Location Information Sharing on Mobile Online Social Networks Using Facial Recognition Method
Abstract
Online social networks allows the users to share their data with their friends. With the advent of mobile computing, traditional social networks have gradually adapted to a fresh paradigms called mobile online social networks. The Mobile online social networks (mOSNs) had become more popular, and compared with traditional OSNs, mOSNs provide the location-based services, which raise significant privacy concerns. Location sharing is a fundamental component of mOSN, but users may be hesitant to share their location and extract sensitive information due to the privacy concern. The mOSNs collect a large amount of location information over time, and the users’ location privacy is compromised if their location information is used by other third party adversaries controlling the mOSNs. While the location-based features make mOSNs popular, they also raise significant privacy concerns. The threat is even more serious when it comes to mOSNs, because user’s locations are being correlated with their profiles. Here, the system achieves social network privacy and location privacy. The system cannot be linked to the same user. The identity of each user in the query set will be replaced with a pseudo identity before sending the query to the location servers. It improves the privacy of users in mobile online social networks. The proposed system provides a face recognition for the privacy-preserving of the users. The given image will be encrypted to a key format and this key will uniquely identify the user. The system uses private photos in a privacypreserving manner for each user.
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Introduction
The evolution of mobile computing had made a significant influence on individuals, organizations and society. Mobile computing helped to adapt the traditional web based online social networks to the mobile platform. This made the growth of mobile online social networks (mOSNs) paradigm. While comparing with the web based social networks, mOSNs provides better connectivity with users from wherever they are. As the shifting of technology from the traditional web based social network to the mobile online social network had increased, it is important to analyse the impact of mOSNs from a privacy standpoint.
Location based services are the fundamental component of the mobile online social networks (mOSNs). By taking in account of the mobile devices geographical location different types of services can be provided to the user. Location sharing for the location based services has increased various privacy issues. Online social networks increasingly allow mobile users to share their location with their friends. The third parties can learn user‟s location from localization and location visualization services.
While the location based features make mOSNs more popular, they also raise significant privacy concerns. The threat is more serious when it comes to mOSNs, where the user‟s physical locations are correlated with their profiles. As indicated in the previous work [2], shows how to flexibly share presence by preserving user privacy with both friends and strangers. Another research [3], shows how untrusted third-party servers are treated simply as encrypted data stores. This approach significantly improves user‟s location privacy. Mobishare [5] and Mobishare+ [6] are two another approaches providing privacy in location sharing in mOSNs. Mobishare, which uses the bloom filter to prevent adversary attack. Mobishare+ employs dummy queries besides dummy location and identities. N-Mobishare [7], is simple and more consistent with the characteristics of social networks. Compared with Mobishare, N-Mobishare is more practical and efficient.
Conclusion
In this work, we have addressed the problem of privacy in online social network. Online social network security and the location server security are the main security concerns in the location based services. Without enough privacy users may be hesitant to share location information to mOSNs. Therefore by considering the privacy of users here proposes a face recognition method. In this a digital image signature is used as a key to uniquely identify each user in the location sharing system. While registering to the online server and updating the location in the location server, each user have a sign which will be generated using the image which has been given by the user. In this way privacy of each user will be achieved in this new architecture.