Cybercasing and privacy implications of geo tagging

Cybercasing the Joint: On the Privacy Implications of Geo-Tagging

Gerald Friedland 1 Robin Sommer 1,2
1
International Computer Science Institute
2
Lawrence Berkeley National Laboratory

Abstract Sites like pleaserobme.com (see § 2) have started cam-
This article aims to raise awareness of a rapidly emerging
paigns to raise the awareness of privacy issues caused
privacy threat that we term cybercasing: using geo-tagged in- by intentionally publishing location data. Often, how-
formation available online to mount real-world attacks. While ever, users do not even realize that their files contain lo-
users typically realize that sharing locations has some implica- cation information. For example, Apple’s iPhone 3G em-
tions for their privacy, we provide evidence that many (i) are beds high-precision geo-coordinates with all photos and
unaware of the full scope of the threat they face when doing videos taken with the internal camera unless explicitly
so, and (ii) often do not even realize when they publish such switched off in the global settings. Their accuracy even
information. The threat is elevated by recent developments exceeds that of GPS as the device determines its position
that make systematic search for specific geo-located data and in combination with cell-tower triangulation. It thus reg-
inference from multiple sources easier than ever before. In ularly reaches resolutions of +/- 1 m in good conditions
this paper, we summarize the state of geo-tagging; estimate the
and even indoors it often has postal-address accuracy.
amount of geo-information available on several major sites, in-
cluding YouTube, Twitter, and Craigslist; and examine its pro- More crucial, however, is to realize that publishing
grammatic accessibility through public APIs. We then present geo-location (knowingly or not) is only one part of the
a set of scenarios demonstrating how easy it is to correlate geo- problem. The threat is elevated to a new level by the
tagged data with corresponding publicly-available information combination of three related recent developments: (i) the
for compromising a victim’s privacy. We were, e.g., able to find sheer amount of images and videos online that make even
private addresses of celebrities as well as the origins of other- a small relative percentage of location data sufficient for
wise anonymized Craigslist postings. We argue that the secu- mounting systematic privacy attacks; (ii) the availability
rity and privacy community needs to shape the further devel- of large-scale easy-to-use location-based search capabil-
opment of geo-location technology for better protecting users ities, enabling everyone to sift through large volumes of
from such consequences.
geo-tagged data without much effort; and (iii) the avail-
ability of so many other location-based services and an-
1 Introduction notated maps, including Google’s Street View, allow-
ing correlation of findings across diverse independent
Location-based services are rapidly gaining traction in sources.
the online world. With big players such as Google and In this article, we present several scenarios demon-
Yahoo! already heavily invested in the space, it is not strating the surprising power of combining publicly
surprising that GPS and WIFI triangulation are becom- available geo-information resources for what we term cy-
ing standard functionality for mobile devices: starting bercasing: using online tools to check out details, make
with Apple’s iPhone, all the major smartphone makers inferences from related data, and speculate about a lo-
are now offering models allowing instantaneously upload cation in the real world for questionable purposes. The
of geo-tagged photos, videos, and even text messages to primary objective of this paper is to raise our commu-
sites such as Flickr, YouTube, and Twitter. Likewise, nu- nity’s awareness as to the scope of the problem at a time
merous start-ups are basing their business models on the when we still have an opportunity to shape further de-
expectation that users will install applications on their velopment. While geo-tagging clearly has the potential
mobile devices continuously reporting their current loca- for enabling a new generation of highly useful personal-
tion to company servers. ized services, we deem it crucial to discuss an appropri-
Clearly, many users realize that sharing location infor- ate trade-off between the benefits that location-awareness
mation has implications for their privacy, and thus de- offers and the protection of everybody’s privacy.
vice makers and online services typically offer different We structure our discussion as follows. We begin
levels of protection for controlling whether, and some- with briefly reviewing geo-location technology and re-
times with whom, one wants to share this knowledge. lated work in § 2. In § 3 we examine the degree to which

1

we already find geo-tagged data “in the wild”. In § 4 we tematic location-based search: the authors leveraged
demonstrate the privacy implications of combining geo- Foursquare’s “check-ins” to identify users who are cur-
tags with other services using a set of example cybercas- rently not at their homes. However, in this case loca-
ing scenarios. We discuss preliminary thoughts on miti- tions were deliberately provided by the potential victims,
gating privacy implications in § 5 and conclude in § 6. rather than being implicitly attached to files they upload.
Also, geo-tagging is a hazard to a much wider audience,
as even people who consciously opt-out of reporting any
2 Geo-Tagging Today information might still see their location become public
through a third party publishing photos or videos, e.g.,
We begin our discussion with an overview of geo-
from a private party. Besmer and Lipford [1] examine a
tagging’s technological background, along with related
related risk in the context of social networks that allow
work in locational privacy.
users to add identifying tags to photos published on their
Geo-location Services. An extensive and rapidly
profile pages. The authors conduct a user study that re-
growing set of online services is collecting, providing,
veals concerns about being involuntarily tagged on pho-
and analyzing geo-information. Besides the major play-
tos outside of a user’s own control. They also present a
ers, there are many smaller start-ups in the space as well.
tool for negotiating photo sharing permissions.
Foursquare, for example, encourages its users to con-
stantly “check-in” their current position, which they then To mitigate the privacy implications, researchers
propagate on to friends; Yowza!! provides an iPhone ap- have started to apply privacy-preserving approaches
plication that automatically locates discount coupons for from the cryptographic community to geo-information.
stores in the user’s current geographical area; and Sim- Zhong et al. [4] present protocols for securely learning
pleGeo aims at being a one-stop aggregator for location a friend’s position if and only if that person is actually
data, making it particularly easy for others to find and nearby, and without any service provider needing to be
combine information from different sources. aware of the users’ locations. Olumofin et al. [7] discuss
In a parallel development, a growing number of sites a technique that allows a user to retrieve point-of-interest
now provide public APIs for structured access to their information from a database server without needing to
content, and many of these already come with geo- disclose the exact location. Poolsappasit et al. [8] present
location functionality. Flickr, YouTube, and Twitter all a system for location-based services that allows specifi-
allow queries for results originating at a certain location. cation and enforcement of specific privacy preferences.
Many third-parties provide services on top of these APIs. From a different perspective, Krumm [5] offers a survey
PicFog, for example, provides real-time location-based of ways that computation can be used to both protect and
search of images posted on Twitter. Such APIs have also compromise geometrical location data.
already been used for research purposes, in particular for GPS and WIFI Triangulation. Currently, it is mostly
automated content analysis such as work by Crandall et high-end cameras that either come with GPS functional-
al. [2], who crawled Flickr for automatically identifying ity or allow separate GPS receivers to be inserted into
landmarks. their Flash connector or the so-called “hot shoe”. Like-
Locational Privacy. Location-based services take wise, it is mostly the high-end smartphones today that
different approaches to privacy. While it is common to have GPS built in, including the iPhone, Android-based
provide users with a choice of privacy settings, the set of devices, and the newer Nokia N-series. An alternative
options as well as their defaults tend to differ. YouTube, (or additional) method for determining the current lo-
for example, uses geo-information from uploaded videos cation is WIFI access point or cell-tower triangulation:
per default, while Flickr requires explicit opt-in. Like- correlating signal strengths with known locations allows
wise, defaults differ across devices: Apple’s iPhone geo- a user or service to compute a device’s coordinates with
tags all photos/videos taken with the internal camera un- high precision, as we demonstrate in § 4. If a device
less specifically disabled; with Android-based phones, does not directly geo-tag media itself, such information
the user needs to turn that functionality on. can also be added in post-processing, either by correlat-
The privacy implications of recording locations have ing recorded timestamps with a corresponding log from
seen attention particularly in the blogosphere. However, a hand-held GPS receiver; or manually using a map or
these discussions are mostly anecdotal and rarely con- mapping software.
sider how the ease of searching and correlating infor- Metadata. For our discussion, we are primarily con-
mation elevates the risk. From a more general perspec- cerned with geo-tagging, i.e., the process of adding lo-
tive, the EFF published a thoughtful white-paper on Lo- cation information to documents later uploaded online.
cational Privacy [3], discussing implications of secretly The main motivation for geo-tagging is the personalized
recording peoples’ activity in public spaces. organizing and searching that it enables. For example,
Pleaserobme.com [9] was probably the first ef- by including current location and time with a series of
fort that demonstrated the malicious potential of sys- vacation photos, it becomes easy to later group them au-

2

tomatically, as well as to find further photos online from much more quickly than those that do. This would then
others who visited the same place. indicate that such an opt-in policy is indeed suitable to
The most common mechanism for associating loca- contain the amount of geo-tagging.
tions with photos are EXIF records, which were orig- We also examined the brands of cameras used for
inally introduced by the Japan Electronic Industry De- taking the photos that have geo-information, derived
velopment Association for attaching metadata to images from their EXIF records which can be retrieved via
such as exposure time and color space. Since then EXIF Flickr’s API as well. Doing so however requires one
has been extended to also cover geographical coordinates API request per image, and hence we resorted to ran-
in the form of latitude and longitude. Currently, EXIF is domly sampling a 5% set of all geo-tagged images up-
used only with JPEG and TIFF image files and WAV au- loaded in 2010. We found that the top-five brands were
dio files. However, most other multimedia formats can Canon (31%), Nikon (20%), Apple (6%), Sony (6%),
contain metadata as well, often including geo-tags. For and Panasonic (5%). A closer look at the individual mod-
videos, proprietary “maker notes” are the most common els confirms our observation in § 2 that today it is mostly
form for storing locations. All these formats are easy devices at the higher end of the price scale that are geo-
to parse with the help of standard tools and libraries, in- tagging.
cluding browser plugins for revealing metadata as well as YouTube. Like Flickr, YouTube also allows queries
Apple’s Preview program that offers a convenient Locate restricted to specific locations. With YouTube however,
button for geo-tags taking one directly to Google Maps. due to restrictions of its API, it is not possible to di-
In general, metadata can pose a privacy risk by storing rectly determine the number of geo-tagged videos, as we
unexpected information not immediately apparent when can with Flickr. YouTube restricts the maximum num-
opening a document. Murdoch and Dornseif [6] demon- ber of responses per query to 1,000; and while it also
strated that editing software may leave thumbnails of the returns an (estimated) number of total results, that fig-
original image behind in EXIF data, and similar prob- ure is also capped at 1,000,000. Still, we believe we can
lems have been found with other formats, such as Word estimate the share of geo-tagged videos in the follow-
and PDF documents. ing way: We first submitted a number of different un-
It turns out, however, that many automatic image ma- constrained queries that each yielded a set of 1,000,000
nipulation tools—especially those used in content man- results. We then refined these queries by adding an addi-
agement systems—“accidentally” discard metadata dur- tional filter to include only videos that had geo-location.
ing processing. For that reason, we find that images on We found that the sizes of the remaining result sets range
many of the larger Web sites do not have any metadata from about 30,000 to 33,000 videos. In other words, out
attached. As we discuss in § 4, we did however find EXIF of what we assume to be a random sample of 1,000,000
data (and thus also locations) on private homepages and YouTube videos, roughly 3 % have geo-location. While
blogs as well as on sites such as Craigslist and TwitPic. this number is clearly an estimate, it matches with what
we derived for Flickr. 1
3 Prevalence of Geo-Tagged Data Craigslist. The virtual flea market Craigslist allows
users to include photos with their postings by either up-
In this section a number of experiments are presented that loading them directly to the company’s servers, or by in-
aim at understanding to what degree image and video serting external HTML IMG links. In the former case,
data is geo-tagged today. images are recoded and stripped off their metadata. In the
Flickr. Flickr has comprehensively integrated geo- latter case, however, such a link can point to the original
location into its infrastructure and it provides a powerful image as taken by the poster’s camera and thus may still
API for localized queries. This API allows direct queries have its EXIF records intact. To estimate the number of
on the number of images that are, or are not, geo-tagged geo-tagged photos linked to from Craigslist postings, we
within a certain time interval. Examining all 158 mil- examined all postings to the San Franscisco Bay Area’s
lion images uploaded in the first four months of 2010, For Sale section over a period of four days (including a
we found that about 4.3% are geo-tagged. When looking weekend). While Craigslist does not provide a dedicated
at the development over past years, we see—somewhat query API, it offers RSS feeds that include the postings’
counter-intuitively—a declining trend: while there was full content. Consequently, during our measurement in-
steep increase in geo-tagging from 2004 to about the end terval, we queried a suitably customized RSS feed every
of 2006 (when it peaked at 9.3%), its share has been de- 10 minutes for the most recent 500 postings having im-
clining to the current level since then. We speculate that ages, each time downloading all linked JPEGs that we
Flickr’s opt-in privacy policy is the reason for this devel- had not yet seen. In total, we collected 68,729 images,
opment: as more users are joining Flickr, the number of 1 YouTube’s API distinguishes between videos without location,
those explicitly enabling EXIF import is likely shrinking, with coarse location (usually manually added, e.g. “Berlin”), and with
and thus the number of images not geo-tagged is rising exact location. For our experiments, we only considered the latter.

3

# Model # Model it for sale (see Figure 1). When we then entered the geo-
414 iPhone 3G 6 Canon PowerShot SD780 coordinates that the phone embedded into the picture into
287 iPhone 3GS 3 MB200 Street View, Google was able to locate the photo’s posi-
98 iPhone 2 LG LOTUS
tion within +/−1 m. Such accuracy is much higher than
32 Droid 2 HERO200
what we believe most people would expect.
26 SGH-T929 2 BlackBerry 9530
20 Nexus One 1 RAPH800 Among the Craigslist postings with geo-information
9 SPH-M900 1 N96 we also found a significant number where the poster
9 RDC-i700 1 DMC-ZS7 chose to not specify a home address, phone number,
6 T-Mobile G1 1 BlackBerry 9630 or e-mail account and opted for Craigslist’s anonymous
emailing option. We take this as an indication that many
Table 1: Devices geo-tagging photos found on Craigslist. posters were not aware that their images were geo-tagged
and thus leaked their location information.
of which about 48% had EXIF information. 914 images We note that while we only performed experiments
were tagged with GPS coordinates, i.e., about 1.3% of with Craigslist’s “For Sale” category, it is not hard
the total. We presume that this number is lower than what to imagine what consequences unintended geo-tagging
we found for Flickr and YouTube because many photos might have in “Personals” or “Adult Services”.
on Craigslist are edited before posting. Still, already with Twitter. Blogging has become a common tool for
a cursory look we found several cases where precise lo- celebrities to provide their fans with updates on their
cations had the potential to compromise privacy, as we lives, and most of such blogs contain images. Likewise,
discuss in § 4. We also examined the camera models used many celebrities now also use public Twitter feeds that,
to take the geo-tagged Craigslist photos (Table 1). While besides potentially being geo-tagged themselves, may
the iPhone models are clearly ahead of all other models, also link to external images they took. Our second sce-
it is interesting to see a wide range of other devices. nario therefore involved tracking a popular reality-TV
host who is very active on Twitter. His show is broad-
cast on US national television and has been exported into
4 Cybercasing Scenarios various foreign countries. In recent episodes, the chan-
nel even began advertising that the host is maintaining a
In this section we take the perspective of a potential at-
tacker to investigate examples of cybercasing. We fo- Twitter feed. It turns out that most images posted to that
cus on four different scenarios: one on Craigslist, one on feed—including photos taken at the host’s studio, places
Twitter, and two on YouTube. To not further harm the where he walks his dog, and of his home—were taken
privacy of the persons involved in our experiments, we with an iPhone 3GS and are hosted on TwitPic, which
refrain from describing identifying specifics. conserves EXIF data. In addition, we noticed that the
host is also commonly tweeting while he is traveling or
Craigslist. In our first scenario, we manually in-
meeting other well-known people away from home. Us-
spected a random sample of Craigslist postings contain-
ing the Firefox plug-in Exif Viewer, a right-click on any
ing geo-located images, collected as described in § 3.
of the Twitter images suffices to reveal these locations
One typical situation we found was a car being offered
using an Internet map service of one’s choice. Again, av-
for sale with images showing it parked in a private park-
eraging geo-tags from multiple images taken at the same
ing space. Most of the time it was straight-forward for us
location would increase accuracy further.
to verify a photo’s geo-location by comparing the image
Geo-location can also be exploited for taking the op-
with what we saw on Google Street View.
posite route: finding a celebrity’s non-advertised Twit-
A fair number of postings with geo-located images
ter feed intended only for private purposes (e.g., for ex-
also offered other high-valued goods, such as diamonds,
changing messages with their personal friends2). Doing
obviously photographed at home, making them potential
so becomes possible with sites such as Picfog, which al-
targets for burglars. In addition, many offered specifics
lows anybody to search all images appearing on Twit-
about when and how the owner wants to be contacted
ter by keyword and geo-location in real-time. Hav-
(“please call Sunday after 3pm”), enabling speculation
ing a rough idea of where a person lives thus allows a
about when somebody might not be at home. Since many
user to tailor queries accordingly until the right photo
postings published more than one image, and some loca-
shows up. As an experiment, we succeeded in finding a
tions were the origin of more than one offer, a more ac-
non-advertised but publicly-accessible Twitter-feed of a
curate estimation of the postal address would have been
celebrity with a residence in Beverly Hills, CA.
possible through averaging the geo-tags.
YouTube. In our final setup, we examined whether
While we did not further verify addresses, we set
one can semi-automatically identify the home addresses
up an experiment to assess GPS accuracy in a typical
of people who normally live in a certain area but are cur-
Craigslist setting: We first photographed a bike in front
rently on vacation. Such knowledge offers opportunities
of a garage with an iPhone 3G, as if we wanted to offer
2 By default, Tweets are public and do not require authentication.

4

Figure 1: Photo of a bike taken with an iPhone 3G and a corresponding Google Street View image based on the stored geo-
coordinates. The accuracy of the camera location (marked) in front of the garage is about +/−1 m. Many classified advertisements
come with photos of objects offered for sale, with geo-tags automatically added.

for burglars to break into their unoccupied homes. We “home”. This time, we found a person who seemed to
wrote a script using the YouTube API that, given a home have moved out of the city. While many of that person’s
location, a radius, and a keyword, finds a set of matching videos had been geo-tagged with coordinates at a specific
videos. For all the videos found, the script then gath- address in San Francisco, the most recent video was at a
ers the associated YouTube user names and downloads place in New Jersey for which Google Maps offered a
all videos that are a certain vacation distance away and real-estate ad including a price of $ 399,999. The person
have been uploaded the same week. had specified age and real name in his YouTube entry.
In our first experiment, we set the home location to be Finally, we note that using our 204-line Python script we
in Berkeley, CA, downtown and the radius to 60 miles. were able to gather all the data for these two experiments
As the keyword to search for we picked “kids” since within about 15 minutes each.
many people publish home videos of their children. The
vacation distance was 1000 miles. Our script reported
1000 hits (the maximum number) for the initial set of 5 Improving Locational Privacy
videos matching “kids”. These then expanded to about
50,000 total videos in the second step, identifying all Educating users about its misuse potential is clearly key
other videos from the corresponding users. 106 of these to avoid wide-spread misuse of location information.
turned out to have been taken more than 1000 miles away However, it is our experience that currently, even many
and uploaded the same week. Sifting quickly through tech-savvy users find it difficult to accurately assess the
the titles of these videos, we found about a dozen that risk they face. We thus believe that the security and pri-
looked promising for successful cybercasing. Examin- vacy community needs to take a more active role in shap-
ing only one of them more carefully, we already had a ing the deployment of this rapidly emerging technology.
hit: a video uploaded by a user who was currently travel- We deem it crucial to ensure that users (i) are put into
ing in the Caribbean, as could clearly be seen by content, a position where they can make informed decisions; and
geo-tagging, and the date displayed in the video (one day (ii) are sufficiently protected unless they explicitly opt-in
before our search). The title of the video was similar to to potentially risky exposure. In the following, we frame
“first day on the beach”. Also, comments posted along preliminary suggestions towards this end.
with the video on YouTube indicated that the user had On a general level, we encourage our community to
posted multiple vacation videos and is usually timely in aim for a consensus on what constitutes an acceptable
doing so. When he is not on vacation, he seemed to privacy policy for location-based services. Current ap-
live with his kids near Albany, CA (close to Berkeley) proaches differ widely across devices and services, and
as several videos were posted from his home, with the we believe that establishing a unified strategy across
kids playing. Although the geo-location of each of the providers would go a long way towards avoiding user
videos could not be pinpointed to a single house due to confusion and thus unnecessary exposure. More specif-
GPS inaccuracies indoors, the user had posted his real ically, we believe that a global opt-out approach to shar-
name in the YouTube profile, which would likely make it ing high accuracy location-information is almost always
easy to find the exact location using social engineering. inappropriate. Rather, users should need to acknowl-
We also performed a second search with the same pa- edge usage at least on a per-application basis. Apple’s
rameters, except for the keyword which we now set to iPhone 3G takes a step into the right direction by re-

5

photo and video capturing devices, allowing potential at-
tackers to easily “case out joints” in cyberspace. Several
factors aggravate the problem. First, many people are
either unaware of the fact that photos and videos taken
with their cell phones contain geo-location, especially
with such accuracy; or what consequences publishing the
information may have. Second, even experts often fail
to appreciate the easy search capabilities of today’s on-
line APIs and the resulting inference possibilities. Third,
the fact that only a small percentage of all data is cur-
rently geo-tagged must not mislead us into ignoring the
Figure 2: Our mockup of a mobile-phone dialog to give users
more control over the geo-location embedded in their photos.
problem because (i) with all the commercial pressure, the
number seems poised to rise; and (ii) our preliminary ex-
periments demonstrate that even a seemingly small frac-
questing permission each time a new application wants
tion like 1% can already translate into several hundred
to access the GPS sensor. However, its user interface
relevant cases within only a small geographical area.
still has two short-comings: (i) it does not apply that pol-
Finally, we want to emphasize that we are not ad-
icy to photos/videos taken with the internal camera; and
vocating avoiding the use of geo-location in general or
(ii) for each application, it is an all-or-nothing decision.
geo-tagging specifically. It is a wonderful technology
Regarding the latter, it seems that often simply reducing
that drives innovation in many areas. However, we feel
a location’s resolution might already be a suitable trade-
there is a clear need for education, as well as for research
off. As an experiment on how such an approach could be
on designing systems to be location-aware while at the
supported, Figure 2 shows a mockup we did for extend-
same time offering maximum protection against privacy
ing the iPhone’s standard permission dialog with a slider
infringement.
allowing to choose an acceptable resolution for each ap-
plication in intuitive terms. According to the choice, the Acknowledgments We would like to thank Gregor Maier and
device would then strip off a corresponding number of Nicholas Weaver for discussions and feedback, the anonymous
the least-significant digits of any coordinates. Not only reviewers for valuable suggestions, and Michael Ellsworth for
English corrections. This work was supported in part by NSF
would this give users more control, but it would also ex-
Award CNS-0831779 and by NGA NURI #HM11582-10-1-
plicitly point out that house-level accuracy is in the cards.
0008. Opinions, findings, and conclusions or recommendations
For jail-broken iPhones, there are already 3rd-party tools are those of the authors and do not necessarily reflect the views
available that spoof the location information visible to of the supporters.
other applications.
An alternative approach is enforcing privacy policies References
at the time when files are uploaded to public reposito-
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Cybercasing and privacy implications of geo tagging

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