A TRUST-BASED PRIVACY-PRESERVING FRIEND RECOMMENDATION SCHEME

A TRUST-BASED PRIVACY-PRESERVING FRIEND RECOMMENDATION SCHEME FOR ONLINE SOCIAL NETWORKS

Online social networks (OSNs), which attract thousands of million people to use everyday, greatly extend OSN users' social circles by friend recommendations. OSN users' existing social relationship can be characterized as 1-hop trust relationship, and further establish a multi-hop trust chain during the recommendation process. As the same as what people usually experience in the daily life, the social relationship in cyberspaces are potentially formed by OSN users' shared attributes, e.g., colleagues, family members, or classmates, which indicates the attribute-based recommendation process would lead to more fine-grained social relationships between strangers. Unfortunately, privacy concerns raised in the recommendation process impede the expansion of OSN users' friend circle. Some OSN users refuse to disclose their identities and their friends' information to the public domain. In this paper, we propose a trust-based privacy-preserving friend recommendation scheme for OSNs, where OSN users apply their attributes to find matched friends, and establish social relationships with strangers via a multi-hop trust chain. Based on trace-driven experimental results and security analysis, we have shown the feasibility and privacy preservation of our proposed scheme.

INTRODUCTION

Online service provision generally happens between parties who have never executed with each other before, in a domain where the service customer regularly has lacking data about the service provider and about the goods furthermore, services offered. This strengths the consumer to acknowledge the "risk of prior performance", i.e. to pay for services and goods before accepting them, which can leave him in a defenseless position. The consumer generally has no chance to see and try products, i.e. to "squeeze the oranges", before he purchases. The service provider, then again, knows precisely what he gets, as long as he is paid in money. The inefficiencies resulting from this data asymmetry can be mitigated through trust and reputation. The idea is that even if the consumer can not try the product or service in advance, he can be confident that it will be what he expects as long as he trusts the seller.

A trusted seller therefore has a significant advantage in case the product quality cannot be verified in advance. Online social networks (OSNs) give people a simple approach to communicate with each other and make new friends in the internet. Similar to what people generally do in real life, OSN clients dependably attempt to grow their social circles in order to satisfy various social demands, e.g., business, leisure, and academia. In such cases, OSN clients may request the help from their existing friends to obtain useful feedback and valuable recommendations, furthermore, establish new connections with friends of friends (FoFs). As several works shows, the social relationship on the OSNs is an asymmetric context-aware trust relationship between two friends, by which they consider the possibility of establishing a multi-hop trust chain two outsiders by utilizing existing 1-hop trust of existing friends on the OSNs. However, the recommendation procedure represents a several crucial privacy breaches in the internet, for example, OSN clients' privacy concerns with respect to their identities and social relationships, as well as the recommended information during the information exchange, all of which should be well addressed. Else, it would be simple for malicious clients to perform serious cyber and physical attacks, for example, identity theft, inferring attack on social relationships, and profile leakage.

SYSTEM ARCHITECTURE

Online social networks (OSNs) provide people with an easy way to communicate with each other and make new friends in the cyberspace. Unfortunately, privacy concerns raised in the recommendation process impede the expansion of OSN user’s friend circle. Some OSN users refuse to disclose their identities and their friend’s information to the public domain. To overcome this problem, use a privacy-preserving trust-based friend recommendation scheme for online social networks, which enable two strangers establish trust relationships based on the existing 1-hop friendships. Proposed system includes: 1. We utilize OSN user’s social attributes and trust relationship to develop the friend recommendation scheme in a progressive way while preserving the privacy of OSN user’s identities and attributes.

CONCLUSION

From this survey we conclude that the privacy becomes major concern issue in friend recommendation system. Because in such system, for recommendation, users personal information is utilized, like users friend list, name, email id etc. This will utilized by unauthorized entities. Therefore the privacy preserving friend recommendation becomes essential feature in online social networking sites. This paper studies some recent methods for recommendation. We also make the comparative analysis of these systems on the basic of technique used, advantages and their disadvantages. These limitations become features challenges in this field.