scholarly journals Enabling Location Privacy Preservation in MANETs Based on Distance, Angle, and Spatial Cloaking

Electronics ◽  
2020 ◽  
Vol 9 (3) ◽  
pp. 458
Author(s):  
Nanlan Jiang ◽  
Sai Yang ◽  
Pingping Xu

Preserving the location privacy of users in Mobile Ad hoc Networks (MANETs) is a significant challenge for location information. Most of the conventional Location Privacy Preservation (LPP) methods protect the privacy of the user while sacrificing the capability of retrieval on the server-side, that is, legitimate devices except the user itself cannot retrieve the location in most cases. On the other hand, applications such as geographic routing and location verification require the retrievability of locations on the access point, the base station, or a trusted server. Besides, with the development of networking technology such as caching technology, it is expected that more and more distributed location-based services will be deployed, which results in the risk of leaking location information in the wireless channel. Therefore, preserving location privacy in wireless channels without losing the retrievability of the real location is essential. In this paper, by focusing on the wireless channel, we propose a novel LPP enabled by distance (ranging result), angle, and the idea of spatial cloaking (DSC-LPP) to preserve location privacy in MANETs. DSC-LPP runs without the trusted third party nor the traditional cryptography tools in the line-of-sight environment, and it is suitable for MANETs such as the Internet of Things, even when the communication and computation capabilities of users are limited. Qualitative evaluation indicates that DSC-LPP can reduce the communication overhead when compared with k-anonymity, and the computation overhead of DSC-LPP is limited when compared with conventional cryptography. Meanwhile, the retrievability of DSC-LPP is higher than that of k-anonymity and differential privacy. Simulation results show that with the proper design of spatial divisions and parameters, other legitimate devices in a MANET can correctly retrieve the location of users with a high probability when adopting DSC-LPP.

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Jie Wang ◽  
Feng Wang ◽  
Hongtao Li

Location-based services (LBS) applications provide convenience for people’s life and work, but the collection of location information may expose users’ privacy. Since these collected data contain much private information about users, a privacy protection scheme for location information is an impending need. In this paper, a protection scheme DPL-Hc is proposed. Firstly, the users’ location on the map is mapped into one-dimensional space by using Hilbert curve mapping technology. Then, the Laplace noise is added to the location information of one-dimensional space for perturbation, which considers more than 70% of the nonlocation information of users; meanwhile, the disturbance effect is achieved by adding noise. Finally, the disturbed location is submitted to the service provider as the users’ real location to protect the users’ location privacy. Theoretical analysis and simulation results show that the proposed scheme can protect the users’ location privacy without the trusted third party effectively. It has advantages in data availability, the degree of privacy protection, and the generation time of anonymous data sets, basically achieving the balance between privacy protection and service quality.


2020 ◽  
Vol 2020 ◽  
pp. 1-16 ◽  
Author(s):  
Xueying Guo ◽  
Wenming Wang ◽  
Haiping Huang ◽  
Qi Li ◽  
Reza Malekian

With the rapid development of Internet services, mobile communications, and IoT applications, Location-Based Service (LBS) has become an indispensable part in our daily life in recent years. However, when users benefit from LBSs, the collection and analysis of users’ location data and trajectory information may jeopardize their privacy. To address this problem, a new privacy-preserving method based on historical proximity locations is proposed. The main idea of this approach is to substitute one existing historical adjacent location around the user for his/her current location and then submit the selected location to the LBS server. This method ensures that the user can obtain location-based services without submitting the real location information to the untrusted LBS server, which can improve the privacy-preserving level while reducing the calculation and communication overhead on the server side. Furthermore, our scheme can not only provide privacy preservation in snapshot queries but also protect trajectory privacy in continuous LBSs. Compared with other location privacy-preserving methods such as k-anonymity and dummy location, our scheme improves the quality of LBS and query efficiency while keeping a satisfactory privacy level.


2016 ◽  
Vol 2016 ◽  
pp. 1-16 ◽  
Author(s):  
Ming Chen ◽  
Wenzhong Li ◽  
Xu Chen ◽  
Zhuo Li ◽  
Sanglu Lu ◽  
...  

Recent years have witnessed the rapid growth of location-based services (LBSs) for mobile social network applications. To enable location-based services, mobile users are required to report their location information to the LBS servers and receive answers of location-based queries. Location privacy leak happens when such servers are compromised, which has been a primary concern for information security. To address this issue, we propose the Location Privacy Preservation Scheme (LPPS) based on distributed cache pushing. Unlike existing solutions, LPPS deploys distributed cache proxies to cover users mostly visited locations and proactively push cache content to mobile users, which can reduce the risk of leaking users’ location information. The proposed LPPS includes three major process. First, we propose an algorithm to find the optimal deployment of proxies to cover popular locations. Second, we present cache strategies for location-based queries based on the Markov chain model and propose update and replacement strategies for cache content maintenance. Third, we introduce a privacy protection scheme which is proved to achievek-anonymity guarantee for location-based services. Extensive experiments illustrate that the proposed LPPS achieves decent service coverage ratio and cache hit ratio with lower communication overhead compared to existing solutions.


2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Rui Zhu ◽  
Li Xu ◽  
Yali Zeng ◽  
Xun Yi

The database-driven cognitive radio networks (CRNs) are regarded as a promising approach to utilizing limited spectrum resources in large-scale Internet of Things (IoT). However, database-driven CRNs face some security and privacy threats. Firstly, secondary users (SUs) should send identity and location information to the database (DB) to obtain a list of available channels, such that the curious DB might easily misuse and threaten the privacy of SUs. Secondly, malicious SUs might send fake location information to the DB in order to occupy channels with better quantity in advance and so gain benefits. This might also cause serious interference to primary users (PUs). In this paper, we propose a lightweight privacy-preserving location verification protocol to protect the identity and location privacy of each SU and to verify the location of SUs. In the proposed protocol, the SU does not need to provide location information to request an available channel from the DB. Therefore, the DB cannot get the location information of any SU. In the proposed protocol, the base station (BS) selects some SUs as witnesses to generate location proofs for each other in a distributed fashion. This new witness selection mechanism makes the proposed protocol reliable when a malicious SU generates fake location information to cheat the BS and also prevents SU-Witness collusion attacks. The results also show that the proposed protocol can provide strong privacy preservation for SUs and can effectively verify the location of the SUs. The security analysis shows that the proposed protocol can resist various types of attacks. Moreover, compared with previous protocols, the proposed protocol is lightweight because it relies on symmetric cryptography and it is unaffected by the area covered by the DB.


2016 ◽  
Vol 2016 (4) ◽  
pp. 102-122 ◽  
Author(s):  
Kassem Fawaz ◽  
Kyu-Han Kim ◽  
Kang G. Shin

AbstractWith the advance of indoor localization technology, indoor location-based services (ILBS) are gaining popularity. They, however, accompany privacy concerns. ILBS providers track the users’ mobility to learn more about their behavior, and then provide them with improved and personalized services. Our survey of 200 individuals highlighted their concerns about this tracking for potential leakage of their personal/private traits, but also showed their willingness to accept reduced tracking for improved service. In this paper, we propose PR-LBS (Privacy vs. Reward for Location-Based Service), a system that addresses these seemingly conflicting requirements by balancing the users’ privacy concerns and the benefits of sharing location information in indoor location tracking environments. PR-LBS relies on a novel location-privacy criterion to quantify the privacy risks pertaining to sharing indoor location information. It also employs a repeated play model to ensure that the received service is proportionate to the privacy risk. We implement and evaluate PR-LBS extensively with various real-world user mobility traces. Results show that PR-LBS has low overhead, protects the users’ privacy, and makes a good tradeoff between the quality of service for the users and the utility of shared location data for service providers.


Author(s):  
Ajaysinh Devendrasinh Rathod ◽  
Saurabh Shah ◽  
Vivaksha J. Jariwala

In recent trends, growth of location based services have been increased due to the large usage of cell phones, personal digital assistant and other devices like location based navigation, emergency services, location based social networking, location based advertisement, etc. Users are provided with important information based on location to the service provider that results the compromise with their personal information like user’s identity, location privacy etc. To achieve location privacy of the user, cryptographic technique is one of the best technique which gives assurance. Location based services are classified as Trusted Third Party (TTP) & without Trusted Third Party that uses cryptographic approaches. TTP free is one of the prominent approach in which it uses peer-to-peer model. In this approach, important users mutually connect with each other to form a network to work without the use of any person/server. There are many existing approaches in literature for privacy preserving location based services, but their solutions are at high cost or not supporting scalability.  In this paper, our aim is to propose an approach along with algorithms that will help the location based services (LBS) users to provide location privacy with minimum cost and improve scalability.


2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Xuejun Zhang ◽  
Haiyan Huang ◽  
Shan Huang ◽  
Qian Chen ◽  
Tao Ju ◽  
...  

The proliferation of location-based services, representative services for the mobile networks, has posed a serious threat to users’ privacy. In the literature, several privacy mechanisms have been proposed to preserve location privacy. Location obfuscation enforced using cloaking region is a widely used technique to achieve location privacy. However, it requires a trusted third-party (TTP) and cannot sufficiently resist various inference attacks based on background information and thus is vulnerable to location privacy breach. In this paper, we propose a context-aware location privacy-preserving solution with differential perturbations, which can enhance the user’s location privacy without requiring a TTP. Our scheme utilizes the modified Hilbert curve to project every 2-d location of the user in the considered map to 1-d space and randomly generates the reasonable perturbation by adding Laplace noise via differential privacy. In order to solve the resource limitation of mobile devices, we use a quad-tree based scheme to transform and store the user context information as bit stream which achieves the high compression ratio and supports efficient retrieval. Security analysis shows that our proposed scheme can effectively preserve the location privacy. Experimental evaluation shows that our scheme retrieval accuracy is increased by an average of 15.4% compared with the scheme using standard Hilbert curve. Our scheme can provide strong privacy guarantees with a bounded accuracy loss while improving retrieval accuracy.


2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Lu Ou ◽  
Hui Yin ◽  
Zheng Qin ◽  
Sheng Xiao ◽  
Guangyi Yang ◽  
...  

Location-based services (LBSs) are increasingly popular in today’s society. People reveal their location information to LBS providers to obtain personalized services such as map directions, restaurant recommendations, and taxi reservations. Usually, LBS providers offer user privacy protection statement to assure users that their private location information would not be given away. However, many LBSs run on third-party cloud infrastructures. It is challenging to guarantee user location privacy against curious cloud operators while still permitting users to query their own location information data. In this paper, we propose an efficient privacy-preserving cloud-based LBS query scheme for the multiuser setting. We encrypt LBS data and LBS queries with a hybrid encryption mechanism, which can efficiently implement privacy-preserving search over encrypted LBS data and is very suitable for the multiuser setting with secure and effective user enrollment and user revocation. This paper contains security analysis and performance experiments to demonstrate the privacy-preserving properties and efficiency of our proposed scheme.


2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Changlun Zhang ◽  
Chao Li ◽  
Jian Zhang

With the rapid development and widespread use of wearable wireless sensors, data aggregation technique becomes one of the most important research areas. However, the sensitive data collected by sensor nodes may be leaked at the intermediate aggregator nodes. So, privacy preservation is becoming an increasingly important issue in security data aggregation. In this paper, we propose a security privacy-preserving data aggregation model, which adopts a mixed data aggregation structure. Data integrity is verified both at cluster head and at base station. Some nodes adopt slicing technology to avoid the leak of data at the cluster head in inner-cluster. Furthermore, a mechanism is given to locate the compromised nodes. The analysis shows that the model is robust to many attacks and has a lower communication overhead.


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