Enhanced RSSI-Based Real-Time User Location Tracking System for Indoor and Outdoor Environments

Yue, Yinliang; Wang, Fang; Feng, Dan

doi:10.1109/iccit.2007.253

Cited by 81 publications

(38 citation statements)

References 7 publications

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“…The benefit of RSSI method is that its implementation does not require any specialized hardware. It has been used by many user location tracking applications [25][26][27] with an estimation error as low as 4.1m [28]. As we need a parameter to be used as a seed and a simple and fast equation to guarantee the anonymity of VANET, therefore in this paper, we leverage the RSSI to propose a user centric anonymity model, which we call RAnonymity.…”

Section: Radio Signal Strength Indication (Rssi)mentioning

confidence: 99%

RSSI-Based User Centric Anonymization for Location Privacy in Vehicular Networks

Shan

2010

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Abstract. In Vehicular Networks, for enhancing driving safety as well as supporting other applications, vehicles periodically broadcast safety messages with their precise position information to neighbors. However, these broadcast messages make it easy to track specific vehicles and will likely lead to compromise of personal privacy. Unfortunately, current location privacy enhancement methodologies in VANET, including Pseudonymization, K-anonymity, Random silent period, Mix-zones and path confusion, all suffer some shortcomings. In this paper, we propose a RSSI (Received Signal Strength Indicator)-based user centric anonymization model, which can significantly enhance the location privacy and at the same time ensure traffic safety. Simulations are performed to show the advantages of the proposed method. In comparison with traditional random silent period method, our method can increase at least 47% of anonymity in both simple and correlation tracking.Keywords: VANET, Location Privacy, Tracking, Anonymity IntroductionNowadays, more and more vehicles are equipped with navigation systems that can provide drivers with the directions to the destination. To fulfill their safety functions, many safety-related applications require that the vehicles broadcast their current position, speed, and direction periodically. Because these safety messages are broadcasted wirelessly in plaintext for safety applications, they are vulnerable to eavesdropping, and the location information of the vehicles can then be extracted from either position related data or identification related data. Therefore, although the broadcast safety messages could in principle improve driving safety, unauthorized parties or attackers may exploit the vulnerabilities of these VANET application systems and compromise the location privacy of the interested vehicles [1].To solve the problem mentioned above, the authors in [2][3][4][5] proposed schemes to remove the correlation between locations and identifiers by periodically or randomly updating vehicles' pseudo identifiers. Although these methods could make vehicles unidentifiable within an anonymity set in motionless states, it can still be traced by movement tracking [6]. Furthermore, the locations visited by the vehicles can be associated with the places of interests [7] by firstly accumulating the driving paths, then by cross-referencing the accumulation results with geographical maps or other location based services. Existing methodologies to enhance location privacy can be

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Section: Radio Signal Strength Indication (Rssi)mentioning

confidence: 99%

RSSI-Based User Centric Anonymization for Location Privacy in Vehicular Networks

Shan

2010

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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“…User terminals constantly signal their location, which is used to determine their distance d from the WiFi AP. Knowing d it becomes possible to estimate RSSI [23]:…”

Section: Performance Evaluationmentioning

confidence: 99%

Network-assisted offloading for mobile cloud applications

Fiandrino

Kliazovich

Bouvry

et al. 2015

2015 IEEE International Conference on Communications (ICC)

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Abstract-Data traffic from mobile devices experiences unprecedented growth, which current cellular network capacities cannot sustain. Traffic offloading to other type of networks, such as WiFi, can be used to reduce load in cellular networks. In this paper, we propose a novel solution, which unlike other existing methodologies, implements tight cooperation with the cellular network to optimize traffic offloading. The cellular network provides information about channel usage statistics, user mobility patterns, available resources and other parameters. The offloading decisions aim at optimizing the balance between user application requirements and availability of network resources. The validation results, obtained from NS-3 simulations, confirm effectiveness of the proposed solution in balancing cellular traffic load while ensuring QoS.

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“…Contrariwise, when an indoor space or in an urban canyon is considered, the GNSS positioning in not possible and it is mandatory to overcome this issue considering different techniques and sensors. In recent years, some indoor location-based services (LBSs) have been developed integrating different technologies and measurements [22], such as cameras [27], infrared (Kinect), ultrasound [20], WLAN/Wi-Fi [6], RFID [23], mobile communication [10], and so forth are examples of the technologies that the scientific community has put at the service of indoor locations. Despite the ample panorama of solutions, mass market applications for indoor positioning require the use of embedded sensors in commercial smartphone without supplementary physical components.…”

Section: Indoor Scenariosmentioning

confidence: 99%

Positioning Techniques with Smartphone Technology: Performances and Methodologies in Outdoor and Indoor Scenarios

Dabove¹,

Pietra²,

Lingua³

2017

Smartphones From an Applied Research Perspective

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Smartphone technology is widespread both in the academy and in the commercial world. Almost every people have today a smartphone in their pocket, that are not only used to call other people but also to share their location on social networks or to plan activities. Today with a smartphone we can compute our position using the sensors settled inside the device that may also include accelerometers, gyroscopes and magnetometers, teslameter, proximity sensors, barometer, and GPS/GNSS chipset. In this chapter we want to analyze the state-of-the-art of the positioning with smartphone technology, considering both outdoor and indoor scenarios. Particular attention will be paid to this last situation, where the accuracy can be improved fusing information coming from more than one sensor. In particular, we will investigate an innovative method of image recognition based (IRB) technology, particularly useful in GNSS denied environment, taking into account the two main problems that arise when the IRB positioning methods are considered: the first one is the optimization of the battery, that implies the minimization of the frame rate, and secondly the latencies due to image processing for visual search solutions, required by the size of the database with the 3D environment images.

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Enhanced RSSI-Based Real-Time User Location Tracking System for Indoor and Outdoor Environments

Cited by 81 publications

References 7 publications

RSSI-Based User Centric Anonymization for Location Privacy in Vehicular Networks

RSSI-Based User Centric Anonymization for Location Privacy in Vehicular Networks

Network-assisted offloading for mobile cloud applications

Positioning Techniques with Smartphone Technology: Performances and Methodologies in Outdoor and Indoor Scenarios

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