Retrieving The Top K Ranked Secure Sensor Data In Cloud

762 words - 4 pages

- With the advent of cloud computing, publishers are motivated to store their complex data management systems from local sites to public cloud for greater flexibility and economic savings. But for protecting data privacy, and also to avoid information leakage, sensed data have to be encrypted before outsourcing onto the cloud servers. Considering the huge number of data users and documents in cloud, it is critical for the search service to allow multi-keyword query and provide ranked result to meet the effective data retrieval need. Most of the current works only consider the single keyword queries without proper ranking schemes. In this paper, we propose an efficient multi-keyword ranked search scheme that certifies users’ privacy over encrypted cloud data. Secure keyword search displays the top list of data with fewer results as output. Using fewer results as output we increase the document retrieval accuracy and reduce the communication overhead. Collaboration between WSN and the cloud environment can achieve this. We have proposed an integrated Publish/Subscribe (pub/sub)-based sensor-cloud service to collaborate with WSN. This collaboration will provide service, resource and storage with sensor driven data to the community. Additionally, we have proposed a Bipartie event matching algorithm to analyze subscriptions and publish relevant contents easily. We have evaluated our algorithm which shows better performance comparing with existing algorithms.

Index terms: Privacy-preserving keyword search, Multi-keyword, Cloud storage, pub/sub, event matching, Ranking.
LOUD computing is grasping more and more attention from both education and industry communities as it becomes a major deployment platform of distributed applications, especially for large-scale data management systems. End users can upload their personal data onto public clouds, and then they can access the data at anytime and anywhere. To protect data privacy and prevent unsolicited accesses in cloud and beyond, sensitive data, e.g., personal health records, emails, photo albums, financial transactions, tax documents etc., may have to be encrypted by data owners before uploading to commercial public cloud; this, however, outdates the traditional data exploitation service based on plaintext keyword search. The simple solution of downloading all the data and decrypting locally is clearly incompetent, due to the large amount of bandwidth cost in cloud scale system. Moreover, aside from excluding the local storage, storing data into the...

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