Interestingness measure on privacy preserved data with horizontal partitioning

Association rule mining is a process of finding the frequent item sets based on the interestingness measure. The major challenge exists when performing the association of the data where privacy preservation is emphasized. The actual transaction data provides the evident to calculate the parameters for defining the association rules. In this paper, a solution is proposed to find one such parameter i.e. support count for item sets on the non transparent data, in other words the transaction data is not disclosed. The privacy preservation is ensured by transferring the x-anonymous records for every transaction record. All the anonymous set of actual transaction record perceives high generalized values. The clients process the anonymous set of every transaction record to arrive at high abstract values and these generalized values are used for support calculation. More the number of anonymous records, more the privacy of data is amplified. In experimental results it is shown that privacy is ensured with more number of formatted transactions

TIME OPTIMIZATION FOR AUTHENTIC AND ANONYMOUS GROUP SHARING IN CLOUD STORAGE

The Cloud computing is a rising technique which offers information sharing are more, and efficient effective economical approaches between group members. To create an authentic and anonymous information sharing, IDentity based Ring Signature (ID-) is one of the promising method between the groups. Ring signature RS conspire grants the chief or data owner to authenticate into the framework in an anonymous way. In conventional Public Key Infrastructure (PKI) information sharing plan contains certificate authentication process, which is a bottleneck due to its high cost for consumption of more time to signature. To maintain a strategic distance from this issue, we proposed Cost Optimized Identity-based Ring Signature with forward secrecy COIRS () scheme. This plan evacuates the traditional certificate verification process. Just once the client should be confirmed by the chief giving his public details. The time required for this procedure is relatively not as much as customary public key framework. If the secret key holder has been compromised, all early generated signatures remain valid (Forward Secrecy). This paper examines how to optimize the time when sharing the documents to the cloud. We provide a protection from collision attack, which means revoked users will not get the original documents. In general better efficiency and secrecy can be provided for group sharing by applying approaches

Sentiment analysis and opinion mining from social media: A review

Ubiquitous presence of internet, advent of web 2.0 has made social media tools like blogs, Facebook, Twitter very popular and effective. People interact with each other, share their ideas, opinions, interests and personal information. These user comments are used for finding the sentiments and also add financial, commercial and social values. However, due to the enormous amount of user generated data, it is an expensive process to analyze the data manually. Increase in activity of opinion mining and sentiment analysis, challenges are getting added every day. There is a need for automated analysis techniques to extract sentiments and opinions conveyed in the user-comments. Sentiment analysis, also known as opinion mining is the computational study of sentiments and opinions conveyed in natural language for the purpose of decision making. Preprocessing data play a vital role in getting accurate sentiment analysis results. Extracting opinion target words provide fine-grained analysis on the customer reviews. The labeled data required for training a classifier is expensive and hence to over come, Domain Adaptation technique is used. In this technique, Single classifier is designed to classify homogeneous and heterogeneous input from di_erent domain. Sentiment Dictionary used to find the opinion about a word need to be consistent and a number of techniques are used to check the consistency of the dictionaries. This paper focuses on the survey of the existing methods of Sentiment analysis and Opinion mining techniques from social media

Multi-hop optimal position based opportunistic routing for wireless sensor networks

Wireless sensor network is a collection of a group of sensors connected to monitor an area of interest. Installation flexibility, mobility, reduced cost and scalability have given popularity to wireless sensor networks. Opportunistic routing is a routing protocol that takes the advantage of broadcasting nature of wireless sensor network for multi-hop communication. Considering the importance of communication between source-destination pairs in a wireless sensor network a Multi-hop Optimal position based Opportunistic Routing (MOOR) protocol is proposed in this paper. The algorithm chooses the path with minimum distance and number of hops between source and destination for transmission of data in the network. It is illustrated by simulation experiments that the proposed protocol has a good effect on End-to-End delay and lifetime of the network. In addition, it is observed that the average End-to-End delay is lesser for different simulation times when compared with existing EEOR protocol