Data Integrity Auditing for Secure Cloud Storage using User Behavior Prediction

2021 ◽  
pp. 102245
Author(s):  
Junfeng Tian ◽  
Haoning Wang ◽  
Meng Wang
2014 ◽  
Vol 14 (4) ◽  
pp. 307-318 ◽  
Author(s):  
Yong Yu ◽  
Man Ho Au ◽  
Yi Mu ◽  
Shaohua Tang ◽  
Jian Ren ◽  
...  

Author(s):  
Wenting Shen ◽  
Jing Qin ◽  
Jia Yu ◽  
Rong Hao ◽  
Jiankun Hu ◽  
...  

Author(s):  
Neha Thakur ◽  
Aman Kumar Sharma

Cloud computing has been envisioned as the definite and concerning solution to the rising storage costs of IT Enterprises. There are many cloud computing initiatives from IT giants such as Google, Amazon, Microsoft, IBM. Integrity monitoring is essential in cloud storage for the same reasons that data integrity is critical for any data centre. Data integrity is defined as the accuracy and consistency of stored data, in absence of any alteration to the data between two updates of a file or record.  In order to ensure the integrity and availability of data in Cloud and enforce the quality of cloud storage service, efficient methods that enable on-demand data correctness verification on behalf of cloud users have to be designed. To overcome data integrity problem, many techniques are proposed under different systems and security models. This paper will focus on some of the integrity proving techniques in detail along with their advantages and disadvantages.


2021 ◽  
Author(s):  
Xiangyu Zhang ◽  
Jun Fang ◽  
Jingfan Zou ◽  
Wenfang Li ◽  
Weigang Xu ◽  
...  

Author(s):  
M A Manazir Ahsan ◽  
Ihsan Ali ◽  
Muhammad Imran ◽  
Mohd. Yamani Idna Idris ◽  
Suleman Khan ◽  
...  

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