Improving the Bluetooth Hopping Sequence for Better Security in IoT Devices

Improving the Bluetooth Hopping Sequence for Better Security in IoT Devices

Matt Sinda (Department of Computer Science, Central Michigan University, Mount Pleasant, USA), Tyler Danner (Department of Computer Science, Central Michigan University, Mount Pleasant, USA), Sean O'Neill (Department of Computer Science, Central Michigan University, Mount Pleasant, USA), Abeer Alqurashi (Department of Computer Science, Central Michigan University, Mount Pleasant, USA) and Haeng-Kon Kim (Daegu Catholic University, Daegu, Korea)
Copyright: © 2018 |Pages: 15
DOI: 10.4018/IJSI.2018100109

Abstract

The Internet of Things (IoT) is becoming more pervasive in our daily lives and is being used to add conveniences to our everyday items. There are several standards that are allowing these devices to communicate with each other and ultimately, with our mobile devices. However, in a rush to meet market demand, security was not considered until after the device had already been placed on the market. Most of the work done in improving security has been in the area of encryption. However, with the relatively small footprint of IoT devices, this makes strong encryption difficult. The authors' method will show that the current algorithm used to determine the next Bluetooth frequency hop is vulnerable to attack, and will suggest a novel algorithm to more securely select the next frequency to use. They will simulate their solution algorithmically to showcase their approach and in so doing demonstrate that it moves to the next frequency in a more random pattern than the existing model achieves. In this article, the authors present a new framework for improving security that focuses on the timing of frequency hopping, particularly in Bluetooth. The results show that focusing on different timing sequences for how long a device stays on a particular frequency both fits the current Bluetooth Lite architecture and provides adequate security for IoT devices, as it is demonstrably more random that the existing architecture.
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2. Background Of Iot And Bluetooth

There are different definitions of the term “Internet of Things”. However, almost all these definitions are related to the integration of the physical world with the virtual world of the Internet (Haller, Karnouskos, & Schroth, 2008). Internet of Things should include physical objects one wants to be able to track, to monitor and to interact with. For examples, objects like pallets, cars, machines, fridges, buildings, rooms, as well as animate objects like animals and humans. These objects are also called the entities of interest.

Technical communication devices are required to monitor and interact with one or more entities and make the connection to the Internet - for examples, RFID readers devices, sensors and actuators, computers and mobile phones. Devices constitute entities of interest in its own right when looking at them from a technical or management perspective. Thus, devices are a subset of all the things in the Internet of Things. However, for some reasons the device and the entity of interest should be treated as a special case.

There are computational elements that provide the technical link to the entities of interest - host resources, they offer information about the thing, like an identifier or sensed data, and provide actuation capabilities, too (Haller et al., 2008)

Underlying much of the communication architecture for the IoT is Bluetooth. Bluetooth was designed in an effort to replace cables and allow electronic devices to communicate wirelessly with each one another (McDermott-Wells 2005). Bluetooth was specifically designed to allow for point-to-point, or point-to-multipoint wireless communications in a range typically no more than 10 meters. However, it is possible for Bluetooth to communicate much further if the proper power and antennae are used, though in everyday applications this is not the case. As the standard has developed over the years, it has become an indispensable feature in many devices including: mobile phones, personal computers, gaming controllers, and fitness devices (Want, Schilit, & Laskowski, 2013).

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