User Location Privacy Protection Research Articles

Knowledge-Driven Location Privacy Preserving Scheme for Location-Based Social Networks

Location privacy-preserving methods for location-based services in mobile communication networks have received great attention. Traditional location privacy-preserving methods mostly focus on the researches of location data analysis in geographical space. However, there is a lack of studies on location privacy preservation by considering the personalized features of users. In this paper, we present a Knowledge-Driven Location Privacy Preserving (KD-LPP) scheme, in order to mine user preferences and provide customized location privacy protection for users. Firstly, the UBPG algorithm is proposed to mine the basic portrait. User familiarity and user curiosity are modelled to generate psychological portrait. Then, the location transfer matrix based on the user portrait is built to transfer the real location to an anonymous location. In order to achieve customized privacy protection, the amount of privacy is modelled to quantize the demand of privacy protection of target user. Finally, experimental evaluation on two real datasets illustrates that our KD-LPP scheme can not only protect user privacy, but also achieve better accuracy of privacy protection.

LBS user location privacy protection scheme based on trajectory similarity

During the data set input or output, or the data set itself adds noise to enable data distortion to effectively reduce the risk of user privacy leakage. However, in the conventional method, the added noise may cause data distortion, thereby appealed against it. However, the amount of noise is too small and cannot meet the effect of privacy protection. Therefore, we propose a LBS user location privacy protection scheme based on trajectory similarity (DPTS). With double privacy protection without reducing the efficiency of algorithms, it does not cause data distortion to provide more reliable privacy protection. The main contributions of this article include: (1) In the process of collecting and publishing the location data, introduce into the privacy protection method, (2) The differential privacy algorithm based on the trajectory prefix tree is superimposed on the basis of the false position replacement algorithm based on the trajectory similarity, (3) Propose LBS-based Difference Privacy Protection Algorithm. In the algorithm, We reach the purpose of protecting user personal privacy by replace the original trajectory into a fake track trace that is the lowest degree of similarity in the interval. Then establish a prefix tree and add noise to the positional frequency. It is in order to further protect the sensitive location information, double protection in the trajectory data set, and the degree of privacy protection is improved. Simulation experiment results show that the proposed algorithm is effective. The algorithm can suppress the distortion rate of data while improving the amount of noise, and in improving the algorithm operation efficiency, it reduces the risk of leakage of sensitive position information.

User location privacy protection mechanism for location-based services

With the rapid development of the Internet of Things (IoT), Location-Based Services (LBS) are becoming more and more popular. However, for the users being served, how to protect their location privacy has become a growing concern. This has led to great difficulty in establishing trust between the users and the service providers, hindering the development of LBS for more comprehensive functions. In this paper, we first establish a strong identity verification mechanism to ensure the authentication security of the system and then design a new location privacy protection mechanism based on the privacy proximity test problem. This mechanism not only guarantees the confidentiality of the user’s information during the subsequent information interaction and dynamic data transmission, but also meets the service provider’s requirements for related data.

An Improved Privacy-Aware Handoff Authentication Protocol for VANETs

Vehicles handover from one road-side unit to another is a common phenomenon in vehicular ad-hoc networks (VANETs). Authenticating vehicles effectively is the key to success of VANETs. Li and Liu et al. proposed a lightweight identity authentication protocol (LIAP) for VANTEs recently, which is based on the concept of dynamic session secret process instead of conventional cryptographic schemes. LIAP possesses many advantages of againsting major existing attacks and performing well at efficiency and low consumption. However, we have demonstrated that the protocol LIAP doesn’t provide user location privacy protection and the resistance of parallel session attack is weak. Therefore, to enhance security of the protocol LIAP, we concatenate the terminal’s pseudo-identity with a random number, then encrypt the connected information by using quadratic residues operation, the generated dynamic identity can against the user location tracking attack. Furthermore, in order to against the parallel session attack during the handover procedure, a new road side unit regenerated a new session secret sequence and computed a challenge sequence with the terminal user’s pseudo-identity through XOR encryption. Through security analysis and experiments, our scheme has higher efficiency and better performance to be applicable to VANETS compared with other existing schemes.

Privacy For Location Based System In Mobile P2P Environment

Advances in mobile communication,it creates a major privacy breach in current location-based services (LBS) where mobile users have to report their exact location information to an LBS provider in order to obtain their desired services. For example, a user who wants to issue a query asking about her nearest gas station has to report her exact location to an LBS provider. However, many recent research reports have indicated that revealing private location information to potentially untrusted LBS providers may lead to major privacy breaches. To preserve user location privacy, spatial cloaking is the most commonly used privacy-enhancing technique in LBS. The basic idea of the spatial cloaking technique is to blur a user's exact location into a cloaked area that satisfies the user specified privacy requirements. Unfortunately, existing spatial cloaking algorithms de-signed for LBS rely on fixed communication infrastructure, e.g., base stations, and centralized/distributed servers. Thus, these algorithms cannot be applied to a mobile peer-to-peer (P2P) environment where mobile users can only communicate with other peers through P2P multi-hop routing without any support of fixed communication infrastructure or servers. In this paper, we propose a spatial cloaking algorithm for mobile P2P environments. As mobile P2P environments have many unique limitations, e.g., user mobility, limited transmission range, multi-hop communication, scarce communication resources, and network partitions, we propose two key features to enhance our algorithm: (1) An information sharing scheme enables mobile users to share their gathered peer location information to reduce communication overhead; (2) A historical location scheme allows mobile users to utilize stale peer location information to overcome the network partition problem .thus our P2P spatial cloaking algorithm is scalable while guaranteeing the user's location privacy protection.