Users’ Privacy Concerns About Wearables

Abstract

Wearables have become popular in several application domains, including healthcare, entertainment and security. Their pervasiveness, small size and autonomy, enlarges the potential of these devices to be employed in different activities and scenarios. Wearable devices collect data ubiquitously and continuously, about the individual user and also her surroundings, which can pose many privacy challenges that neither users nor stakeholders are ready to deal with. Before designing effective solutions for developing privacy-enhanced wearables, we need first to identify and understand what are the potential privacy concerns that users have and how they are perceived. To contribute to that purpose, in this paper we present findings from a qualitative content analysis of online comments regarding privacy concerns of wearable device users. We also discuss how form factors, sensors employed, and the type of data collected impact the users’ perception of privacy. Our results show that users have different levels and types of privacy concerns depending on the type of wearable they use. By better understanding the users’ perspectives about wearable privacy, we aim at helping designers and researchers to develop effective solutions to create privacy-enhanced wearables.

Full text

Users’ Privacy Concerns About Wearables:
Impact of Form Factor, Sensors and Type of Data Collected
Vivian Genaro Motti and Kelly Caine
School of Computing, Clemson University, Clemson, USA
{vgenaro,caine@clemson.edu}
Abstract. Wearables have become popular in several application domains, in-
cluding healthcare, entertainment and security. Their pervasiveness, small size
and autonomy, enlarges the potential of these devices to be employed in differ-
ent activities and scenarios. Wearable devices collect data ubiquitously and con-
tinuously, about the individual user and also her surroundings, which can pose
many privacy challenges that neither users nor stakeholders are ready to deal
with. Before designing effective solutions for developing privacy-enhanced
wearables, we need first to identify and understand what are the potential priva-
cy concerns that users have and how they are perceived. To contribute to that
purpose, in this paper we present findings from a qualitative content analysis of
online comments regarding privacy concerns of wearable device users. We also
discuss how form factors, sensors employed, and the type of data collected im-
pact the users’ perception of privacy. Our results show that users have different
levels and types of privacy concerns depending on the type of wearable they
use. By better understanding the users’ perspectives about wearable privacy, we
aim at helping designers and researchers to develop effective solutions to create
privacy-enhanced wearables.
Keywords. Privacy; Wearable Computing; Wearable Devices; Form Factors;
Privacy Concerns; User studies; Human Factors
1 Introduction
The significant advances in technology in the past decades, characterized by the min-
iaturization of components, more efficient power sources, alternative network solu-
tions and novel sensors, boosted the development of wearable devices. As a conse-
quence, a variety of form factors have been created, enabling wearable devices to be
applied for multiple different purposes. Despite the large potential and known benefits
of wearable devices, their spread usage entails several privacy concerns. Wearables,
by continuously collecting, transmitting and storing data, handle information that are
often considered as personal, private, sensitive or confidential. This information can
be publicly available or posted in social media, where it is shared with a network of
friends of the individual user or even with unknown or untrusted parties. While the
data collection and sharing brings many benefits for end users, it also brings novel
privacy challenges for stakeholders involved in the creation of wearable devices and

applications. Wearables enable the surveillance and sousveillance of individuals, their
behaviors and surroundings as well, which can lead to severe privacy implications,
threats and risks. These issues affect not only the individual user but also the society
and organizations involved, for instance when the data collected are misused. Due to
the novelty of the wearable field such implications are not yet fully understood.
The continuous use of wearables involves a variety of privacy concerns, however
because the usage of these devices is relatively recent, users are not aware of the po-
tential privacy implications of continuous data collection, storage and online sharing.
To better understand how users actually perceive wearable privacy and to identify
what are their main concerns nowadays, we collected commentaries from users (end
users and prospective users) from online sources (such as IT forums, websites, discus-
sion lists and social medias) about several wearable devices (either commercially
available or to be soon launched in the market) including head-mounted and wrist-
mounted devices. With the analysis of the users’ comments extracted from a set of
online sources, we identified different concerns about wearable privacy, and we ana-
lyzed how they are related to specific form factors, sensors employed and data col-
lected.
The main contributions of this paper consist in identifying: i) what are the users’
concerns for wearable privacy; ii) how form factors, data collected and sensors em-
ployed impact these privacy concerns (regarding their levels and nature); and iii) what
concerns are specific to wearable devices, sensors and applications.
This paper is organized as follows: Section 2 motivates and contextualizes this re-
search by presenting related works and the scope in which this research is inserted;
Section 3 describes the method of the research; Section 4 presents the results ob-
tained; Section 5 discusses them and Section 6 concludes.
2 Related Work
Privacy concerns are not exclusive from the technological domain, being discussed
since 1890 [1]. Despite being in discussion for a long time, privacy issues related to
mobile technologies are relatively new, complex to study and still poorly understood
[2]. Moreover, mobile and wearable devices continuously collect data, spreading the
use of sensors, such as: cameras, GPS, and accelerometers, whose small size and in-
visibility adds novel challenges to ensure users’ privacy.
Most of the previous works on user privacy has focused on mobile devices and
their applications [3], social networks [4,5], web applications [6], or other security
concerns, as account hijacking [7]. Little is known about wearable privacy [8,9] from
a human-centered perspective. Existing solutions frame the privacy problems too
narrowly and satisfactory general solutions remain elusive [8], besides having a frag-
mented landscape [5]. The nature of privacy concerns remains an open question, re-
quiring a better understanding of privacy behaviors in technology [10].
The following sections summarize related research findings, presenting and dis-
cussing privacy concerns and human perspectives in ubiquitous, mobile and wearable
computing.

2.1 Privacy in Ubiquitous Computing
Characterized by the integration of computational solutions into the physical envi-
ronment, ubiquitous computing enables inanimate objects to acquire intelligence, by
sensing, processing and communicating data [11]. These data concern the individual
user and also her surroundings, and can imply in privacy issues. Despite the existence
and importance of these issues, users have a limited understanding about those. By
centering potential solutions for privacy-enhanced technologies on the users’ perspec-
tives and concerns, stakeholders can aid users to better understand and control their
privacy in these systems [12].
2.2 Privacy in Mobile Devices
Significant improvements in mobile computing in the past decades popularized the
use of mobile devices, with smart phones and mobile apps playing nowadays a fun-
damental and intimate role in users’ everyday life. Despite the continuous data collec-
tion and transmission with these devices and apps, previous research shows that users
are not aware about what data are collected and how they are used [3]. Despite the
importance of mobile privacy concerns, they still remain poorly understood [2].
2.3 Privacy in Wearable Devices
Similarly to ubiquitous and mobile computing, in wearable computing, privacy is one
of the main challenges yet to be solved [13]. Not only because wearable computers
are able to sense, process and store intimate information about the users, but also
because wearables are able to do it continuously and discreetly [14]. Besides this,
currently, users cannot fully understand the potential risks, threats and implications
involved with data collection and tend to underestimate those. However the data col-
lected often enable to infer private information, especially when combined with other
data, which can result in significant risks to the users’ privacy [15].
As previous research identified, privacy became a key concern to users [14], being
for instance among the top five concerns that users consider important in the weara-
bility of HMD (head-mounted devices) [16]. Despite its relevancy, wearable privacy
is still an emergent topic and many questions remain open.
Previous works related to wearable privacy have focused on its different aspects,
including: i) users’ behaviors with wearable cameras, to identify the factors that im-
pact how sensitive a photo is [9] and the privacy concerns in pictures illustrating eat-
ing behaviors of users [17]; ii) requirements for remote communication in fashion
garments [18]; iii) perceptions of anklet wearers, to identify location-based privacy
concerns [8]; iv) privacy for augmented reality systems [19]; and v) surveillance con-
cerns of Google Glass users [20]. Although these works aid to understand how users
perceive wearable privacy, they focus on specific wearable devices or applications.

2.4 Users’ Perspectives on Privacy
Privacy behaviors across multiple technologies were identified and analyzed in [10],
aiding to understand the users’ perspectives and concerns and to propose and devise
novel solutions to ensure users’ privacy. Despite extensive user studies, this work
targets a general understanding of privacy concerns, regardless of the technology
employed. User studies were also conducted by [21], to better understand users’ pri-
vacy concerns. This work, although focused on e-commerce applications, suggests a
significant gap between reported concerns and actual users’ behaviors, reinforcing
that users often sacrifice their privacy in exchange of benefits. For [22], considering
current users’ needs and their cognitive models is key to ensure privacy control. The
users’ understanding about privacy was also analyzed in [6], but mainly regarding
their interaction with web sites.
Despite previous works focusing on ubiquitous, mobile and wearable computing, it
is still not clear what are the users’ concerns about wearable privacy and how these
are related to specific devices, sensors and applications. However, without under-
standing what the privacy problems are, privacy cannot be addressed in a meaningful
way [23].
3 Methods
Because we were interested in assessing the privacy perceptions of a broad range of
people who already had interest or experience in using wearable devices, and we
wanted to gather a geographically and demographically diverse sample, we chose to
conduct an observational study of online comments posted by wearable users. To
identify concerns, we extracted comments from a series of online sources (described
below). First, we selected a set of devices and data sources, then we identified, select-
ed and analyzed the users’ concerns about privacy in wearable devices. Further details
about the methodology of this work are described in the following sections.
3.1 IRB Approval
To ensure the protection of human subjects, before data collection started, the Clem-
son University Institutional Review Board (IRB) approved this study as exempt.
3.2 Data Selection, Extraction and Analysis
Due to the fact the head-mounted and wrist-mounted devices are the most popular
form factors available and in use today, we considered both form factors for data col-
lection. To minimize bias in the data collected we selected a set of 59 different online
sources, including popular websites for discussion and reviews of technology and e-
commerce pages for shopping, reviewing and recommending devices. The data col-
lection process resulted in more than 2,000 commentaries extracted for analysis. This
process was conducted in April and May 2014 and consisted in visiting the online

sources previously selected, searching for the users’ comments regarding specific
devices, and manually extracting the contents of interest to compose a report.
For the analysis, we filtered and selected the commentaries related to privacy con-
cerns. For that a member of our research team read and analyzed each comment, to
identify and annotate those related to privacy. Then, the annotated comments were
analyzed again to identify the nature of the privacy concern regarding its motivations
and rationale behind it. For example, a user who fears the consequences of his/her
location being posted online in a live feed through social media apps concerns the
Implications of Location Disclosure). In order to identify the relationships between
the privacy concerns and respective data collected and sensors, we analyzed the na-
ture of the concerns identified and assessed whether they were specific to a given
form factor and/or application or generic to mobile devices. The results of this analy-
sis are graphically presented in a Venn diagram (Figure 1).
3.3 Devices, Online Data Sources and Figures
The users’ commentaries collected were generated at latest in May 2014. The date
when a commentary was posted was not always available in the web sources selected,
however users start commenting about a new device usually when a vendor announce
it, launch it for sale or when a new release is made available. The comments collected
were related to six wrist-mounted devices with different purposes, including:
• 27 privacy comments about six armbands and smart watches: Sony SWR10 (Core)
Smartwear and Thalmic Labs Myo, Basis, Qualcomm Toq, LG Lifeband Touch,
Razer Nabu.
The users’ commentaries about the 32 head-mounted devices analyzed, included:
• 11 privacy comments about 19 earpieces, headbands and headphones: Looxcie, LG
Lifeband Earphones, Intel Smart Earbuds, Microsoft Septimu, Avegant glyph, the
Immersion headset, The Vigo, iRiver On, The Voyager Legend, NeuronOn,
Recon’s Snow 2, The Cynaps Enhance, iWinks Aurora Dreamband, Life Beam’s
Sports Headband, Emotiv Insight, Axio EEG Headband, InteraXon Muse, Muzik,
Neurowear Zen tune Headphones;
• 34 privacy comments about 13 glasses: EmoPulse Nano Glass, Epson Moverio BT-
200, Google Glass, Google Smart Contact Lenses, ICIS, K-Glass, Laster See Tru,
Meta Pro, Oculus Rift, Olympus MEG4.0, Second Sight’s Argus II, Sony HMz-T1,
The Atheer One, Vuzix Smart Sun Glasses.
The 59 online sources used for data collection included 15 forums, 34 technical
websites, 6 e-commerce websites, and 4 social medias, e.g.: Amazon, Ars Technica,
BestBuy, CNET, ComputerWorld, DigitalTrends, ExpertReviews, Engadget, eWeek,
Geek, GizMag, GizModo, Overstock, PCAdvisor, PCMag, PCPro, PCWorld,
PhoneArena, Popular Science, Mashable, MIT Technology Review, Reddit, Slate,
TechCrunch, TechRadar, TheInquirer, TheNextWeb, TheVerge, T3, TrustedReviews,
Wearable Computing Review, Wearable Technologies, Wired, ZDNet. With a diver-

sity of sources, we aimed at more representativeness in the data collected and mini-
mizing the potential bias of commentaries that were not posted by actual users. The
main differences among the comments consisted in: more extensive, detailed and
formal comments produced by reviewers (posted in IT forums), and shorter, more
informal and objective comments produced by end users and posted in e-commerce
websites. By gathering comments from heterogeneous sources, we ensure a diversity
of user profiles, and still focus on the study goals, covering a set of specific wearable
devices and privacy concerns of users for different wearable applications.
The analysis of online reviews has some drawbacks, for instance, little is known
about the profile of the user who posted a comment and we cannot ensure whether the
comment was in fact generated by an individual user or by a bot, a spammer or even a
competitor company, which can introduce bias in the study. In our analysis, to mini-
mize this risk, we selected heterogeneous online sources (59 websites with high popu-
larity) and an extensive list of comments (n>2,000). Despite these drawbacks, as pre-
vious research indicate [24, 25, 26, 27], the analysis of online reviews has several
benefits as well, for instance: i) users are placed in a wild study, i.e. not constrained
by laboratory settings, ii) the commentaries are self-reports of the users’ opinions,
without a standard format or pre-defined set of questions, and iii) a large sample of
reviews can be analyzed covering heterogeneous user profiles.
4 Identifying User Privacy Concerns for Wearable
Technologies
The analysis of the online comments, revealed 13 users’ concerns about wearable
privacy. These concerns are closely related to the type of data each device collects,
stores, processes and shares. Embedded sensors, such as cameras and microphones,
capture data about the individual user or people nearby, often without their awareness
or consent. These data are oftentimes personal, confidential, and sensitive, which
poses privacy challenges, for instance regarding surveillance. Other sensors, such as
heart rate monitors, glucometers and activity trackers, are often considered by users as
involving fewer privacy concerns.
By analyzing the users’ commentaries, 13 privacy concerns emerged, six for wrist-
mounted devices and seven for head-mounted devices. These concerns are presented
in the following sections, ordered by form factor and the activity they are related to,
respectively: data collection, data processing and data sharing (according to the three
first groups of activities defined in the Solove’s privacy taxonomy [23]).
4.1 Privacy Concerns for Wrist-Mounted Devices
Wrist-mounted devices collect data whose nature is less sensitive than head-mounted
devices, at least in a first sight. Some HMDs are able to capture audio, image and
videos, whose privacy implications tend to be more critical or at least apparent for
users. WMDs, on the other hand, often include activity trackers and sense the user
location, which is considered by users as less privacy-critical data. Actually, from our

analysis, the GPS sensor is pointed as the most critical privacy concern for users of
WMDs, as their location is sensed and stored, and sometimes even shared online in
real time through live feeds of social media applications. Besides this, the form fac-
tors of wrist-mounted devices are similar to conventional accessories worn in a daily
basis, such as watches and bracelets, so they fit seamlessly in conventional outfits of
users, raising less attention or suspicion from other people. Among the six privacy
concerns identified for WMDs and presented below, the two first ones are related to
data collection and the other four refer to data sharing.
4.1.1 General Social Implications: Unawareness
An activity tracker that synchronizes data (e.g., location and photos) and relates it to
the network of friends of an authenticated user, can also impact the privacy of other
people (e.g., individuals belonging to the social network contacts of a given user):
‘it does not just record your activities, but also activities of people around you, it
can also connect to other devices’
The people belonging to the social network of a user are not necessarily aware of
and compliant with the data collected, stored, published or shared.
4.1.2 Right to Forget
When data are continuously collected, stored, published and shared, they can include
information that users do want to recall later, but also events and facts that users were
not willing to capture or to be reminded of later on:
‘it gives a record of everything you’ve done, day in and day out, possibly even
some things you don’t want to be reminded of’
4.1.3 Implications of Location Disclosure
The users’ comments analyzed revealed that users were afraid that their location when
tracked could be disclosed to malicious parties and criminals, such as thieves and
stalkers. These malicious parties could then misuse the user location, for instance to
better plan a crime or other harmful actions:
‘It [wearable device] just knows when to take pictures of the epic moments, know if
you're riding in your car so your friends and stalkers know where you are at all
times of the day, know when you go to sleep, riding a car, or climbing a mountain’
4.1.4 Discrete Display of Confidential Information: Non-disclosure
Wrist-worn devices, such as smart watches, often use a screen to display notifications.
These notifications can include sensitive or confidential information, which is also
accessible to people located close to the end user. Being able to hide this information
from co-located individuals is considered good for some users:

‘the second screen will act as sort of a privacy screen, keeping folks from read-
ing your texts by glancing at your wrist’
4.1.5 Lack of Access Control
Users who are aware about data storage in the cloud, fear that organizations or even
the government will use their personal data without their awareness or consent, for
instance for abusive or malicious purposes:
‘[wearable devices are] the NSA's new best friend’
4.1.6 Users’ Fears: Surveillance and Sousveillance
While most wearable device users acknowledge the many benefits of collecting and
tracking their personal information, they fear the continuous surveillance and
sousveillance and potential implications that this can bring them in the future:
‘I'm not sure if I should be totally excited or totally frightened about this Sony
band logging my every move. I can't help but think it could be good ole big brother
in disguise’
4.2 Privacy Concerns for Head-Mounted Devices
Head-mounted devices that focus on augmented and virtual reality and gaming expe-
riences did not raise as many privacy concerns for users (e.g., Oculus Rift and Sony
HMz-T1), because less sensitive data are collected, and also because the device does
not store or share information, keeping it protected from social media and other online
applications with networks of online users. On the other hand, head-worn computers,
such as Google Glass, which are equipped with cameras and microphones, are often
synchronized with a smart phone, allowing users to connect to social media applica-
tions. This results in several privacy concerns, as indicated our analysis of the users’
commentaries. The next sections detail specific users’ concerns with HMD. Among
the seven users’ concerns, the four first are related to data collection, one to data pro-
cessing, and the last two refer to data sharing.
4.2.1 Speech Disclosure
Using speech recognition enables users to have a hands-free interaction, however
when users are not alone and need to handle confidential information, audio as a
unique input modality poses serious privacy concerns:
‘though you can’t mind people overhearing what you are saying’
4.2.2 Surveillance, Sousveillance and Criminal Abuse
By capturing data without any consent or awareness, users reported that they were
concerned about a potential for criminal abuse:

‘There are a lot of concerns about privacy invasion, spying and situations
where people are more concerned with recording an event than actually engaging
with it’
4.2.3 Surreptitious Audio and Video Recording: Unawareness
Although smart phones and mobile computers such as tablet PCs also include cameras
and microphones, a HMD allows users to start recording content discreetly:
‘the video camera that is even easier to use than a smartphone's … privacy is-
sues are indeed huge with that’
‘Placing a tiny wearable device on someone's eye could potentially be a lot
more discreet, though some privacy advocates might see that as a downside’
‘I do believe there is a difference between snapping pictures with something
which is obviously a camera, and recording video surreptitiously. Social norms al-
ready frown on making surreptitious audio recordings (though it isn't illegal, it is
done only infrequently and with an air of "secret agency" about it); video is much
more of an intrusion.’
‘the more subtle and high tech augmented vision gets, the more dangerous it
gets as well. Basically, we're teetering on a slippery slope here unless we find a so-
lution for the privacy/harassment concern that is growing’
4.2.4 Surveillance, Sousveillance and Social Implications: Unawareness
The fact that the device captures information from the users’ surrounding extends the
privacy issues to the social environment, as people nearby are often unaware or not
compliant with the data collection:
‘There's also another challenge that affects not only those who wear Glass, but
everyone else around: privacy’
Users may not feel comfortable to wear a device with a camera on their heads, at
least nowadays and especially in environments in which this is not a common prac-
tice:
‘The privacy concerns may very well be overblown, but I think it'll take a while
for people to get comfortable with the idea of others walking around with camera-
equipped devices strapped to their faces’
4.2.5 Facial Recognition: Identifiability
Users acknowledge the benefits of facial recognition to augment their memory, how-
ever, they are also aware that privacy concerns will likely emerge in the near future,
as previously pointed out by [28]:
‘…totally needs a camera. I want to be able to look at people and it have them
tell me their names, limit it to my personal database of contacts if you must, but I'm
terrible with names, if it wants to give me an immersive world experience, then it
needs to be able to see what I see regardless of privacy worries.’

‘Privacy officials understand that Google won’t include facial recognition in
Glass for now, but raised concerns about Google’s future facial recognition plans’
‘…image analysis. This of course raises all sorts of new privacy concerns with
things like identifying people through facial recognition associated with Facebook
pictures… ’
4.2.6 Automatic Synchronization with Social Media: Linkability
Some users do not like the idea of their devices to immediately synchronize with so-
cial media applications and share their data without being able to control it:
‘Why in the HELL would I ever want to tweet or facebook from a pair of head-
phones. Isn't there enough horror in the world without these in it?’
‘Oh, how nice! Another unsubscribe factor to add to my unsubscribe rule list.
Tweets from headphones? Unsubscribed!’
‘Can't wait for the trend when not having a Facebook integration is a big
thing…’
4.2.7 Visual Occlusion: Non-disclosure
HMDs that cover the field of view of the user, e.g., Oculus Rift and Sony HMz-T1,
allow users to interact privately because their vision is occluded:
‘Not as a primary display but for those times when I really need some privacy’
‘watch what they want in the privacy of their own rooms.’
‘covered design will enable complete privacy for the viewer.’
‘What I want is a head-mounted replacement for my laptop screen. So I don't have
to have its size, weight, fragility, power consumption, and lack of privacy when I'm
traveling’
‘provide you some privacy for your augmented-reality browsing.’
4.3 Privacy Concerns across Form Factors
The analysis of the users’ comments collected resulted in 13 privacy concerns for
wearable devices, some of them existing regardless of the form factor. By analyzing
these concerns we noticed that some concerns (4) are device-specific, others (3) are
sensor-specific, few (2) depend on the data collected, or (2) are both de-
vice/application- and data-specific:
• Device-specific privacy concerns: social implications (in general, devices that
collect data that do not belong solely to an individual user, impact social aspects of
privacy), criminal abuse (collecting personal data can facilitate criminal abuse), fa-
cial recognition can take place if the appropriate algorithms are available in the de-
vice, social media synchronization are not necessarily a user wish for wearables;
• Sensor-specific privacy concerns: location disclosure is associated with GPS
usage, speech disclosure depends on the ability of using audio as input modality
(HMD with a microphone), and surreptitious audio and video recording (HMD

with cameras) depend on how invisible the sensors are embedded in a device, as
data can be captured without it being noticeable;
• Data-specific privacy concerns: right to forget (all data that are collected without
the consent, awareness or users’ will should be able to be deleted after collection),
users fear that certain data types when combined could have critical implications;
• Device/Application and Data-specific privacy concerns: discrete display and
visual occlusion depends on devices with a screen available which should enable
users to decide what, when and even if information can be displayed.
Most of the users’ concerns, although identified in the analysis of one specific form
factor, can also relate to different devices, depending usually on the availability of a
specific sensor, feature or application. The location disclosure for instance depends
mainly on a GPS to track users’ location, which is usually embedded in a wrist-
mounted device, but can be also found in an anklet or a helmet. Besides the GPS,
other sensors or data sources can also be used to track the users’ location. Figure 1
illustrates how the privacy concerns identified can be placed regarding their influenc-
ing factors.
5 Discussion
From the analysis of the users’ concerns in wearable privacy we note that several
factors affect the privacy concerns among users. These include: the nature of the data
collected, their respective levels of confidentiality and sensitiveness, ability to share
and disclose the information, and also potential implications (social, criminal, etc.).
Fig. 1. Privacy concerns per form factor and according to their influencing factors: de-
vice, application, sensor or data. Concerns marked with a ‘*’ were identified particularly
for head-mounted devices.

The findings indicate that privacy concerns are not necessarily unique to one spe-
cific device or form factor, but are intimately related to the sensors embedded in the
device and the respective data collected. We found that devices that include cameras
and microphones resulted in more and more extreme privacy concerns, followed by
devices with GPS and displays. Activity trackers that monitor heart rate, steps, and
pulse for instance, are usually seen as inoffensive to the users’ privacy, however it is
likely that users are not aware of how such data could be misused by third-parties or
potential privacy implications when the data are collected in a long term or associated
with complementary information.
We also note a significant overlap between the users’ concerns about mobile priva-
cy and wearable privacy, mostly because the tasks that users can perform with weara-
bles are also possible with alternative devices, which were previously used in a large
scale (including cameras, pedometers, and tablet PCs). However from the analysis of
the users’ comments we do notice that specific characteristics of wearables strengthen
these concerns. For example, while cameras and microphones were already employed
in mobile devices, wearables make it easier to record data without other people notic-
ing, so their lack of awareness, compliance and consent becomes more critical for
privacy in the wearable context. Similarly, users have privacy concerns about location
information, primarily because wrist-mounted devices are able to track their position
and immediately publish it online in social media applications to a network of con-
tacts. Users worry that this group can include malicious users and people that the
individual user does not know or trust.
5.1 Limitations
An extensive list of 38 devices has been covered in the analysis of online comments,
however, because the landscape of wearable devices is shifting very rapidly, obvious-
ly this list did not include every wearable device possible. For example, our analysis
of wrist-mounted devices included six devices, mainly armbands and smart watches.
In future work, to complement our research findings, we plan to analyze fitness track-
ers as well, as we hypothesize that this specific type of WMD may pose more privacy
concerns than smart watches and armbands currently do.
Although this work focuses mainly on head and wrist-mounted devices, we believe
that chest and back-mounted devices, such as the Polar band for heart rate monitoring
and Lumo back band for posture tracking could also raise privacy concerns. To ob-
serve this, in future work, we plan to verify potential privacy implications that such
devices could involve, and identify potential users’ concerns.
Collecting and analyzing online data is a relatively new research method, and de-
spite enabling the analysis of large amounts of contents, it involves two main limita-
tions: first, no well-established and validated protocol is available regarding data col-
lection and analysis, so the method employed in this research is both exploratory and
empirical. Second, little is known about the users’ profiles, as all data collected are
anonymous. However, we can assume that users who post online comments access
frequently the web (forums, IT websites) and are interested in technology (to follow
new trends and news in the domain). Despite being a niche of users, which limits the

generalization of the research findings, they also correspond to actual or potential
users interested in wearable technologies.
6 Conclusion
The analysis of the users’ comments shows that the privacy concerns about wearables
are similar, but in some cases more specific than privacy concerns about mobile de-
vices. It also shows that users are aware about potential privacy implications, but
mainly during data collection and sharing. The privacy concerns of users are related
to the ability of the wearable device to sense, collect, and store data, which are often
private, personal, confidential or sensitive, and then share these data with unknown or
untrusted parties.
Users’ concerns about wearable privacy cover different aspects of the user interac-
tion with a wearable, including: disclosure of sensitive information, subtle data collec-
tion (of audio and video), public posts in social media apps (sharing), and lack of
control and awareness regarding who has access to the data collected.
Although the level of privacy concerns of users is similar to that of mobile devices,
the nature of their concerns is critical, showing that because users are somewhat una-
ware about potential privacy implications, vendors should alert them about possible
problems, enabling them to apply a fine-grained control about what is collected,
when, and how, and also how data are shared (who has access).
While there is a long way to go to build wearable devices and applications that are
actually privacy-enhanced, this work brings insight in clarifying the users’ concerns
about wearable privacy, aiding to devise better solutions in the future.
Acknowledgments. This material is based upon work supported by the National Sci-
ence Foundation under Grant No. 1314342. Any opinions, findings, and conclusions
or recommendations expressed in this material are those of the author(s) and do not
necessarily reflect the views of the National Science Foundation.
7 References
1. Warren, S.D., Brandeis, L.D.: Right to privacy. Harvard Law Review, vol. 4, pp. 193–220.
(1890)
2. Mancini, C., Thomas, K., Rogers, Y., Price, B. A., Jedrzejczyk, L., Bandara, A. K., Join-
son, A. N., Nuseibeh, B.: From Spaces to Places: Emerging Contexts in Mobile Privacy.
In: UbiComp’2009, pp. 1–10. (2009).
3. Shklovski, I., Mainwaring, S.D., Skúladóttir, H.H., Borgthorsson, H.: Leakiness and
Creepiness in App Space: Perceptions of Privacy and Mobile App Use. In: CHI '14. ACM,
New York, NY, USA, pp. 2647–2656. http://doi.acm.org/10.1145/2556288.2557421
(2014)
4. Ur, B., Wang, Y.: A cross-cultural framework for protecting user privacy in online social
media. In: Proceedings of the 22nd International Conference on WWW. Steering Commit-
tee (2013)

5. Gürses, S., Diaz, C.: Two Tales of Privacy in Online Social Networks. In: IEEE Security
& Privacy, vol. 11, n. 3, pp. 29–37. Retrieved from http://ijeee.in/wp- con-
tent/uploads/2014/05/IJEEE-131-134.pdf (2013)
6. Reidenberg, J. R. et al.: Disagreeable Privacy Policies: Mismatches between Meaning and
Users’ Understanding (August 15, 2014). Fordham Law Legal Studies. At:
http://ssrn.com/abstract=2418297 (2014)
7. Shay, R., Ion, I., Reeder, R.W., Consolvo, S.: My religious aunt asked why I was trying to
sell her viagra: experiences with account hijacking. In: CHI '14. ACM, New York, NY,
USA, pp. 2657–2666. DOI=10.1145/2556288.2557330 (2014)
8. Troshynski, E., Lee, C., Dourish, P. Accountabilities of Presence: Reframing Location-
Based Systems. In: CHI’2008 Proceedings, pp. 487–496. (2008)
9. Hoyle, R., Templeman, R., Armes, S., Anthony, D., Crandall, D., Kapadia, A.: Privacy
Behaviors of Lifeloggers using Wearable Cameras. In: Proceedings of the 2014 Interna-
tional Joint Conference on Pervasive and Ubiquitous Computing, Seattle, WA, USA, Sep-
tember, pp. 13–17. (2014)
10. Caine, K.: Exploring Everyday Privacy Behaviors and Misclosures. PhD Thesis. Georgia
Institute of Technology, (2009)
11. Schaub, F. M.: Dynamic privacy adaptation in ubiquitous computing. PhD Thesis. Univer-
sität Ulm, (2014)
12. Könings, B., Schaub, F., Weber, M.: Who, How, and Why? Enhancing Privacy Awareness
in Ubiquitous Computing. In: PerCom’2013, March, pp. 364–367. (2013)
13. Starner, T.: The Challenges of Wearable Computing: Part 1. In: IEEE Micro 21, vol. 4 (Ju-
ly 2001), 44- 52. DOI=10.1109/40.946681 http://dx.doi.org/10.1109/40.946681 (2001)
14. Starner, T.: The Challenges of Wearable Computing: Part 2. In: IEEE Micro 21, vol. 4, pp.
54-67. (2001)
15. Raij, A., Ghosh, A., Kumar, S., Srivastava, M.: Privacy risks emerging from the adoption
of innocuous wearable sensors in the mobile environment. Proceedings of the 2011 Annual
Conference on Human Factors in Computing Systems - CHI ’11, 11.
doi:10.1145/1978942.1978945 (2011)
16. Motti, V. G., Caine, K. Understanding the wearability of head-mounted devices from a
human-centered perspective. In: Proceedings of the 2014 ACM International Symposium
on Wearable Computers (ISWC '14). ACM, New York, NY, USA, pp. 83–86.
DOI=10.1145/2634317.2634340 http://doi.acm.org/10.1145/2634317.2634340 (2014)
17. Thomaz, E., Parnami, A., Bidwell, J., Essa, I., Abowd, G.D. Technological approaches for
addressing privacy concerns when recognizing eating behaviors with wearable cameras.
In: UbiComp’2013, pp. 739–748. Retrieved from
http://dl.acm.org/citation.cfm?id=2493509 (2013).
18. Jacob, C., Dumas, B.: Designing for Intimacy: How Fashion Design Can Address Privacy
Issues in Wearable Computing. In Proceedings of the 2014 ACM International Symposium
on Wearable Computers: Adjunct Program (ISWC '14 Adjunct). ACM, New York, NY,
USA, pp. 185–192. DOI=10.1145/2641248.2641353
http://doi.acm.org/10.1145/2641248.2641353 (2014)
19. Roesner, F., Kohno, T., Molnar, D.: Security and privacy for augmented reality sys-
tems. In: Communications of the ACM, vol. 57, no. 4 (April 2014), pp. 88–96.
DOI=10.1145/2580723.2580730 http://doi.acm.org/10.1145/2580723.2580730 (2014).
20. Mcnaney, R., Vines, J., Roggen, D., Balaam, M., Zhang, P., Poliakov, I., Olivier, P.: Ex-
ploring the Acceptability of Google Glass as an Everyday Assistive Device for People with
Parkinson. In: Proceedings of CHI’2014, pp. 1–4. (2014)

21. Berendt, B., Günther, O., Spiekermann, S.: Privacy in e-commerce: stated preferences vs.
actual behavior. In: Communications of ACM, vol. 48, n. 4 (April 2005), pp. 101–106.
DOI=10.1145/1053291.1053295 (2005)
22. Nguyen, D., Mynatt, E.: Privacy Mirrors: Understanding and Shaping Socio-technical
Ubiquitous Computing Systems. Georgia Institute of Technology GVU Technical Report
(GIT-GVU-02-16) (2002)
23. Solove, D.J.: Understanding Privacy, Harvard University Press, May 2008; GWU Legal
Studies Research Paper No. 420; GWU Law School Public Law Research Paper No. 420.
Available at SSRN: http://ssrn.com/abstract=1127888 (2008)
24. Hedegaard, S., Simonsen, J.: Extracting usability and user experience information from
online user reviews. In: Proceedings of CHI’2013, pp. 2089–2098. Retrieved from
http://dl.acm.org/citation.cfm?id=2481286 (2013)
25. Iacob, C., Veerappa, V., Harrison, R.: What are you complaining about?: a study of online
reviews of mobile applications. In: Proceedings of the 27th International BCS Human
Computer Interaction Conference (pp. 6). Retrieved from
http://dl.acm.org/citation.cfm?id=2578086 (2013)
26. Fu, B., Lin, J., Li, L., Faloutsos, C.: Why people hate your app: Making sense of user
feedback in a mobile app store. In: Proceedings of KDD’13. Retrieved from
http://dl.acm.org/citation.cfm?id=2488202 (2013)
27. Khalid, H., Shihab, E., Nagappan, M., Hassan, A.: What Do Mobile App Users Complain
About? A Study on Free iOS Apps, In: Software, IEEE, vol. PP, no. 99, pp.1, 1 DOI:
10.1109/MS.2014.50 (2014)
28. Acquisti, A., Gross, R., Stutzman, F.: Faces of facebook: Privacy in the age of augmented
reality. In: BlackHat Webcast Series USA, (2011)