A Verifiable Semantic Searching Scheme by Optimal Matching over Encrypted Data in Public Cloud
|A Verifiable Semantic Searching Scheme by Optimal Matching over Encrypted Data in Public Cloud
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IEEE BASE PAPER ABSTRACT:
Semantic searching over encrypted data is a crucial task for secure information retrieval in public cloud. It aims to provide retrieval service to arbitrary words so that queries and search results are flexible. In existing semantic searching schemes, the verifiable searching does not be supported since it is dependent on the forecasted results from predefined keywords to verify the search results from cloud, and the queries are expanded on plaintext and the exact matching is performed by the extended semantically words with predefined keywords, which limits their accuracy. In this paper, we propose a secure verifiable semantic searching scheme. For semantic optimal matching on ciphertext, we formulate word transportation (WT) problem to calculate the minimum word transportation cost (MWTC) as the similarity between queries and documents, and propose a secure transformation to transform WT problems into random linear programming (LP) problems to obtain the encrypted MWTC. For verifiability, we explore the duality theorem of LP to design a verification mechanism using the intermediate data produced in matching process to verify the correctness of search results. Security analysis demonstrates that our scheme can guarantee verifiability and confidentiality. Experimental results on two datasets show our scheme has higher accuracy than other schemes.
PROJECT OUTPUT VIDEO:
- Fu et al. proposed a verifiable semantic searching scheme that extends the query words to get the predefined keywords related to query words, then they used the extended keywords to search on a symbol-based trie index.
- Liu et al. introduce the Word2vec technique to utilize the semantic information of word embeddings, their approach damages the semantic information due to straightly aggregating all the word vectors. We think that secure semantic searching schemes should further utilize a wealth of semantic information among words and perform optimal matching on the ciphertext for high search accuracy.
DISADVANTAGES OF EXISTING SYSTEM:
- The traditional searchable encryption schemes require that query words must be the predefined keywords in the outsourced documents, which leads to an obvious limitation of these schemes that similarity measurement solely base on the exact matching between keywords in the queries and documents.
- Fu et al. scheme only verifies whether all the documents containing the extended keywords are returned to users or not, and needs users to rank all the documents for getting top-k related documents. Therefore, it is challenging to design a secure semantic searching scheme to support verifiable searching.
- The existing scheme is unable to support semantic searching and introduces multiple rounds of communication between data owners.
- In this paper, we propose a secure verifiable semantic searching scheme that treats matching between queries and documents as an optimal matching task. We treat the document words as “suppliers,” the query words as “consumers,” and the semantic information as “product,” and design the minimum word transportation cost (MWTC) as the similarity metric between queries and documents. Therefore, we introduce word embeddings to represent words and compute Euclidean distance as the similarity distance between words, then formulate the word transportation (WT) problems based on the word embeddings representation. However, the cloud server could learn sensitive information in the WT problems, such as the similarity between words.
- Treating the matching between queries and documents as an optimal matching task, we explore to propose a secure verifiable semantic searching scheme that performs semantic optimal matching on the ciphertext.
- For secure semantic optimal matching on the ciphertext, we formulate the word transportation (WT) problem and propose a secure transformation obtaining the encrypted minimum word transportation cost as measurements between queries and documents.
ADVANTAGES OF PROPOSED SYSTEM:
- The experiments results show that the accuracy of our proposed scheme is better than that of other schemes.
- The results demonstrate the effectiveness of our secure verifiable semantic searching scheme based on word transportation optimal matching.
- The accuracy of the proposed scheme using the description topics is still higher than that of other schemes. A reason is that the word transportation optimal matching is beneficial to analyze the semantic relationship between the words and the importance of the distinction among words in long-text queries.
- It is worth spending more time to get higher search accuracy for the applications in practical scenarios. Take the medical profile as an example, a correct personal medical profile of a patient is essential and useful to help the doctor make a precise disease diagnosis and health evaluation.
- System : Pentium i3 Processor
- Hard Disk : 500 GB.
- Monitor : 15’’ LED
- Input Devices : Keyboard, Mouse
- Ram : 2 GB
- Operating system : Windows 10.
- Coding Language : Java.
- Tool : Netbeans 8.2
- Database : MYSQL
Wenyuan Yang, Student Member, IEEE, and Yuesheng Zhu, Senior Member, IEEE, “A Verifiable Semantic Searching Scheme by Optimal Matching over Encrypted Data in Public Cloud”, IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, 2021.
PROJECT COST: Rs.3000/
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