Secure Cloud Storage with Client-Side Encryption Using a Trusted Execution Environment

With the evolution of computer systems, the amount of sensitive data to be stored as well as the number of threats on these data grow up, making the data confidentiality increasingly important to computer users. Currently, with devices always connected to the Internet, the use of cloud data storage services has become practical and common, allowing quick access to such data wherever the user is. Such practicality brings with it a concern, precisely the confidentiality of the data which is delivered to third parties for storage. In the home environment, disk encryption tools have gained special attention from users, being used on personal computers and also having native options in some smartphone operating systems. The present work uses the data sealing, feature provided by the Intel Software Guard Extensions (Intel SGX) technology, for file encryption. A virtual file system is created in which applications can store their data, keeping the security guarantees provided by the Intel SGX technology, before send the data to a storage provider. This way, even if the storage provider is compromised, the data are safe. To validate the proposal, the Cryptomator software, which is a free client-side encryption tool for cloud files, was integrated with an Intel SGX application (enclave) for data sealing. The results demonstrate that the solution is feasible, in terms of performance and security, and can be expanded and refined for practical use and integration with cloud synchronization services

A Comparative Analysis of Agile Teamwork Quality Measurement Models

Multiple models (or instruments) for measuring Teamwork Quality (TWQ) for Agile Software Development can be found in the literature. Regardless, such models have different constructs and measures, with no empirical evidence for comparing them. This study analyzed two agile TWQ models, resulting in equivalent results. We mapped the models\u27 variables given their definitions.We then collected data using both a Bayesian Network model, namely the TWQ-BN model, and Structural Equation Modeling, namely the TWQ-SEM model. We interviewed 162 team members from two software development companies. We analyzed the data using the Bland-Altman method. We obtained enough evidence to conclude that the results for Communication, Coordination, Cohesion and Mutual Support variables are not equivalent. On the other hand, we did not have enough evidence to claim that the models do not agree for measuring Effort and Balance of member contribution variables. The results of this study detail how two state-of-the-art agile TWQs compare in terms of their measures as well as potential research areas for further investigation