A Trust-based Privacy-Preserving Friend Recommendation Scheme for Online Social Networks

ABSTRACT

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.

AIM

The aim of this paper is OSN users apply their attributes to find matched friends, and establish social relationships with strangers via a multi-hop trust chain

SCOPE:

The Scope of this Paper is to trace-driven experimental results and security analysis, we have shown the feasibility and privacy preservation of our Trust Based Privacy Preserving Friend Recommendation Scheme.

EXISTING SYSTEM

On the one hand, directly asking recommendations to strangers or a non close friend not only reveals Alice’s identity, but also reveals her health condition and medical information. Even worse, traditional recommendation approaches applying identity to recommend strangers will disclose OSN users’ social relationships to the public, which impede patients from utilizing it, and also decrease the possibility of establishing the multi-hop trust chain if one of OSN users on the chain returns a negative result. On the other hand, current approaches cannot achieve the fine-grained and context-aware results automatically, due to the fact that OSN users have to determine the recommended friends based on their own judgments on the recommendation query. As in our example, Alice would like to ask for help from her friends who work in a hospital, but not a truck driver. To overcome the above issue, we consider the possibility of singsong users’ social attributes to establish the multi-hop trust chain based on each context-aware 1-hop trust relationship, where most of trust relationships are formed and strengthened by the shared social attributes.

DISADVANTAGES

1. Privacy  concerns raised in the recommendation process impede the expansion of OSN users’ friend circle
2. Some OSN users refuse to disclose their identities and their friend’s information to the public domain.

PROPOSED SYSTEM

In this paper, design a light-weighted privacy-preserving friend recommendation scheme for OSNs by utilizing both users’ social attributes and their existing trust relationships to establish a multi-hop trust chain between strangers. In our scheme, we jointly consider privacy leakages and preservation approaches regarding the identity, social attributes, and their trust relationships of OSN users during the recommendation process. By trace-driven experimental results, we demonstrate both the security and efficiency of our proposed scheme

ADVANTAGES

1. Based on the 1-hop trust relationships, we extend existing friendships to multi-hop trust chains without compromising recommenders identity privacy
2. Extensive trace-driven experiment are deployed to verify the performance of our scheme in terms of security, efficiency, and feasibility.
   

SYSTEM ARCHITECTURE

SYSTEM CONFIGURATION:-

HARDWARE REQUIREMENTS:-

ü Processor          -   Pentium –III

ü Speed                -    1.1 Ghz

ü RAM                 -    256 MB(min)

ü Hard Disk         -   20 GB

ü Floppy Drive    -    1.44 MB

ü Key Board                 -    Standard Windows Keyboard

ü Mouse               -    Two or Three Button Mouse

ü Monitor             -    SVGA

SOFTWARE REQUIREMENTS:-

v  Operating System      : Windows 7    

v  Front End                  :ASP.net and C#

v  Database                    : MSSQL

v  Tool                           : Microsoft Visual studio

REFERENCE

Zhang, C Fang, Y.Guo, L.“ A Trust-based Privacy-Preserving Friend Recommendation Scheme for Online Social Networks,” IEEE Transactions on Dependable and Secure Computing, Volume 12 ,  Issue 4  , SEPTEMBER 2014.

SECURE DISTRIBUTED DEDUPLICATION SYSTEMS WITH IMPROVED RELIABILITY

ABSTRACT:

Data deduplication is a technique for eliminating duplicate copies of data, and has been widely used in cloud storage to reduce storage space and upload bandwidth. However, there is only one copy for each file stored in cloud even if such a file is owned by a huge number of users. As a result, deduplication system improves storage utilization while reducing reliability. Furthermore, the challenge of privacy for sensitive data also arises when they are outsourced by users to cloud. Aiming to address the above security challenges, this paper makes the first attempt to formalize the notion of distributed reliable deduplication system. We propose new distributed deduplication systems with higher reliability in which the data chunks are distributed across multiple cloud servers. The security requirements of data confidentiality and tag consistency are also achieved by introducing a deterministic secret sharing scheme in distributed storage systems, instead of using convergent encryption as in previous deduplication systems. Security analysis demonstrates that our deduplication systems are secure in terms of the definitions specified in the proposed security model. As a proof of concept, we implement the proposed systems and demonstrate that the incurred overhead is very limited in realistic environments

AIM

The main goal is to enable deduplication and distributed storage of the data across multiple storage servers.

SCOPE

Data deduplication techniques are widely employed to backup data and minimize network and storage overhead by detecting and eliminating redundancy among data

SYNOPSIS

A number of deduplication systems have been proposed based on various deduplication strategies such as client-side or server-side deduplication, file-level or block-level deduplication. Especially, with the advent of cloud storage, data deduplication techniques become more attractive and critical for the management of ever-increasing volumes of data in cloud storage services which motivates enterprises and organizations to outsource data storage to third-party cloud providers, as evidenced by many real-life case studies. According to the analysis report of IDC, the volume of data in the world is expected to reach 40 trillion gigabytes in 2020 [ Today’s commercial cloud storage services, such as Drop box, Google Drive and Mozy, have been applying deduplication to save the network bandwidth and the storage cost with client-side deduplication.

EXISTING SYSTEM

The challenge for data privacy also arises as more and more sensitive data are being outsourced by users to cloud. Encryption mechanisms have usually been utilized to protect the confidentiality before outsourcing data into cloud. Most commercial storage service provider are reluctant to apply encryption over the data because it makes deduplication impossible. The reason is that the traditional encryption mechanisms, including public key encryption and symmetric key encryption, require different users to encrypt their data with their own keys. As a result, identical data copies of different users will lead to different cipher texts.

DISADVANTAGES:

1. To work on secure deduplication can properly address the reliability and tag consistency problem in distributed storage systems
2. To protect both confidentiality and reliability while achieving deduplication in a cloud storage system is still a challenge.

PROPOSED SYSTEM

Four new secure deduplication systems are proposed to provide efficient deduplication with high reliability for file-level and block-level deduplication, respectively. The secret splitting technique, instead of traditional encryption methods, is utilized to protect data confidentiality. Specifically, data are split into fragments by using secure secret sharing schemes and stored at different servers. Our proposed constructions support both file-level and block-level deduplication Security analysis demonstrates that the proposed deduplication systems are secure in terms of the definitions specified in the proposed security model. In more details, confidentiality, reliability and integrity can be achieved in our proposed system. Two kinds of collusion attacks are considered in our solutions. These are the collusion attack on the data and the collusion attack against servers. In particular, the data remains secure even if the adversary controls a limited number of storage servers.  We implement our deduplication systems using the Ramp secret sharing scheme that enables high reliability and confidentiality levels. Our evaluation results demonstrate that the new proposed constructions are efficient and the redundancies are optimized and comparable with the other storage system supporting the same level of reliability

ADVANTAGES

1. To protect data confidentiality, the secret sharing technique is utilized, which is also compatible with the distributed storage systems
2.  To improve the reliability of data while achieving the confidentiality of the users’ outsourced data without an encryption mechanism.

SYSTEM CONFIGURATION

HARDWARE REQUIREMENTS:-

·                Processor          -   Pentium –III

·                Speed                -    1.1 Ghz

·                RAM                 -    256 MB(min)

·                Hard Disk         -   20 GB

·                Floppy Drive    -    1.44 MB

·                Key Board                 -    Standard Windows Keyboard

·                Mouse               -    Two or Three Button Mouse

·                Monitor             -    SVGA

SOFTWARE REQUIREMENTS:-

·                Operating System      : Windows  7                                     

·                Front End                  : ASP.NET and C#

·                Database                   : MSSQL

·                Tool                           :Visual Studio

REFERENCE:

Chen, X. ; Huang, X. ; Tang, S. “SECURE DISTRIBUTED DEDUPLICATION SYSTEMS WITH IMPROVED RELIABILITY” IEEE Transactions on Computers, VOL PP, ISS 99,FEBRUARY  2015.

Selcsp: A Framework To Facilitate Selection Of Cloud Service Providers

Abstract

With rapid technological advancements, cloud marketplace witnessed frequent emergence of new service providers with similar offerings. However, service level agreements (SLAs), which document guaranteed quality of service levels, have not been found to be consistent among providers, even though they offer services with similar functionality. In service outsourcing environments, like cloud, the quality of service levels are of prime importance to customers, as they use third-party cloud services to store and process their clients’ data. If loss of data occurs due to an outage, the customer’s business gets affected. Therefore, the major challenge for a customer is to select an appropriate service provider to ensure guaranteed service quality. To support customers in reliably identifying ideal service provider, this work proposes a framework, SelCSP, which combines trustworthiness and competence to estimate risk of interaction. Trustworthiness is computed from personal experiences gained through direct interactions or from feedbacks related to reputations of vendors. Competence is assessed based on transparency in provider’s SLA guarantees. A case study has been presented to demonstrate the application of our approach. Experimental results validate the practicability of the proposed estimating mechanisms

Aim

The aim of this paper proposes a framework, SelCSP, which combines trustworthiness and competence to estimate risk of interaction.

Scope:

The scope of this paper tends to validate the practicability of the proposed estimating the risk of interaction.

Existing System

In most cases, it has been observed that the failover time is quite long and customers’ businesses were hugely affected owing to lack of recovery strategy on vendor side. Moreover, in some instances, customers were not even intimated about the outage by providers. Cloud providers may use the high-quality first replication (HQFR) strategy proposed in to model their recovery mechanism. In this work, authors propose algorithms to minimize replication cost and the number of QoS-violated data replicas. Hence, it is desirable from customer’s point of- view to avoid such loss, rather than getting guarantees of service credits following a cloud outage. Avoidance of data loss requires reliable identification of competent service provider. As customer does not have control over its data deployed in cloud, there is a need to estimate risk prior to outsourcing any business onto a cloud. This motivated us to propose a risk estimation scheme which makes a quantitative assessment of risk involved while interacting with a given service provider.

 Disadvantages

 Lack of assurances and violations for SLA guarantees

 Multi-tenancy, lack of customer’s control over their data and application

Non-transparency with respect to security profiles of remote datacenter locations

Proposed System

In this paper estimation of risk of interaction in cloud environment has not been addressed. Hence, in this respect, the current work is significant as it proposes a framework, SelCSP , which attempts to compute risk involved in interacting with a given cloud service provider. The framework estimates perceived level of interaction risk by combining trustworthiness and competence of cloud provider. Trustworthiness is computed from ratings obtained through either direct interaction or feedback.

Advantages

1. The framework estimates trustworthiness in terms of context-specific, dynamic trust and reputation feedbacks.
2. Both these entities are combined to model interaction risk, which gives an estimate of risk level involved in an interaction

 System Architecture

SYSTEM CONFIGURATION

HARDWARE REQUIREMENTS:-

·                Processor          -   Pentium –III

·                Speed                -    1.1 Ghz

·                RAM                 -    256 MB(min)

·                Hard Disk         -   20 GB

·                Floppy Drive    -    1.44 MB

·                Key Board                 -    Standard Windows Keyboard

·                Mouse               -    Two or Three Button Mouse

·                Monitor             -    SVGA

SOFTWARE REQUIREMENTS:-

·                Operating System      : Windows  7                                     

·                Front End                  : ASP.NET and C#

·                Database                   : MSSQL

·                Tool                           :Visual Studio

References

Ghosh, N.,Ghosh, S.K.,  Das, S.K. “SelCSP: A Framework to Facilitate Selection of Cloud Service Providers” IEEE Transactions on Cloud Computing, Volume 3 ,  Issue 1 JULY 2014.