IoT platforms have become quite complex from a technical viewpoint, becoming the cornerstone for information sharing, storing, and indexing given the unprecedented scale of smart services being available by massive deployments of a large set of data-enabled devices. These platforms rely on structured formats that exploit standard technologies to deal with the gathered data, thus creating the need for carefully designed customised systems that can handle thousands of heterogeneous data sensors/actuators, multiple processing frameworks, and storage solutions. We present the SCoT2.0 platform, a generic-purpose IoT Platform that can acquire, process, and visualise data using methods adequate for both real-time processing and long-term Machine Learning (ML)-based analysis. Our goal is to develop a large-scale system that can be applied to multiple real-world scenarios and is potentially deployable on private clouds for multiple verticals. Our approach relies on extensive service containerisation, and we present the different design choices, technical challenges, and solutions found while building our own IoT platform. We validate this platform supporting two very distinct IoT projects (750 physical devices), and we analyse scaling issues within the platform components.

Most of the security threats in relational database applications have their source in client-side systems when they issue requests formalized by Create, Read, Update and Delete (CRUD) expressions. If tools such as ODBC and JDBC are used to develop business logics, then there is another source of threats. In some situations the content of data sets retrieved by Select expressions can be modified and then committed into the host databases. These tools are agnostic regarding not only database schemas but also regarding the established access control policies. This situation can hardly be mastered by programmers of business logics in database applications with many and complex access control policies. To overcome this gap, we extend the basic Role-Based Access policy to support and supervise the two sources of security threats. This extension is then used to design the correspondent RBAC model. Finally, we present a software architectural model from which static RBAC mechanisms are automatically built, this way relieving programmers from mastering any schema. We demonstrate empirical evidence of the effectiveness of our proposal from a use case based on Java and JDBC.

In the business world, database applications are a predominant tool where data is generally the most important asset of a company. Companies use database applications to access, explore and modify their data in order to provide a wide variety of services. When these applications run in semi-public locations and connect directly to the database, such as a reception area of a company or are connected to the internet, they can become the target of attacks by malicious users and have the hard-coded database credentials stolen. To prevent unauthorized access to a database, solutions such as virtual private networks (VPNs) are used. However, VPNs can be bypassed using internal attacks, and the stolen credentials used to gain access to the database. In this paper the Secure Proxied Database Connectivity (SPDC) is proposed, which is a new methodology to enhance the protection of the database access. It pushes the credentials to a proxy server and separates the information required to access the database between a proxy server and an authentication server. This solution is compared to a VPN using various attack scenarios and we show, with a proof-of concept, that this proposal can also be completely transparent to the user