International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Science , Computer Science and Engineering

Volume5,March 2018,

Topic : Flexibility of the Natural Source of Attribute Based Encryption Based on the Network

Authors:C.Selvalakshmi || M.Karthikeyan

Abstract:Attribute based encryption (ABE) is a famous cryptographic generation to protect the security of users’ data. However, the decryption cost and cipher text size restriction the utility of ABE in exercise. For most present ABE schemes, the decryption price and cipher text size develop linearly with the complexity of access structure. This is unwanted to the gadgets with restrained computing functionality and garage area. Outsourced decryption is taken into consideration as a possible method to lessen the consumer's decryption overhead, which allows a person to outsource a big variety of decryption operations to the cloud provider issuer (CSP). However, outsourced decryption cannot guarantee the correctness of transformation finished by means of the cloud, so it's far vital to test the correctness of outsourced decryption to make certain safety for users’ facts. Current research mainly specializes in verifiability of outsourced decryption for the legal users. It nonetheless stays a hard difficulty that a way to guarantee the correctness of outsourced decryption for unauthorized users. In this paper, we recommend an ABE scheme with verifiable outsourced decryption (called full verifiability for outsourced decryption), that could simultaneously test the correctness for transformed cipher text for the authorized customers and unauthorized customers. The proposed ABE scheme with verifiable outsourced decryption is proved to be selective CPA at ease within the standard version.

Keywords: Attribute based encryption,outsourced decyrption,CPA-secure

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DOI: 01.1617/vol5/iss3/pid51823


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Dr. Allon Guez
Professor, Drexel University,
USA


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IMPACT FACTOR: 4.890

ISSN(Online):2394-2320

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Thomson Reuters ID : q-6288-2016.
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ACCEPTANCE RATIO: 28.69%
ARTICLES PUBLISHED:0521
PAPER RECEIVED:01730
Journal Code : IJERCSE
Electronic ISSN : 2394-2320
Impact Factor : 4.890
Frequency : monthly
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