Abstract
Organizations are starting to
realize the significant value of advertising on mobile devices, and a number of
systems have been developed to exploit this opportunity. From a privacy
perspective, practically all systems developed so far are based either on a
trusted third-party model or on a generalized architecture. We propose a system
for delivering context, location, time, and preference-aware advertisements to
mobiles with a novel architecture to preserve privacy. The main adversary in
our model is the server distributing the ads, which is trying to identify users
and track them, and to a lesser extent, other peers in the wireless network. When a node is interested in an ad, it forms a group of
nearby nodes seeking ads and willing to cooperate to achieve privacy. Peers
combine their interests using a shuffling mechanism in an ad-hoc network and
send them through a primary peer to the ad-server. In this way, preferences are
masqueraded to request custom ads, which are then distributed by the primary
peer. Another mechanism is proposed to implement the billing process without
disclosing user identities.
Aim
The aim is to provide a system
for delivering context, location, time, and reference-aware advertisements to
mobiles with a novel architecture to preserve privacy.
Scope
The scope is to implement the
billing process without disclosing user identities, preferences are masqueraded
to request custom ads, which are then distributed by the primary peer.
Existing
System
Whether it is TV, radio,
newspapers, or the Internet, advertisements generate substantial revenues.
According to the Interactive Advertising Bureau (IAB), $8.4 Billion is the U.S.
Internet advertising revenue in the first quarter of 2012. And, as mobile devices
get more involved as media delivery platforms, the worth of advertising on
these devices becomes significant. With billions of mobile users worldwide, it
is indeed a potentially huge market for advertising. Moreover, considering that
a decent fraction of these users own smart phones or tablets certainly expands
this opportunity. These users spend significant time browsing the different
multimedia and gaming capabilities of their devices, making them more exposed
to ads. Also, these devices now come with Wi‑Fi and 3G, meaning they can be
reached virtually everywhere. Add to this GPS capability and computing user
preferences, and a new level of targeted advertising can be attained.
Personalized ads that can match users’ preferences with products and services
in their vicinities have much higher chances of succeeding in capturing these
users’ attention and achieving better customer satisfaction, consequently
increasing the profitability of ads. From a privacy perspective,
practically all systems developed so far are based either on a trusted
third-party model or on a generalized architecture.
Disadvantages
· Most of the developed systems
do not take privacy into consideration. Even in MobiAd, which considers
privacy, there is no clear information on the implementation details and the
billing process.
· The same aspects that make
these devices great platforms for advertising also impose strict guidelines
since they contain key private data, like contacts information and calendar
entries. Hence, proper use and confidentiality of this data should be
respected.
Proposed
System
Mobile advertising relies on
content providers like applications and web pages to deliver ads to users.
Service providers register ads to an ad server, which delivers them to users
through content providers who usually subscribe to host ads for profit making.
When a user accesses an application subscribed to an ad server, the application
requests an ad from the server with the user location and id. The server then
checks based on the id the interests of the user through an online profile, and
delivers targeted ads that refer to service providers in the vicinity of the
user which are relevant to his interests. For example, a user in downtown San
Francisco interested in pizza will get an ad for pizzerias within that
location. After the user clicks the delivered ad, a click report is sent to the
ad server for billing purposes. In this scenario we can make the following
observations about the ad server. It has the ability to track users even if it
declares that such information is not being stored, knowing that most ad
providers acknowledge that they store such information. The ad server has access
to all the users'สน personal information including their interests and location
info, and thus it can easily profile users. Even though such privacy invasion
of user personal information is currently regulated by the industry, several
users decide not to opt-in because of privacy concerns. Thus, implementing a
privacy preserving architecture will ensure a greater extent of penetration of
targeted advertising.
Advantages
This project addresses this gap
by integrating privacy preservation into the design.
1) A simpler overall system
that allows peers to send requests any time, and does not require them to back
off for a certain time after becoming primary.
2) An extended fairness method
that makes fairness in the system long lived, i.e., widespread among all peers,
and not temporary where it only applies to peers in the same group.
3) A new billing system that
does not rely on a trusted third party model (server).
4) A more robust shuffling technique with
multiple encryption levels that greatly increases privacy.
5) An aggregation scheme that
retains privacy even when the number of peers in the group is small.
6) A new caching system that
stores not only application requests but also specific requested ads.
7) Algorithms that make the system more
resilient to malicious attempts to breach user privacy.
8) A thorough overhead analysis
of request delay, generated traffic, and battery energy consumption.
9) A simulation platform for
testing system privacy while varying various system parameters.
System
Architecture
Overall system components
HARDWARE REQUIREMENTS:-
· Processor - Pentium –III
· Speed - 1.1 Ghz
· RAM - 256 MB(min)
· Hard Disk - 20 GB
· Floppy Drive - 1.44 MB
· Key Board - Standard
Windows Keyboard
· Mouse - Two or Three Button Mouse
· Monitor - SVGA
SOFTWARE REQUIREMENTS:-
·
Operating
System : Windows 7
·
Front
End :
JSP AND SERVLET
·
Database :
MYSQL
References
Hassan
Artail, and Raja Farhat “A
PRIVACY-PRESERVING FRAMEWORK FOR MANAGING MOBILE AD REQUESTS AND BILLING
INFORMATION”
Mobile
Computing, IEEE Transactions on
(Volume:14 , Issue: 8 ) September
2014
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