Internet-of-Things (IoT) devices are nowadays massively integrated in daily life: homes, factories, or public places. This technology offers attractive services to improve the quality of life as well as new economic markets through the exploitation of the collected data. However, these connected objects have also become attractive targets for attackers because their current security design is often weak or flawed, as illustrated by several vulnerabilities such as Mirai, Blueborne, etc. This paper presents a novel approach for detecting intrusions in smart spaces such as smarthomes, or smartfactories, that is based on the monitoring and profiling of radio communications at the physical layer using machine learning techniques. The approach is designed to be independent of the large and heterogeneous set of wireless communication protocols typically implemented by connected objects such as WiFi, Bluetooth, Zigbee, Bluetooth-Low-Energy (BLE) or proprietary communication protocols. The main concepts of the proposed approach are presented together with an experimental case study illustrating its feasibility based on data collected during the deployment of the intrusion detection approach in a smart home under real-life conditions.
Internet of Things (IoT) devices are nowadays widely used in individual homes and factories. Securing these new systems becomes a priority. However, conducting security audits of these connected objects based on experimental evaluation is a challenging task: it requires the use of heterogeneous hardware components leading to a set of specialised software tools, generally incompatible with each other and often complex to use. In this paper, we present a security audit and penetration testing framework called Mirage. This framework, written in Python, is dedicated to the analysis of wireless communications commonly used by IoT devices, and provides a generic, modular, unified and low level audit environment that is easy to adapt to new protocols. The paper describes the software architecture of Mirage, its goals and main features, and presents a concrete example of security audit performed with this framework.
Bluetooth Low Energy (BLE) is nowadays one of the most popular wireless communication protocols for Internet of Things (IoT) devices. As a result, several attacks have targeted this protocol or its implementations in recent years, illustrating the growing interest for this technology. However, some major challenges remain from an offensive perspective, such as injecting arbitrary frames, hijacking the Slave role or performing a Manin-The-Middle in an already established connection. In this paper, we describe a novel attack called InjectaBLE, allowing to inject malicious traffic into an existing connection. This attack is highly critical as the vulnerability exploited is inherent to the BLE specification itself, which means that any BLE connection can be possibly vulnerable, regardless of the BLE devices involved in the connection. We describe the theoretical foundations of the attack, how to implement it in practice, and we explore four critical attack scenarios allowing to maliciously trigger a specific feature of the target device, hijack the Slave and Master role or to perform a Man-in-the-Middle attack. Finally, we discuss the impact of this attack and outline some mitigation measures.
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