Categorical Heuristic for Attribute Based Encryption in the Cloud Server
Journal Title: INTERNATIONAL JOURNAL OF COMPUTER TRENDS & TECHNOLOGY - Year 2014, Vol 9, Issue 2
Abstract
Attribute-based encryption (ABE) is a public-key based one-to-many encryption that allows users to encrypt and decrypt data based on user attributes. A promising application of ABE is flexible access control of encrypted data stored in the cloud, using access polices and ascribed attributes associated with private keys and Ciphertexts. One of the main efficiency drawbacks of the existing ABE schemes is that decryption involves expensive pairing operations and the number of such operations grows with the complexity of the access policy. In ABE system, a user provides an untrusted server, say a cloud service provider, with a transformation key that allows the cloud to translate any ABE ciphertext satisfied by that user’s attributes or access policy into a simple ciphertext, and it only incurs a small computational overhead for the user to recover the plaintext from the transformed ciphertext. However, it does not guarantee the correctness of the transformation done by the cloud. In the existing system, a new requirement of ABE with outsourced decryption: verifiability. Informally, verifiability guarantees that a user can efficiently check if the transformation is done correctly. In the proposed Categorical Heuristics on Attribute-based Encryption (CHAE) is an adaptation of Attribute Based Encryption (ABE) for the purposes of providing guarantees towards the provenance of the signed data, and moreover towards the anonymity of the signer. Finally, show an implementation of our scheme and result of performance measurements, which indicates a significant reduction on computing resources imposed on users
Authors and Affiliations
R. Brindha , R. Rajagopal
Keywords
Related Articles
- EP ID EP162718
- DOI -
- Views 92
- Downloads 0
Reconstruction Models for Attractors in the Technical and Economic Processes
The article discusses building models based on the reconstructed attractors of the time series. Discusses the use of the properties of dynamical chaos, namely to identify the strange attractors structure models. Here is...
Journey from Data Mining to Web Mining to Big Data
This paper describes the journey of big data starting from data mining to web mining to big data. It discusses each of this method in brief and also provides their applications. It states the importance of mining big dat...
Efficient Data Gathering and Improving Network Lifetime in Wireless Sensor Networks
In large-scale wireless sensor networks the data-gathering mechanism to introducing mobility into the network. . We consider the location service in a WSN, where each sensor needs to maintain its location information by...
Early Proliferation Stage of Detecting Diabetic Retinopathy Using Bayesian Classifier Based Level Set Segmentation
This article presents Bayesian Classifier which controls the levels set segmentation and it detect the retinal clots at an early stage from the image captured from fundus camera. The classifier is a probabilistic and use...
An Estimation Method of Measuring Image Quality for Compressed Images of Human Face
Nowadays digital image compression and decompression techniques are very much important. So our aim is to calculate the quality of face and other regions of the compressed image with respect to the original image. Image...