Anonymization Mechanism for Privacy-Preserving Location Monitoring System in WSN

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1 Anonymization Mechanism for Privacy-Preserving Location Monitoring System in WSN D.Gayathri 1, Abdul Vahed 2 1 Student,M.Tech (CSE), 2 Assistant Professor,CSE Department, Sri Sunflower college of Engineering and Technology, Lankapalli. Abstract Data anonymization is the process of destroying tracks or the electronic trail on the data that would lead an eavesdropper to its origins. An electronic trail is the information that is left behind when someone sends data over network. Anonymizing wireless sensor networks allow users to access services privately by using a series of routers to hide the client s IP address from the server. In the network there can be a privacy threat of which users can view the content of the other users. Users can even modify copy or perhaps delete the information. Here we introduce an effective location tracking process. This system involves two algorithms resource algorithm and quality aware algorithm. Both the algorithms depend on the k-anonymity privacy concept. Resource algorithm is aimed at notifying server any time two users communicate where as quality aware algorithm aims to find the aggregate location on the files which tend to be accessed by other users. The server system may also view the user screen and the current application that are running on the person system. Thus the systems inside a network can possibly be securely monitored by the server and this transferred files as well as their formats tend to be graphically. Keywords location privacy, resource aware algorithm, wireless sensor networks(wsn) Wireless sensor networks (WSN): Main purpose of the WSN is to monitor some physical phenomena (e.g., temperature, barometric pressure, light) inside an area of deployment. Nodes are equipped with radio transceiver, processing unit, battery and sensor(s). Nodes are constrained in processing power and energy, whereas the base stations are not severely energy resources. The base station act as gateways between the WSN and other networks such as Internet etc... The WSN is used in various applications like military, health and commercial. WSNs are becoming one of the building blocks of pervasive computing. They provide simple and cheap mechanism for monitoring in the specified area. But WSN technology is an inappropriate use can significantly violate privacy of humans. WSNs are frequently deployed to collect sensitive information. WSN can be used to monitor the movements of traffic in a city. Such a network can be used to determine location of people or vehicles. The sensor nodes such networks are deployed over a geographic area by aerial scattering or other means. Each sensor node can only detect events within a very limited distance, called the sensing range. In addition, sensor nodes normally have fairly limited transmission and reception capabilities so that sensing data have to be relayed via a multihop path to a distant base station (BS), which is a data collection centre with sufficiently powerful processing capabilities and resources. With identity sensors, the system can pinpoint the exact location of each monitored person. Unfortunately, monitoring personal locations with a potentially un-trusted system poses privacy threats to the monitored individuals, because an adversary could abuse the location information gathered by the system to infer personal sensitive information. For the location monitoring system using identity sensors, the sensor nodes report the exact location information of the monitored persons to the server; thus using identity sensors immediately poses a major privacy breach. Although the counting sensors by nature provide aggregate location information, they would also pose privacy breaches. I. INTRODUCTION Fig1:Privacy Preserving protections in WSNs II. LITERATURE SURVEY Once the programmers start building the tool the programmers need lot of external support. Before building the system the above consideration are taken into account for developing the proposed system. Overview We now discuss the privacy threat in existing location monitoring systems. In an identity-sensor location monitoring system, since each sensor node reports the exact location information of each monitored object to the server, the adversary can pinpoint each object's exact location. On the other hand, in a counting-sensor location monitoring system, each sensor node reports the number of objects in its sensing area to the server. ISSN: Page 2447

2 The particular adversary can map the monitored elements of the sensor nodes to the system layout. If the object count of the monitored area is very small or comparable to one, the adversary can infer the actual identity of the monitored objects while using mapped monitored area. However, when many users decide never to reveal their locations, the position monitoring system cannot provide almost any useful services. The closest work to ours will be the hierarchical location anonymization algorithm that divides the system space into hierarchical levels while using physical units, for example, sub-rooms, areas and floors. We consider the situation of how to utilize the anonymized location data to provide privacypreserving location monitoring services. III. A. Problem Definition: SYSTEM ANALYSIS We consider the problem of how to utilize the anonymized location data to provide privacy-preserving location monitoring services while the usability of anonymized location data was not discussed in other privacy related works include: anonymous communication that provides anonymous routing between the sender and the receiver. B. Existing System Existing location monitoring systems in an identity-sensor location monitoring System, since each sensor node reports the exact location information of each 0monitored object to the server, the adversary can pinpoint each object's exact location. On the other hand, in a counting-sensor location monitoring system, each sensor node reports the number of objects in its sensing area to the server. The adversary can map the monitored areas of the sensor nodes to the system layout. C. Limitations of Existing System We consider the problem of how to utilize the anonymized location data to provide privacy-preserving location monitoring services while the usability of anonymized location data was not discussed in other privacy related works include: anonymous communication that provides anonymous routing between the sender and the receiver. D. Proposed System and Advantages This paper elaborated a privacy-preserving location monitoring system for wireless sensor networks to provide monitoring services with help of anonymization algorithms, namely, resource- and quality-aware algorithms. The estimated distribution is used to provide location monitoring services through answering range queries, while preserving the monitored object's location privacy. IV. REQUIREMENTS A. HARDWARE REQUIREMENTS: System : Pentium IV 2.4 GHz. Hard Disk : 40 GB. Floppy Drive : 1.44 Mb. Monitor : 15 VGA Colour. Mouse : Logitech. RAM : 512 Mb. B. SOFTWARE REQUIREMENTS: Operating system : Windows XP or higher. Coding Language : JDK 1.6 Tools : Eclipse Indigo Front End : Swing(JFC) Back End :SQL server C. FUNCTIONAL REQUIREMENTS: Functional requirements specify which output file should be produced from the given file they describe the relationship between the input and output of the system, for each functional requirement a detailed description of all data inputs and their source and the range of valid inputs must be specified. D. NON FUNCTIONAL REQUIREMENTS: Describe user-visible aspects of the system that are not directly related with the functional behavior of the system. Non-Functional requirements include quantitative constraints, such as response time (i.e. how fast the system reacts to user commands.) or accuracy ((.e. how precise are the systems numerical answers.) E. PSEUDO REQUIREMENTS: The client that restricts the implementation of the system imposes these requirements. Typical pseudo requirements are the implementation language and the platform on which the system is to be implemented. These have usually no direct effect on the users view of the system. V. MODULES DESCRIPTION 1. WSN LOCATION MONITORING MODULE The location monitoring system using identity sensors, the sensor nodes report the exact location information of the monitored persons to the server; thus using identity sensors immediately poses a major privacy breach. To tackle such a privacy breach, the concept of aggregate location information, that is, a collection of location data relating to a group or category of persons from which individual identities have been removed, has been suggested as an effective approach to preserve location privacy. Although the counting sensors by ISSN: Page 2448

3 nature provide aggregate location information, they would also pose privacy breaches. 2. AGGREGATE LOCATIONS MODULE VI. A. Data Flow Diagram SYSTEM DESIGN We design two in-network location anonymization algorithms, namely, resource- and quality-aware algorithms that preserve personal location privacy, while enabling the system to provide location monitoring services. Both algorithms rely on the well established k-anonymity privacy concept that requires a person is indistinguishable among k persons. In our system, sensor nodes execute our location anonymization algorithms to provide k- anonymous aggregate locations, in which each aggregate location is a cloaked area A 3. MAPPED LOCATION MONITORING MODULE SENSOR NODES: Each sensor node is responsible for determining the number of objects in its sensing area, blurring its sensing area into a cloaked area A, which includes at least k objects, and reporting A with the number of objects located in A as aggregate location information to the server. We do not have any assumption about the network topology, as our system only requires a communication path from each sensor node to the server through a distributed tree. Each sensor node is also aware of its location and sensing area. The DFD is also called as bubble chart. It is a simple graphical formalism that can be used to represent a system in terms of the input data to the system, various processing carried out on these data, and the output data is generated by the system B. Modelling Rules There are several common modelling rules when creating DFDs: 1. All processes must have at least one data flow in and one data flow out. 2. All processes should modify the incoming data, producing new forms of outgoing data. 3. Each data store must be involved with at least one data flow. 4. Each external entity must be involved with at least one data flow. C. Project Architecture SERVER: The server is responsible for collecting the aggregate locations reported from the sensor nodes, using a spatial histogram to estimate the distribution of the monitored objects, and answering range queries based on the estimated object distribution. Furthermore, the administrator can change the anonymized level k of the system at anytime by disseminating a message with a new value of k to all the sensor nodes. SYSTEM USERS: Authenticated administrators and users can issue range queries to our system through either the server or the sensor nodes, as depicted in Above System Architecture figure. The server uses the spatial histogram to answer their queries. 4. MINIMUM BOUNDING RECTANGLE (MBR) We find the minimum bounding rectangle (MBR) of the sensing area of A. It is important to note that the sensing area can be in any polygon or irregular shape. Fig 2:System Architecture VII. PROCESS SPECIFICATION A. Input Design The input design is the link between the information system and the user. It comprises the developing specification and procedures for data preparation and those steps are necessary to put transaction data in to a usable form for processing can be achieved by inspecting the computer to read data from a written or printed document or it can occur by having people keying the data directly into the system. The design of input focuses on controlling the amount of input required, controlling the errors, avoiding delay, avoiding extra steps and keeping the process simple. The input is designed in such a way so that it provides security and ease of use with retaining the privacy. Input Design considered the following things: ISSN: Page 2449

4 Objectives: What data should be given as input? How the data should be arranged or coded? The dialog to guide the operating personnel in providing input. Methods for preparing input validations and steps to follow when error occur. 1. Input Design is the process of converting a user-oriented description of the input into a computer-based system. This design is important to avoid errors in the data input process and show the correct direction to the management for getting correct information from the computerized system. 2. It is achieved by creating user-friendly screens for the data entry to handle large volume of data. The goal of designing input is to make data entry easier and to be free from errors. The data entry screen is designed in such a way that all the data manipulates can be performed. It also provides record viewing facilities. 3. When the data is entered it will check for its validity. Data can be entered with the help of screens. Appropriate messages are provided as when needed so that the user will not be in maize of instant. Thus the objective of input design is to create an input layout that is easy to follow Signal important events, opportunities, problems, or warnings. Trigger an action. Confirm an action. C. Techniques: Resource-Aware Algorithm &Quality-aware Algorithms: The resource-aware algorithm aims to minimize communication and computational cost, while the qualityaware algorithm aims to minimize the size of cloaked areas in order to generate more accurate aggregate locations. The quality-aware algorithm starts from a cloaked area A, which is computed by resource aware algorithm. Then A will be iteratively updated based on extra communication among the sensor nodes until its area reaches the minimal possible size. For both algorithms, the sensor node reports its cloaked area with the number of monitored persons in the area as an aggregate location to the server. Fig 3:-Steps in resource aware algorithm B. Output design A quality output is one, which meets the requirements of the end user and presents the information clearly. In any system results of processing are communicated to the users and to other system through outputs. In output design it is determined how the information is to be displaced for immediate need and also the hard copy output. It is the most important and direct source information to the user. Efficient and intelligent output design improves the system s relationship to help user decision-making. 1. Designing computer output should proceed in an organized, well thought out manner; the right output must be developed while ensuring that each output element is designed so that people will find the system can use easily and effectively. When analysis design computer output, they should Identify the specific output that is needed to meet the requirements. 2.Select methods for presenting information. 3.Create document, report, or other formats that contain information produced by the system. The output form of an information system should accomplish one or more of the following objectives. Convey information about past activities, current status or projections of the Future. Fig 4:-Steps in quality aware algorithm To avoid reporting aggregate locations with a containment relationship to the server validation is required. We do not allow the sensor nodes to report their aggregate locations with the containment relationship to the server, because combining these aggregate locations may pose privacy leakage. Sensor network has a large number of sensor nodes hence it is very costly for a sensor node to gather the information of all the sensor nodes to compute its minimal cloaked area. To reduce the cost, node determines a search space based on the input cloaked area computed by the resource-aware algorithm. To provide location monitoring services based on the aggregate location information, we propose a spatial histogram approach that analyzes the aggregate locations reported from the sensor nodes to estimate the distribution of the monitored objects. The estimated distribution is used to provide location monitoring services through answering range queries. We evaluate our system through simulated experiments. ISSN: Page 2450

5 VIII. CONCLUSION In this paper, we propose an efficient location tracking system and we explained two anonymization algorithms namely resource and quality aware algorithm and we efficiently track the client and the path of the files. To minimize communication and computational cost resource aware algorithm used. To minimize the size of cloaked areas in order to generate more accurate aggregate locations, quality aware algorithm used. Location monitoring services based on the aggregate location information. While preserving the monitored object's location privacy, the results supporting statement that high quality monitoring services guaranteed. REFERENCES [1] A. Harter, A. Hopper, P. Steggles, A. Ward, and P. Webster,.The anatomy of a context-aware application,. in Proc. of MobiCom, [2] N. B. Priyantha, A. Chakraborty, and H. Balakrishnan,.The cricket location-support system,. in Proc. of MobiCom, [3] B. Son, S. Shin, J. Kim, and Y. Her,.Implementation of the realtime people counting system using wireless sensor networks,. IJMUE, vol. 2, no. 2, pp , [4] M. Gruteser, G. Schelle, A. Jain, R. Han, and D. Grunwald,.Privacyaware location sensor networks,. in Proc. of HotOS, [5] G. Kaupins and R. Minch,.Legal and ethical implications of employee location monitoring,. in Proc. of HICSS, [6] Location Privacy Protection Act of 2001, techlawjournal.com/cong107/privacy/location/s1164is.asp.. [7] D. Culler and M. S. Deborah Estrin,.Overview of sensor networks,. IEEE Computer, vol. 37, no. 8, pp , [8] A. Perrig, R. Szewczyk, V. Wen, D. E. Culler, and J. D. Tygar,.SPINS: Security protocols for sensor netowrks,. in Proc. of MobiCom, [9] J. Kong and X. Hong,.ANODR: Anonymous on demand routing with untraceable routes for mobile adhoc networks,. in Proc. Of MobiHoc, ISSN: Page 2451

A Collaborative Approach to Enhance Security in Location Based Services by Answering Range Queries in WSN

A Collaborative Approach to Enhance Security in Location Based Services by Answering Range Queries in WSN 1 Anandhi, 2 S.Amudha 1 Student, 2 Assistant Professor 1 Software Engineering, SRM University,