Vertical Fragmentation of Location Information to Enable Location Privacy in Pervasive Computing

International Journal of Ambient Systems and Applications (IJASA) Vol.1, No.1, March 2013

Vertical Fragmentation of Location Information
to Enable Location Privacy in Pervasive
Computing

Jeeva Susan Jacob1 and Preetha K.G2
1
Rajagiri School of Engineering and Technology, Rajagiri Valley, Cochin, India
jeevasj27@gmail.com
2
Rajagiri School of Engineering and Technology, Rajagiri Valley, Cochin, India
preetha_kg@rajagiritech.ac.in

Abstract.
The aim of the development of Pervasive computing was to simplify our lives by integrating
communication technologies into real life. Location aware computing which is evolved from pervasive
computing performs services which are dependent on the location of the user or his communication
device. The advancements in this area have led to major revolutions in various application areas,
especially mass advertisements. It has long been evident that privacy of personal information, in this
case location of the user, is rather a touchy subject with most people. This paper explores the Location
Privacy issue in location aware computing. Vertical fragmentation of the stored location information of
users has been proposed as an effective solution for this issue.

Keywords: Pervasive Computing, Location Aware Computing, Location Privacy, Privacy
issues, Vertical Fragmentation, Ubiquitous Computing.

1 Introduction
Pervasive computing techniques integrate three converging areas namely computing,
communications and user interfaces to simplify the lives of users. This is accomplished with
the assistance of a handheld user device like a smartphone. It imparts the reverse concept of
Virtual Reality; to create a real life situation virtually using computing technologies. Pervasive
computing enables the notion of anytime anywhere computing practically possible.
Communication with diverse daily use devices can be done in most situations with the help of
smartphones, sensors and the transceiver devices installed in them.
As an example, consider a situation where you are walking on a road. Your pervasive device,
mostly a smartphone, tracks your location and senses other parameters related to your
movement. If you have an accident and you faint, your phone can sense that your location is
not compatible with the travelling plan you made. In addition to that, the sensors in the device
can sense your heartbeat, blood pressure, body temperature and so on. So if you are hurt the
device can alert the device in the nearest hospital or ambulance communication system all by
itself. Thus valuable time is saved during accidents. Figure 1 shows this example case in detail.

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Fig. 1. Example for Pervasive Computing Application

Recent advances in technology have paved the way from pervasive computing by enhancing
existing technical methods towards ubiquitous computing. Ubiquitous computing is more
advanced form of pervasive computing where communication does not require a mediator
communication
device like smartphones. Any objects which have transceiver devices integrated in it can
object
communicate with each other. Consider the previous instance of accident itself. Bear in mind
that now you were travelling in a car and you had an accident. Here your car contacts the
nd
ambulance directly through the transceiver devices installed in them, thus utilizing pervasive
computing. Figure 2 shows the previous example in a ubiquitous environment.

Fig. 2. Block Diagram of Location Aware Computing

12

Notice that in this case we are utilizing one of the significant application areas of pervasive
computing; ie, Location aware computing. Location aware computing comprises of systems
which percepts the location information of the users and changes their behavior or perform
and
specific functions according to the instructions preprogrammed. In the example described, the
location information of the user or the car enabled providing speedy and adequate medical
attention to the injured user.
Location information describes a user’s location over a specific period of time. They can be
ation
collected through the following methods.
• Locating Systems
They detect the location of a device or find out the devices existing in a particular
location. It provides the answer to the question: “What is the location of a particular
pervasive device?”
• Location Systems
They detect identification of the device and then determine the location information. It
provides the answer to the question: “What pervasive devices exist in a particular region or
ist
location?”
Location aware computing consists of location sensing through the implementation of various
sensing techniques, processing the location information as per location dependent or location
aware queries and then provide them to advanced applications which execute functions based
e
on this processed data. Figure 3 shows the functioning of Location aware computing.

Fig. 3. Block Diagram of Location Aware Computing

Location information can be collected using the methods of proximity location sensing or
methods
triangulation. Proximity location sensing determines the nearest known location of a device or a
famous site located in the proximity of the pervasive device. In the case of the triangulation
location sensing, some geometrical methods based on displacement and angles are utilized for
rical
location determination. The main methods used are lateration and angulation.

13

Lateration senses the location of a user by performing calculations based on displacements with
a known object. Angulation is a similar method to sense location based on the calculation of
ngulation
angles existing between lines of visions with known objects nearby. Another method for
location sensing which utilizes nonmathematical steps is the scene analysis method. Here the
location can be sensed by comparing and analyzing it with the locations of other prominent
objects in the scene observed. These location sensing methods are shown in figure 4.

Fig. 4. Classification of Location Sensing Techniques
L

2 Location Privacy: Armament for Pervasive Computing
The major applications of location aware computing include location based advertising,
instantaneous medical services, independent travels, resource discovery, network route
selection and the like. The reduction in prices of location sensing hardware and the rise in the
widespread use of personal handheld devices are opening up new opportunities in the domain
of location aware computing.
One of the major challenges in location aware computing is ensuring privacy by the protection
of location information of users. Privacy can be a sensitive issue when it comes to the majority
of people. People insist on maintaining the right to determine who should be acquainted with
what amount of information about them. Misusing location information can lead to major
location
trouble to people. Exposure of the location information about some public figures might even
be a threat to their lives.
Disclosing the location of a person can also lead to fraudulent attacks or spam attacks. Who
will be responsible if someone changes the value of a coordinate in our location information to
frame us for a crime we have not committed? Who would be okay with being under the
limelight for each and every second of our lives? Users might always have the feeling of being
feeling
exposed or constantly being tracked by alien eyes. This is because location information can
uniquely identify us, just like our genetic profile. Figure 5 shows the bad effects of revealing
the precise location of an individual.

14


Fig. 5. User being tracked with respect to the location

Major location privacy attacks comprises of impersonation attacks, spam attacks and constant
tracking of user’s whereabouts. Laws have been passed in various countries to preserve the
right of people to take decisions on the usage of data regarding their whereabouts by the
isions
government or other communication service providers. But these do not cover the location
tracking of users and using this location information for various applications. Effective
methods need to be developed for ensuring location privacy in pervasive computing.
o

3 Related Work
Numerous methods have been proposed by researchers around the world in this field. Privacy
Sensitive Information Diluting Mechanism (PSIUM) [17] ensures privacy in the user location
data collected by service providers by sending multiple location information messages along
with service requests. Device can select the accurate information from these, but the service
providers cannot. Use of mix nodes [1] reorders the packet flow thus confusing attackers since
ket
these packets appear to be independent of each other.
LocServ [1] acts as a middleware layer between location sensing devices and location
dependent applications. It gives the control of location information to corresponding users.
corresponding
Thus it prevents transfer of location information to other third party agencies which may query
the server for location data of users. Another technique is Mist [1], which is specially designed
to provide location privacy for users in pervasive computing environments. The GeoPriv [18]
pervasive
model integrates location based services with location privacy preservation measures for
effective implementation of location based applications. This is designed for applications
dealing with surveying, mapping, tracking and so on.
ng,
Majority of these proposals are for preventing privacy attacks by tracking the traffic flow
through these systems. In this paper, a proposal for preserving privacy of location information

15

of users by preventing attacks on the servers using fragmentation techniques is discussed. Third
party attacks and tracking attacks on the information storage base in the location servers can
thus be prevented by this method.

4 Fragmentation: A Database Trait for Preeminent Storage
Fragmentation is a technique commonly used in database management systems to classify data
belonging to a single database and store them properly. Usually it is done in the case of
distributed systems, where systems distributed among geographically distant regions share
resources and applications. Fragmentation and replication of databases is done to ensure
durability and redundancy of significant data in distributed systems. These are mainly of the
types: horizontal fragmentation and vertical fragmentation.
Horizontal fragmentation is done based on the rows or tuples of the database. This is done to
separate tuples or records belonging to a single database into parts. This may happen when
storage of data need to be divided into separate sections or to retrieve some tuples belonging to
a particular category which complies with some constraint. Reconstruction of the original
database is much easier in this case. Each horizontal fragment with tuples can simply be joined
together or can be joined in the order of their primary key.

Fig. 6. Horizontal Fragmentation of Database

Vertical fragmentation is done based on different attributes of a database. Each fragment is
separated based on a particular attribute related to the tuples. On each fragment a unique key
field is attached so that queries can be executed without rejoining these fragments. In most
cases the primary key of the database is replicated in each fragment.
Figure 7 shows the vertical fragmentation of a database where each fragment has the primary
key field, PK, to interlink them as and when required. By using this method we can fragment
the data regarding the users stored in location servers. This separates the location information
from the user’s personal information. Thus an attack on the data storage cannot effectively
16

reveal a particular user’s location. A malicious attacker may never be able to connect the user
with the corresponding location information when the details of the user lies in separate
fragments of storage.

Fig. 7. Vertical fragmentation of Database with PK as the primary key field

5 Vertical Fragmentation on Location Information
Info
Location information of users is usually maintained in the location servers using Location Area
Identity (LAI). This uniquely identifies the location area (LA) of a particular user at a particular
instant of time.

Fig.8. Vertical Fields of Loc
Location Area Identity (LAI)

This information is stored in the Visitor Location Register (VLR) of the communication
network infrastructure used by the user’s smartphone or handheld device. LAI comprises of
Mobile Country Code (MCC) which identifies the country, Mobile Network Code (MNC)
country,
which identifies the mobile network used and the Location Area Code (LAC) which identifies
unique locations.
When a communication or some other service is requested by the user, the location server
tracks the current location of the user through the handheld device and then provides the
17

suitable service. Thus on querying the database which stores the user’s profile with personal as
well as location information the user can be tracked without much difficulty. So, in order to
prevent attacks on these databases, vertical fragmentation can be applied fragmenting the
vent
personal information and location information into separate modules of storage.
The values for the unique key field to be added to each of these fragments need to be car
carefully
calculated. Here the Subscriber Identity Module (SIM) (19-20 digits), International Mobile
(19 20
Equipment identity (IMEI) (15 or 17 digits), MCC (3 digits) and MNC (2 digits) values are
considered. These are mathematically combined and a fixed length hash value is generated
hash
using a suitable hash function. These values will vary for each user and thus the new key value
generated will also be unique.
A key field with unique key values thus calculated is added to each of the database fragments
containing personal information and location information respectively. When a service request
rsonal
is sent by the user, the server can calculate the unique key field value and then combine the
required records of the fragments to form the original record with both personal and location
information. The request is then processed based on the information gathered and the requested
service can be provided as per the user’s eligibility for receiving that service.
Figure 9 shows the vertical fragmentation of location server databases. In the case of an attack
databases.
on the server, the attacker cannot identify which tuple in the location information fragment
corresponds to the particular entry in the personal information fragment. Also fake requests can
be identified since imposter would not be able to fake location information since SIM and IMEI
numbers are both considered here. In order to ensure more security to the method the hash
function used can be changed periodically.

Fig.9. Vertical Fragmentation to ensure Location Privacy

18

Thus, this method ensures privacy to the users by preventing attacks on the location server
databases by third party or malicious agencies. Since this method separates the location
information from the personal information any outsider who intends to attack finds a whole
load of data with no connection to one another. Unfortunately, it cannot prevent the misuse of
location information by the service provider itself, since all the values considered are known to
it.

6 Future Enhancements
Although the proposed method can ensure privacy of location information from external
attacks, measures need to be adapted to prevent misuse of it by the service provider network.
Privacy Laws may prevent it up to a limit, but effective techniques are required. One method
would be to provide only an approximate value for the location information instead of the
accurate coordinates of the location.
Future work also involves research on methods for preventing other kinds of privacy attacks.
Since enhanced pervasive computing or ubiquitous computing techniques does not depend on
handheld user devices, other hardware independent measures need to be developed.
Advancements in hardware technology and communication standards can accelerate the
transformation from Pervasive computing to Ubiquitous computing.

7 Conclusion
As Anthony Burgess says, “To be left alone is the most precious thing one can ask of the
modern world”. In a world which is evolving into a global apartment building from a global
village, ensuring location privacy is a crucial fight against the peeping toms of the
communication world. Measures from the world governments, like the Location Privacy
Protection Bill (2011) which forces Google and Apple to get user’s permission before location
information is tracked, reassure the public that all is not lost yet.
This paper discusses the issue of Location Privacy of users in Pervasive computing
environments. Vertical Fragmentation technique has been proposed as a solution for the attacks
on Location Servers and theft of location information. Its effectiveness in preventing third party
attacks and fake users have been analyzed theoretically. Even though internal attacks cannot be
prevented, it ensures location privacy for the users of a reliable service provider.

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Authors

Ms. Jeeva Susan Jacob
M.Tech scholar at Rajagiri School of Engineering and Technology, Cochin,
India. Completed B.Tech Degree from Mahatma Gandhi University, Kerala
India. Research areas of interest include Mobile Computing, Pervasive
Computing, Green Computing, Computer Networks and Wireless
Communication.

Ms. Preetha K.G.
Assistant Professor at Rajagiri School of Engineering and Technology, Cochin,
India. Currently pursuing research in Mobile Adhoc Networks. Research areas
of interest include Mobile Computing, Adhoc Networks, Computer Networks,
and Wireless Communication.

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Vertical Fragmentation of Location Information to Enable Location Privacy in Pervasive Computing

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