
Modified Dynamic Hash Table with Threshold RSA for Dynamic and Public Auditing on Cloud Data
Author(s) -
T. Kishore Babu,
Guruprakash C D
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.k1448.0981119
Subject(s) - computer science , hash table , cloud computing , merkle tree , hash function , overhead (engineering) , dynamic data , computation , algorithm , computer security , hash chain , database , operating system
Cloud storage is one of the major application in the cloud, which can provide the on-demand outsourcing data service for both organizations as well as individuals. The Data Integrity (DI) check in the cloud is applied by the user to ensure the integrity of data. The Third Party Auditing (TPA) technique is later introduced to check the cloud DI. Many research has been carried out in the public auditing to minimize the computation cost of the integrity check. The most existing method involves in lack of security and low computation overhead. In this research, the Modified Dynamic Hash Table with threshold Rivest, Shamir, and Adelman Algorithm (RSA) algorithm (MDHT-RSA) is proposed to improve the security and reduce the computation cost. The threshold RSA cryptography system increase the security by generating the secret key to the user and reduce the computation cost. The Modified Dynamic Hash Table (MDHT) is used to record the data information for dynamic auditing, which is located in the TPA. The MDHT is differed from the Dynamic hash table, that the MDHT doesn’t contain the tag block whereas the dynamic hash table has the tag block. The MDHT-RSA is analyzed with the computation cost and compared with existing method. The experimental result proved that the MDHT-RSA method has low computation cost than state-of-art method in public auditing. The verification cost of the MDHT-RSA is 1.3 s while a state-of-art method DHT-PA has the 1.35 s for the 200 blocks of data.