Challenges of Privacy aware Localization on Wearable Devices
In this paper, we give a brief survey of the main research results in the area of wearable localization solutions, with a particular focus on the privacy constraints in the localization on wearable devices. We identify several open research challenges and define open questions for further research directions. It is shown that finding adequate methods to protect the user location privacy on wearables is becoming increasingly important with the advent of new Location Based Services relying on wearable devices. 1 State of the art and motivation The gradual increase1 of IoT connected devices in recent years has been caused by the evolution of wireless technology and advanced discoveries in this field. The expansion in the number of wireless devices in use, and, in particular, in wearable devices, is inextricably intertwined with privacy concerns. Despite their typically small sizes, wearable devices are created to sense, collect, and store the data to assist in various application areas, such as healthcare [1] education [2] or industrial manufacturing [3] Users already spend quite a lot of time with their smartphones in the pockets or close to their bodies, and such smart devices are continuously recording data about their owners. Wearables are also becoming more powerful and smarter in terms of being able to collect more and more userrelated sensitive data, such as biometric parameters, e.g. heart rate, breath rate, sleep patterns, blood pressure, or activity related parameters, e.g. number of steps, location [4] Data sensitivity is defined in the EU GDPR2. There are several significant differences between a smartphone and a wearable device: (i) the smartphone typically serve as a gateway for the wearable, (ii) the location accuracy is still worse on a low cost wearable device than on a smartphone equipped with a GPS receiver, (iii) accuracy requirements may be different for different applications, (iv) certain technologies may not be miniaturized enough for wearables, e.g. angle measurements require large antenna arrays of the order of l/2 (with l being the signal wavelength) and they also exhibit coupling problems. However, wearables of the future have the potential of a much higher user tracking ability, as they might continuously be in use (day and night) and mounted on the body unlike most of the smartphones. Some relevant studies [5, 6] have demonstrated that most of the modern wearable devices include built in sensors, which provide accurate location data, information about physical activity level, and possibly about the user mental health. The study [5] also shows that wearable data are typically easily accessible even without user awareness. There is no unique solution to cover all possible threats appearing in the use of wearable technology. Thus, further research and development are required. Our paper gives an overview of open challenges related to wearable based localization and it is structured as follows. Section 2 describes the main localization technologies applicable to wearables, Section 3 summarizes the challenges and open questions in preserving the location privacy on wearables, while Section 4 concludes the paper. 1See "Internet of Things (IoT) connected devices installed base worldwide from 2015 to 2025 (in billions)" by Statista, 2019: https:/www.statista.com/statistics/471264/iot number of connected devices worldwide/ 2See "What personal data is considered sensitive?" by European Commission, 2019: https:/ec.europa.eu/info/law/law topic/data protection/reform/rules business and organisations/ 2 Localization aspects of wearable technology Wearable devices can be classified in function of their type, their purpose of use, proximity to human body [7] etc. If the wearables are endowed with various wireless sensors and own computationally intensive functions, such as localization features, researchers often call such devices "smart" in order to highlight the difference with other categories of machines without their own computationally intensive features. Three main categories of wearable devices were mentioned in [8] as (i) accessories, such as wrist wearables, head mounted gadgets, and other smart jewelry; (ii) e Textiles, meant to be worn as part of clothes; (iii) e Patches, needed to be tattooed on human body; and we include (iv) smart implants, i.e. sensor implants in human body, typically of nano sizes. Wearables and their in built sensors are a crucial part of wireless data exchange processes. They can support diverse wireless connectivity ranges, from ultra short and short to long ranges (the latter being less common than the former) After collecting data, wearables typically send it to a nearby smartphone or straight to the cloud database for further use. Whereas GPS/GNSS technology can provide an excellent accuracy outdoors, indoor systems require to be equipped with non GNSS sensors, such as accelerometers, gyroscopes, Bluetooth Low Energy (BLE) or WiFi chipsets, for improving range and accuracy of localization. A comparison of main localization techniques that may be utilized of wearables is illustrated in Table 1. The comparison is given in terms of achievable accuracy and privacy levels according to the Authors' evaluation: stands for a good level, stands for a moderate level, stands for a low level. There is clear evidence that usually higher accuracy is achievable in trade off to lower privacy and vice versa. Table 1: Comparison of Main Localization Techniques for Wearables. Title Accuracy Privacy Received Signal Strength (RSS) Fingerprinting (FP) Time of Arrival (TOA) Time Difference of Arrival (TDOA) Angle of Arrival (AOA) Proximity Inertial Infrastructure less (e.g. sounds, lights, odor) One of the goals in future location enabled wearables is to achieve a better user privacy level. For example, the term "location information" raises a number of concerns regarding ethics, such as possible unauthorized access, utilization, disclosure, alteration, and other types of fraud interaction with location sharing [9] The security issue is also related to privacy in the context of a spatiotemporal location's integrity. In case such integrity is compromised, attackers can possibly exploit the user location data. Another aspect related to wearable based localization is the cooperative localization involving proximity based device to device communications (D2D) Indeed, D2D architectures are increasingly penetrating many use cases, in particular, due to the rising trend of the 5G networks [10, 11] One of the main advantages of D2D mode is the ability to share the information without intermediaries, such as access nodes (ANs) which reduces the amount of possible data leaks and decreases the latency by sharing the information directly within the network. Besides, D2D architectures can avoid physical protocol and other level privacy attacks [11] to maintain the integrity of the whole system. Yet a diverse aspect related to wearable based localization is the novel concept of delegation of use [12] referring to pools of (wearable) devices being shared by a pool of different users, i.e. a similar concept with shared bikes in smart cities. All these various aspects of wearable based localization are illustrated in a futuristic vision of a wearable supporting network architecture in Fig. 1. The pool of wearable devices, i.e. the wearable cloud, can be shared, can belong to a static or moving person, and can act as standalone devices connected directly to a service provider or as terminals requiring a gateway (e.g. mobile device) to the network. The service provider related to location is the Location Solution Provider (LSP) namely the provider of the actual location technology (e.g. Google, HERE technologies) and the Location Based Service Provider, namely the provider of a wearable service (e.g. Fitbit, Bittium) [13, 14] Both D2D and AN enabled modes are envisioned in our architecture, with examples of ANs given in Fig. 1 based on cellular, WiFi, or BLE networks (with the note that many other wireless supporting technologies can also fit in here) The numbered places (1 to 5) represent possible weak points of user privacy chain in a wearable architecture, from the cloud servers (numbered with 1) which might be insecure, to the LBSP and LSP providers, which may be offered by the same entity or by different entities, and to D2D or to the device to infrastructure (D2I) wireless links and third parties involved in the Location Based Service (LBS) provisioning.