Data Integrity and Data Dynamics with Secure Storage Service in Cloud

被引:0
|
作者
Nithiavathy, R. [1 ]
机构
[1] Coimbatore Inst Engn & Technol, Dept Comp Sci & Engn, Coimbatore, Tamil Nadu, India
来源
2013 INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, INFORMATICS AND MEDICAL ENGINEERING (PRIME) | 2013年
关键词
Error localization; data dynamics; Cloud Computing; Data Integrity; storage; Audit;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The current utilization of the spectrum is quite inefficient; consequently, if properly used, there is no shortage of the spectrum that is presently available. Therefore, it is anticipated that more flexible use of spectrum and spectrum sharing between radio systems will be key enablers to facilitate the successful implementation of future systems. Cognitive radio, however, is known as the most intelligent and promising technique in solving the problem of spectrum sharing. In this paper, we consider the technique of spectrum sharing among users of service providers to share the licensed spectrum of licensed service providers. It is shown that the proposed technique rCloud computing is upcoming technology which has gained a lot of hype in the current world of I. T. Cloud computing is said to be the next big thing in the computer world after the internet. Though the benefits are huge, such a service is also relinquishing users' physical possession of their outsourced data, which inevitably poses new security risks towards the correctness of the data in cloud. In order to address this new problem and further achieve a secure and dependable cloud storage service. We propose in this paper a flexible distributed storage integrity auditing mechanism, utilizing the homomorphic token and distributed erasure-coded data for dynamically storing data. The proposed design allows users or third party auditor to audit the cloud storage with very lightweight communication and less computation cost. The auditing result ensures reliable cloud storage correctness, and simultaneously achieves fast data error localization, i.e., finding which server is misbehaving in the fast rapidly changing its data in the cloud and the user's application stored in cloud, it also supports efficient dynamic operations on outsourced data which is secured, including, deletion, and append, block modification and resilient against Byzantine failure, malicious data modification attack, and even server colluding attacks.
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页数:6
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