WLAN Location Sharing through a Privacy Observant Architecture

Localization in WLAN networks has been an active area of research recently. However, most of the previous schemes in this area do not consider the presence of any malicious user within the network. The growing interest in location based services would necessitate the development of a lowcost localization scheme which is robust against the attacks from these malicious users. We have developed such a lowcost secure localization scheme that is based on the current access point (AP) capability of transmitting at different power levels. The main idea here is to leverage this capability of APs so that at every location in the system a unique set of messages transmitted by various APs can be received. The client is expected to transmit back the receiving messages to the AP it is associated with. The location of the client is then estimated using the set of messages received from the client. We intend to present a poster discussing the performance of this scheme along with its inherent security capabilities. The implementation of this message based scheme for a pilot location based service implementation, controlled by the enterprise policy, over a testbed deployment will also be described. We will also present our preliminary experiments which indicate that this scheme has similar or better performance as compared to the traditional signal strength based localization schemes. We intend to discuss various open issues in this area and obtain valuable feedback on this work at the conference. * Note that for any practical deployment there is a significant deviation from the ideal environment assumptions. This is later taken in account during actual deployment in Section III.

2015

Abstract—Indoor Positioning Systems (IPS) have recently received considerable attention, mainly because GPS is unavailable in indoor spaces and consumes considerable energy. On the other hand, predominant Smartphone OS localization subsystems currently rely on server-side localization processes, allowing the service provider to know the location of a user at all times. In this paper, we propose an innovative algorithm for protecting users from location tracking by the localization service, without hindering the provisioning of fine-grained location updates on a continuous basis. Our proposed Temporal Vector Map (TVM) algorithm, allows a user to accurately localize by exploiting a k-Anonymity Bloom (kAB) filter and a bestNeighbors generator of camouflaged localization requests, both of which are shown to be resilient to a variety of privacy attacks. We have evaluated our framework using a real prototype developed in Android and Hadoop HBase as well as realistic Wi-Fi traces scaling-u...

Enriching a mobile device with the ability to detect it's location can enable the provision of a range of Location Based Services to it's user. Outdoors, the location detection facility is sufficiently provided by GPS, however GPS is not suited for the challenge of non-line-of-sight indoor environments. In these environments smaller scale location estimation techniques must be employed. Due to their ubiquity, WiFi signals are a commonly employed indicator of location; knowledge of the identity and intensity of these signals throughout an environment can allow the estimation of the receiving device's location. This paper outlines work towards the development of efficient, privacy conservative positioning algorithms suitable for deployment on commonly available mobile phones. For a number of algorithms, the frequency of correct location prediction is presented along with the execution time on a real mobile phone.

2011

GPS can only be used in outdoors where the satellite signals can be received, so it cannot be used to know the position of a device inside buildings. Cellular networks can be used to locate devices indoors, but the mobile phone network is owned by an enterprise, so a regular user is not allowed to know this information. So, new positioning systems are needed for urban zones and indoor locations. In this paper, we present a geopositioning system that uses public and private WiFi networks placed in cities in order to estimate the location of the user. Then we present the architecture of the system and the prototype implementation. Finally, we will show the developed protocol operation.

2007

This paper describes the current efforts to develop an open source, privacy sensitive, location determination software component for mobile devices. Currently in mobile computing, the ability of a mobile device to determine its own location is becoming increasingly desirable as the usefulness of such a feature enhances many commercial applications. There have been numerous attempts to achieve this from both the network positioning perspective and also from the wireless beacon angle not to mention the integration of GPS into mobile devices. There are two important aspects to consider when using such a system which are privacy and cost. This paper describes the development of a software component that is sensitive to these issues. The ICiNG Location Client (ILC) is based on some pioneering work carried out by the Place Lab Project at Intel. (Hightower et al., 2006) The ILC advances this research to make it available on mobile devices and attempts to integrate GSM, WiFi, Bluetooth and ...

2007

Location privacy is one of the major security problems in a Wireless Personal Area Network (WPAN). An eavesdropper can keep track of the place and time mobile devices are communicating. The hardware address of a device can often be linked to the identity of the user operating the mobile device; this represents a violation of the user's privacy. In this paper, we consider four communication scenarios and present several techniques to solve the location privacy problem in each of these scenarios. We will also show that these scenarios are related to each other. As mobile devices in a WPAN are typically operated by a user and energy constrained, we focused on user-friendliness and energy consumption during the design of our solutions.

Indoor Positioning System (IPS) has played a major part in using navigation inside an enclosed or indoor location. Predominant Smartphone as localization subsystems currently relies on server-side localization processes, allowing the service provider to know the location of a user at all time. Here we propose an algorithm to avoid the other sources from accessing personal data from the user hence avoiding data theft. A key observation is that these incidents typically involve large congregations of individuals, which form durable and stable areas with high density. Since the process of discovering, gathering patterns over large-scale trajectory databases can be quite lengthy, we further develop a set of well thought out techniques to improve the performance. We have evaluated our framework using a real prototype developed in Android and Hardtop HBase as well as realistic Wi-Fi traces scaling-up to several GBs. We can offer fine-grained localization in approximately four orders of magnitude less energy and number of Messages than competitive approaches.

The 13th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, 2002

Location aware services are becoming attractive with the deployment of next generation wireless networks and broadband multimedia wireless networks especially in indoor and campus areas. To provide location aware services, obtaining the position of a user accurately is important. While it is possible to deploy additional infrastructure for this purpose, using existing communications infrastructure is preferred for cost reasons. Because of technical restrictions, location fingerprinting schemes are the most promising. In this paper we are presenting a systematic study of the performance/tradeoff and deployment issues. In this paper we present some experimental results towards such a systematic study and discuss some issues related to the indoor positioning problem.

IEEE Transactions on Knowledge and Data Engineering, 2015

Indoor Positioning Systems (IPS) have recently received considerable attention, mainly because GPS is unavailable in indoor spaces and consumes considerable energy. On the other hand, predominant Smartphone OS localization subsystems currently rely on server-side localization processes, allowing the service provider to know the location of a user at all times. In this paper, we propose an innovative algorithm for protecting users from location tracking by the localization service, without hindering the provisioning of fine-grained location updates on a continuous basis. Our proposed Temporal Vector Map (TVM) algorithm, allows a user to accurately localize by exploiting a k-Anonymity Bloom (kAB) filter and a bestNeighbors generator of camouflaged localization requests, both of which are shown to be resilient to a variety of privacy attacks. We have evaluated our framework using a real prototype developed in Android and Hadoop HBase as well as realistic Wi-Fi traces scaling-up to several GBs. Our analytical evaluation and experimental study reveal that TVM is not vulnerable to attacks that traditionally compromise k-anonymity protection and indicate that TVM can offer fine-grained localization in approximately four orders of magnitude less energy and number of messages than competitive approaches.

2007

There are several problems encountered when trying to determine the location of a mobile phone, including whether you are in an urban or rural environment. Also, it is well known that some positioning technologies work better than others depending on the environment they are in. For example, GPS works well in rural areas but not as well in urban areas, GSM positioning accuracy can be acceptable in urban areas with the right triangulation technology, but is less accurate in rural areas. Positioning with other technologies such as WiFi, Bluetooth, and Semacode all have their own advantages and disadvantages as well, depending on the overall environment in which they are used. One research task of the ICiNG project is to address these issues and introduce the next logical step for freely available mobile positioning, advancing the pioneering work done by Place Lab at Intel. The EU-FP6 ICiNG project component that initiates this advance is called the ILC (ICiNG Location Client). The ILC integrates all the above location finding technologies into one positioning module. This paper outlines the technique we developed to combine these technologies and the architecture used to deploy them on a mobile phone. With all these technologies finally available on one device, it is now possible to employ a personal positioning system that can work effectively in any environment. Another important advantage of the ILC is its ability to do this without any direct communication with outside sources, so users need not worry about "big brother" tracking their every movement. The ILC only "listens" for, and makes use of, radio signals that are freely available in the current environment, and does not actively connect to any external network or other services to triangulate its position.