Biblio

In this research we propose a framework that will strengthen the IoT devices security from dual perspectives; avoid devices to become attack target as well as a source of an attack. Unlike traditional devices, IoT devices are equipped with insufficient host-based defense system and a continuous internet connection. All time internet enabled devices with insufficient security allures the attackers to use such devices and carry out their attacks on rest of internet. When plethora of vulnerable devices become source of an attack, intensity of such attacks increases exponentially. Mirai was one of the first well-known attack that exploited large number of vulnerable IoT devices, that bring down a large part of Internet. To strengthen the IoT devices from dual security perspective, we propose a two step framework. Firstly, confine the communication boundary of IoT devices; IoT-Sphere. A sphere of IPs that are allowed to communicate with a device. Any communication that violates the sphere will be blocked at the gateway level. Secondly, only allowed communication will be evaluated for potential attacks and anomalies using advance detection engines. To show the effectiveness of our proposed framework, we perform couple of attacks on IoT devices; camera and google home and show the feasibility of IoT-Sphere.

Internet of Things (IoT) devices industry is rapidly growing, with an accelerated increase in the list of manufacturers offering a wide range of smart devices selected to enhance end-users' standard of living. Security remains an after-thought in these devices resulting in vulnerabilities. While there exists a cryptographic protocol designed to solve such authentication problem, the computational complexity of cryptographic protocols and scalability problems make almost all cryptography-based authentication protocols impractical for IoT. Wireless RFF (Radio Frequency Fingerprinting) comes as a physical layer-based security authentication method that improves wireless security authentication, which is especially useful for the power and computing limited devices. As a proof-of-concept, this paper proposes a universal SDR (software defined Radio)-based inexpensive implementation intended to sense emitted wireless signals from IoT devices. Our approach is validated by extracting mobile phone signal bursts under different user-dedicated modes. The proposed setup is well adapted to accurately capture signals from different telecommunication standards. To ensure a unique identification of IoT devices, this paper also provides an optimum set of features useful to generate the device identity fingerprint.