Improved Information Retrieval Technique for Cryptographic Data Storage
Data Security, Encryption, Decryption, Blowfish, Cryptography, Secure Search, MD5
Cryptography is a technique to secure the data and their sensitivity and privacy from other users. That is a low cost and easy implementable technique for achieving these goals. Therefore different services and applications are consuming these techniques. In this presented work the cryptographic cloud technology is studied. The cryptographic cloud provides the security of data over the data during the data storage, retrieval and outsourcing. But that data is not searchable due to cryptographic data transformation. In this context the presented work provides the technique to secure the data using cryptographic and also make the data searchable using the keywords available in the data stored on cloud server. In order to develop such application first a hybrid cryptographic algorithm is implemented which usages the MD5 hash generation algorithm. That algorithm is used to generate the cryptographic key for encryption and the blowfish algorithm is implemented for computing the cryptographic data. On the other hand for making the data searchable first the text mining technique is used which extract the essential keywords form the data. Then for security purpose the keywords are stored in data base using the MD5 hash. During the search, data first indexed using the inverted index and then bloom filter is used for finding the most probable index. In further the data precisely searched using the KNN algorithm. That process improves the performance of search accuracy and resource consumption during the search. The observed results demonstrate the efficient and acceptable performance of implemented system.
"Improved Information Retrieval Technique for Cryptographic Data Storage ", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.3, Issue 10, page no.180 - 189, October-2018, Available :https://ijsdr.org/papers/IJSDR1810030.pdf
Volume 3
Issue 10,
October-2018
Pages : 180 - 189
Paper Reg. ID: IJSDR_180690
Published Paper Id: IJSDR1810030
Downloads: 000347037
Research Area: Engineering
Country: -, -, -
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
