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- Devika BV
The purpose of this document is to present a detailed description of the Locating Service Similarity with Privacy using queries. It will explain the purpose and features of the system, the interfaces of the system, what the system will do, the constraints under which it must operate and how the system will react to external stimuli.
Location Based Search
Search the neighboring points of interests by custom query
Software Requirements Specification
A document that completely describes all of the functions of a proposed system and the constraints under which it must operate. For example, this document.
End users who use this web application
The details pertaining to the entity with mobile device. Locating the current location of a user needs to be kept private.
Quality metrics that measures the service delivered to an entity, in general. The metrics has definite goal and the percentage is calculated with the actual delivery.
This web application is chosen for an academic study and implementation. Location-based applications utilize the positioning capabilities of a mobile device to determine the current location of a user, and customize query results to include neighboring points of interests. However, location knowledge is often perceived as personal information. One of the immediate issues hindering the wide acceptance of location-based applications is the lack of appropriate methodologies that offer fine grain privacy controls to a user without vastly affecting the usability of the service.
In specific, the following are the contributions towards this project.
- A novel architecture for LBS applications that is directed towards revealing privacy/utility trade-offs to a user before an actual geo-tagged query is made.
- A proof-of-concept design for a privacy-supportive local search location based search.
Exploiting Service Similarity for Privacy in Location Based Search Queries Qin Liu, Guojun Rinku Dewri, Member, IEEE, and Ramakrisha Thurimella
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS VOL:25 NO:2 YEAR 2014
“Supporting Anonymous Location Queries in Mobile Environments with Privacy Grid,”in Proceedings of the 17th International World Wide Web Conference,2008, pp. 237–246.
B. Bamba, L. Liu, P. Pesti, and T. Wang
This section will give an overview of the whole system. The system will be explained in its context to show how the system interacts with other systems and introduce the basic functionality of it. It will also describe what type of stakeholders that will use the system and what functionality is available for each type. At last, the constraints and assumptions for the system will be presented.
To begin with, this is a very dynamic concept. Usability has a twofold meaning a) privacy controls should be intuitive yet flexible, and
b) the intended purpose of an application is reasonably maintained
It is worth mentioning that a separate line of research in analyzing anonymous location traces has revealed that user locations are heavily correlated, and knowing a few frequently visited locations can easily identify the user behind a certain trace. The privacy breach in these cases occurs because the location to identity mapping results in a violation of user anonymity. The system attempts to prevent the reverse mapping—from user identity to user location—albeit in a user-controllable manner.
Mobile search is an evolving branch of information retrieval services that is centered on the convergence of mobile platforms and mobile phones, or that it can be used to tell information about something and other mobile devices. Web search engine ability in a mobile form allows users to find mobile content on websites which are available to mobile devices on mobile networks. The first module is to build a mobile search engine with ranking based approach to retrieve results with respect to the localized position of the user. Geo-tagging is a function, where devices can insert metadata with geographical information (coordinates) into a file such as photo, associating it with the geographic location it was taken at.
In response to this first query phase, the user obtains a service-similarity profile. This profile is a representation of the similarities in the query output at different geographic locations. The exact form taken by this profile, as well as the data structures employed in computing this profile, may vary from application to application. A location movement engine on the user side then determines a noisy location to use based on the user’s privacy profile and the retrieved service-similarity profile.
What is private and what is not private should be actually defined before the query has been raised, this helps the result set not to include those details that are private to the user and thus it would not be shared by the application.
The service-contour inferencing is not just a collection of positions, but includes additional information about the businesses located at those positions such as names, addresses, categories, subcategories. Additionally, some specific values such as feedback score, the entire profile of the entity with personal information, so on and forth.
The following could be the modules for this project:
- Login/Register module
- Search results by ranking module
- Similarity profiler service module
- Service-contour inferencing module
The user is expected to be Internet literate and be able to register/login and know how to search for information from the system. The user is expected to know how to provide information. The interface, however, provides easy access to all these, nonetheless, the user needs to know the basics to operate and get the best results. The user is expected to be Windows literate and to be able to use button, pull-down menus, and similar tools.
There are two types of users who can interact with the system: 1. The registered users who will get access to information of the businesses for a specific location; 2. The business owners who may receive personal information regarding the user at a specific location.
The following Hardware configuration is expected to smoothly execute the project.
Processor – Pentium V or above
Speed – 2.1 GHz or above
RAM – 1 GB RAM
Hard Disk – 60 GB
Key Board – Standard Windows Keyboard
Mouse – Two or Three Button Mouse
Monitor – SVGA
The following Software configuration is expected to smoothly execute the project.
Operating System : Window 7 or above
Language : C# (.NET Language)
Front End : Visual Studio 2010
Database : SQL Server/Express
Web Server :Internet Information Server (IIS 6.0)
Since the application searches data from the database server, it is crucial that there is a good bandwidth/good system resource for the application to function. Data-base search can be laborious when we have larger-data to be executed.
One assumption about the emulator product is that it will be always be used with internet connection, since it has to collect information about a random user moving from the API’s. It is also assumed that the internet connection is stable during these transactions. If not high, a moderate speed is required to operate with the system.
Another assumption is that since the API’s are third-party services, this could go down or may not work as expected at times. However, it is assumed that the down-time may not be longer enough to disrupt the working of our emulators.
This section provides a detailed description of all inputs into and outputs from the system. It also gives a description of the hardware, software and communication interfaces and provides basic prototypes of the user interface.
A first-time user of the mobile application should see the log-in page when user opens the application. If the user has not registered, they should be able to do that on the log-in page. Refer to Fig. 2. If the user is not a first-time user, they should be able to see the latitude and longitude information where the user is current located, see Figure 3. On selecting the user destination, the random movement is simulated and reported by the system.
Fig. 2. Login Screen Fig. 3. Current Location Fig. 4. Random User Movement
No external hardware devices are expected to be used in this project. A system with Windows Operating System running on it should be fine to run the web application.
The communication between the different parts of the system is important since they depend on each other. However, in what way the communication is achieved is not important for the system and is therefore handled by the underlying operating systems and the database for both the cloud and the web application.
The user should be able to register or login (if already a member) from the mobile emulator. The login/register module helps the user to locate his geo location and will be able to view the businesses/services surrounding the user. The system will also ensure that the privacy details of the user are shared only what is made “Public” or “Private” by the user. Modifications to this sensitive information are provided to the user by the system.
In general, a local search application provides information on local businesses, events, and/or friends, weighted by the location of the query issuer. Location and service accuracy trade-offs are clearly present in a local search LBS. A privacy-supportive variant is therefore
well-suited for this application class. Local search results tend to cycle through periods of plateaus and minor changes as one moves away from a specified location. The plateaus provide avenues for relaxation in the location accuracy without affecting service accuracy, while the minor changes allow one to assess accuracy in a continuous manner.
Given a search term (e.g. generic ones such as “cafes”, and targeted ones such as “starbucks
coffee”) and a highly generalized user location (e.g. the metropolitan city), the privacy-supportive LBS generates a concise representation of the variation in the 10-nearest neighbor result set as a hypothetical user moves across the large metropolitan area. Once the representation is communicated to the user, he/she can infer the geographic variability that can be introduced in her location coordinates to retrieve all or a subset of the result set.
This profile is a representation of the similarities in the query output at different geographic locations. The exact form taken by this profile, as well as the data structures employed in computing this profile, may vary from application to application. A location perturbation engine on the user side then determines a noisy location to use based on the user’s privacy profile and the retrieved service-similarity profile. The LBS processes the query with respect to the noisy location.
The result set from the query is not simply a collection of positions, but includes additional attributes about the businesses located at those positions. This could range from names, addresses, categories, subcategories, to specifics such as value, feedback scores, and entire profiles of individuals with personal information. The ranking function is often a well-guarded business secret on how these attributes are combined. Another approach is to send a set of similarity matrices to the user, one each corresponding to a specific co-ordinate in the grid. The approach requires the computation and transfer of an inordinate amount of information.
The requirements in this section provide a detailed specification of the user interaction with the web application software and measurements placed on the system performance. The system on which this client application runs should have installed .NET framework 2. The following software(s) must be installed for smooth implementation of the project.
- Visual Studio 2012
- IIS Web Server/Service
- SQL Server database
- Browser application such as Internet Explorer / Mozilla / Google Chrome
- Windows Mobile Emulator
- Windows operating system with wired or wireless internet connection
All care should be taken to ensure that at any point there is no compromise on the safety requirement during the process of building/executing this project. At this time, there is none that needs serious consideration.
Database should be password-protected. The system should allow access to users only with a login credentials.
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