Design optimization of iot models: structured safety and security flaw identification

Abstract

More and more devices are being interconnected, thus extending the use of Internet of Things (IoT) systems. However, the larger the networks are the more vulnerable and inscrutable they become. This is a significant challenge especially when IoT is used in safety- and security-critical areas. In these areas, a flawless architecture must be guaranteed already in the design phase. Therefore, a structured possibility is needed to scan models completely for vulnerabilities as early as possible. We developed a pattern recognition framework (PRF) that enables the definition of design patterns and anti-patterns. These patterns are used for a holistic and automated identification of flaws in IoT models during design phase and enable a design optimization.