions (e.g., temperature and humidity) to which the goods are exposed. To address the problem, this paper discusses the implementation of an IoT system and relevant metrics for monitoring, in real-time, the conditions that goods face during transportation. In the prototype that we have implemented, we use conventional low-cost cost widely available technologies, namely, temperature and light sensors connected to a Raspberry Pi device that sends the sensors' data to a database server. We then analyze the data with the help of a web application that we have also implemented.

We discuss a practical implementation and performance evaluation of a desktop cloud environment that enables international corporations to make their data available to their staff members transparently, regardless of the location of the data and the staff members. It has been implemented for the benefit of the European and American multinational retail companies that operate in the Yangtze River Delta region, these companies normally collect large amounts of sensitive data that demand protection. It is meant to be used as an alternative to off-the-shelf solutions that companies cannot import due to restrictions that the Chinese government has currently in force. As such, it must comply with both local and international regulations imposed by the government. Notably, it is expected to comply with the data security and data protection regulations imposed by the Chinese government and at the same time with international regulations such as the GDPR followed by European countries. Our implementation takes advantage of the functions (e.g., deployment of virtual applications, desktop control management, and secure network access) provided by Citrix — a technology that we have selected after evaluating it against other well-known virtualization technologies. We have divided the implementation and discussion of our system into two parts: network virtualization and virtual architecture. In the end, Login VSI is used to test the performance of our system.

Federated cloud systems increase the reliability and reduce the cost of the computational support. The resulting combination of secure private clouds and less secure public clouds, together with the fact that resources need to be located within different clouds, strongly affects the information flow security of the entire system. In this paper, the clouds as well as entities of a federated cloud system are assigned security levels, and a probabilistic flow sensitive security model for a federated cloud system is proposed. Then the notion of opacity—a notion capturing the security of information flow—of a cloud computing systems is introduced, and different variants of quantitative analysis of opacity are presented. As a result, one can track the information flow in a cloud system, and analyze the impact of different resource allocation strategies by quantifying the corresponding opacity characteristics.

Summary Although information security technologies (such as digital rights management products) have been proven effective and successful in protecting the confidentiality of sensitive information by providing access control, these technologies have not been widely adopted and used to their potential. One reason for this could be that cost and benefit of these products have not been analyzed in a systematic and quantitative manner to date. As a result, companies do not have an established procedure to evaluate the cost and benefit of implementing these products. In this document, the benefits of implementing a digital rights management product in enterprises are quantified using stochastic Petri nets models and are compared with the security needs of a corporation and potential costs incurred by the implementation process. An evaluating procedure for implementing these products is established. This procedure has the potential to be used to improve the ability of a corporation to make sensible security investment decisions.