Charles V. Neu

Roben C. Lunardi, Regio A. Michelin, Charles V. Neu et al.

The Internet of Things (IoT) is transforming our physical world into a complex and dynamic system of connected devices on an unprecedented scale. Connecting everyday physical objects is creating new business models, improving processes and reducing costs and risks. Recently, blockchain technology has received a lot of attention from the community as a possible solution to overcome security issues in IoT. However, traditional blockchains (such as the ones used in Bitcoin and Ethereum) are not well suited to the resource-constrained nature of IoT devices and also with the large volume of information that is expected to be generated from typical IoT deployments. To overcome these issues, several researchers have presented lightweight instances of blockchains tailored for IoT. For example, proposing novel data structures based on blocks with decoupled and appendable data. However, these researchers did not discuss how the consensus algorithm would impact their solutions, i.e., the decision of which consensus algorithm would be better suited was left as an open issue. In this paper, we improved an appendable-block blockchain framework to support different consensus algorithms through a modular design. We evaluated the performance of this improved version in different emulated scenarios and studied the impact of varying the number of devices and transactions and employing different consensus algorithms. Even adopting different consensus algorithms, results indicate that the latency to append a new block is less than 161ms (in the more demanding scenario) and the delay for processing a new transaction is less than 7ms, suggesting that our improved version of the appendable-block blockchain is efficient and scalable, and thus well suited for IoT scenarios.

Daniel Dalalana Bertoglio, Guilherme Girotto, Charles Varlei Neu et al.

Mobile applications are used to handle different types of data. Commonly, there is a set of personal identifiable information present in the data stored, shared and used by these applications. From that, attackers can try to exploit the mobile application in order to obtain or to cause private data leakage. Therefore, performing security assessments is an important practice to find vulnerabilities in the applications and systems before the application is deployed, or even during their use. Regarding security assessments, Penetration Test (Pentest) is one of the security test types that can be used to detect vulnerabilities through simulated attacks. Additionally, Pentest can be performed using different methodologies and best practices, through several frameworks to: organize the test execution, execute tools, provide estimations, provide reports and document a Pentest. One such framework is Tramonto, which aims to assist a cybersecurity expert during the Pentest execution by providing organization, standardization and flexibility to the whole Pentest process. This paper presents a Pentest case study applied to a Brazilian university Mobile App using the Tramonto framework. The main goal of this case study is to present how Tramonto can be applied during a Pentest execution, assisting cybersecurity experts in the tasks included in the Pentest process. Our results show details on how to perform a Pentest using Tramonto and the found vulnerabilities in the Mobile App. Besides that, there is a discussion about the main contributions obtained from our results, and we were able to verify that Tramonto managed, organized and optimized the whole Pentest process.