APPLAUS: A Privacy-Preserving Location Proof Updating System for location-based services

Zhu, Zhichao; Cao, Guohong

doi:10.1109/infcom.2011.5934991

Cited by 112 publications

(69 citation statements)

References 24 publications

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“…Privacy issues in mobile social networks have been well studied in the literature (e.g., privacy in LBSs [13], [14], privacy in mobile sensing [15], [16], etc.). In this section, we review some existing research on user's privacy issues for LBSs.…”

Section: Related Workmentioning

confidence: 99%

Achieving k-anonymity in privacy-aware location-based services

Niu

Zhu

et al. 2014

IEEE INFOCOM 2014 - IEEE Conference on Computer Communications

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374

357

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Abstract-Location-Based Service (LBS) has become a vital part of our daily life. While enjoying the convenience provided by LBS, users may lose privacy since the untrusted LBS server has all the information about users in LBS and it may track them in various ways or release their personal data to third parties. To address the privacy issue, we propose a DummyLocation Selection (DLS) algorithm to achieve k-anonymity for users in LBS. Different from existing approaches, the DLS algorithm carefully selects dummy locations considering that side information may be exploited by adversaries. We first choose these dummy locations based on the entropy metric, and then propose an enhanced-DLS algorithm, to make sure that the selected dummy locations are spread as far as possible. Evaluation results show that the proposed DLS algorithm can significantly improve the privacy level in terms of entropy. The enhanced-DLS algorithm can enlarge the cloaking region while keeping similar privacy level as the DLS algorithm.

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Section: Related Workmentioning

confidence: 99%

Achieving k-anonymity in privacy-aware location-based services

Niu

Zhu

et al. 2014

IEEE INFOCOM 2014 - IEEE Conference on Computer Communications

Self Cite

374

357

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“…Security and privacy in mobile sensing systems have been addressed by many works (e.g., [13][14][15][16]), but they do not consider aggregation of data. There are many existing works (e.g., [17]) on privacy-preserving data aggregation, but most of them assume a trusted aggregator.…”

Section: Related Workmentioning

confidence: 99%

Efficient Privacy-Preserving Stream Aggregation in Mobile Sensing with Low Aggregation Error

Cao

2013

Privacy Enhancing Technologies

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Abstract. Aggregate statistics computed from time-series data contributed by individual mobile nodes can be very useful for many mobile sensing applications. Since the data from individual node may be privacy-sensitive, the aggregator should only learn the desired statistics without compromising the privacy of each node. To provide strong privacy guarantee, existing approaches add noise to each node's data and allow the aggregator to get a noisy sum aggregate. However, these approaches either have high computation cost, high communication overhead when nodes join and leave, or accumulate a large noise in the sum aggregate which means high aggregation error. In this paper, we propose a scheme for privacy-preserving aggregation of time-series data in presence of untrusted aggregator, which provides differential privacy for the sum aggregate. It leverages a novel ring-based interleaved grouping technique to efficiently deal with dynamic joins and leaves and achieve low aggregation error. Specifically, when a node joins or leaves, only a small number of nodes need to update their cryptographic keys. Also, the nodes only collectively add a small noise to the sum to ensure differential privacy, which is O(1) with respect to the number of nodes. Based on symmetric-key cryptography, our scheme is very efficient in computation.

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“…Zhu and Guohong Cao, [3] in this paper, a privacy-preserving location proof updating system, called APPLAUS was proposed, which explains co-located Bluetooth enabled mobile devices mutually create location proofs, and transfer to the location proof server. To protect source location privacy from one another, and from the distrusted location proof server, they use statistically changed pseudonyms for each device.…”

Section: Related Workmentioning

confidence: 99%

Proximity Based Security Technique for Mobile User in Wireless Networks Using Multilevel Session Aggregation

Salame¹

2015

IJIRCCE

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Establishment of secure communication between wireless devices/nodes that do not share a prior trust relationship is an important problem. Today's location-sensitive service relies on users mobile device for determining its location and send it to the application. Data aggregation is a key challenging task in wireless senor network to minimize energy consumption and guarantees the data security and reliability. Multi-level data aggregation technique assures security and reliability of data aggregation in the presence of secure routing. We propose a privacy-preserving proximity-based multilevel reliable data aggregation security system for location-based services in wireless networks, without requiring any public key infrastructure, trusted authority or early required secret. In this system, the proximity based authentication and multi level session key establishment are implemented based on temporal location tags. Combining the unique physical features of the signals which may be sent from more than one ambient radio sources, the location tags cannot be easily faked by attackers. More specifically, Distributed data server (DDS) which is the uppermost level builds a public location tag according to some parameters of ambient packet i.e. sequence numbers, received signal strength indicators, and media access control (MAC) addresses. DDS also keeps a secret location tag contain the packet arrival time information which will helpful in generating multilevel session key. As DDS never expose their secret location tags, this system is vigorous against spoofers and eavesdroppers outside the proximity range. Moreover, by exploiting the packet arrival time of the ambient signals the multi level session key establishment strategy will significantly increases the key generation rate.

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APPLAUS: A Privacy-Preserving Location Proof Updating System for location-based services

Cited by 112 publications

References 24 publications

Achieving k-anonymity in privacy-aware location-based services

Achieving k-anonymity in privacy-aware location-based services

Efficient Privacy-Preserving Stream Aggregation in Mobile Sensing with Low Aggregation Error

Proximity Based Security Technique for Mobile User in Wireless Networks Using Multilevel Session Aggregation

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