ABSTRACT:
Outsourcing data to a third-party
administrative control, as is done in cloud computing, gives rise to security
concerns. The data compromise may occur due to attacks by other users and nodes
within the cloud. Therefore, high security measures are required to protect
data within the cloud. However, the employed security strategy must also take
into account the optimization of the data retrieval time. In this paper, we
propose Division and Replication of Data in the Cloud for Optimal Performance
and Security (DROPS) that collectively approaches the security and performance
issues. In the DROPS methodology, we divide a file into fragments, and
replicate the fragmented data over the cloud nodes. Each of the nodes stores
only a single fragment of a particular data file that ensures that even in case
of a successful attack, no meaningful information is revealed to the attacker.
Moreover, the nodes storing the fragments, are separated with certain distance
by means of graph T-coloring to prohibit an attacker of guessing the locations
of the fragments. Furthermore, the DROPS methodology does not rely on the
traditional cryptographic techniques for the data security; thereby relieving
the system of computationally expensive methodologies. We show that the
probability to locate and compromise all of the nodes storing the fragments of
a single file is extremely low. We also compare the performance of the DROPS
methodology with ten other schemes. The higher level of security with slight
performance overhead was observed.
SYSTEM REQUIREMENTS:
HARDWARE REQUIREMENTS:
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System : Pentium Dual Core.
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Hard Disk : 120 GB.
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Monitor : 15’’ LED
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Input Devices : Keyboard, Mouse
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Ram : 1 GB
SOFTWARE REQUIREMENTS:
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Operating system : Windows 7.
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Coding Language : JAVA/J2EE
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Tool : Netbeans 7.2.1
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Database : MYSQL
REFERENCE:
Mazhar Ali, Student
Member, IEEE, Kashif Bilal, Student Member, IEEE, Samee U. Khan, Senior Member,
IEEE, Bharadwaj Veeravalli, Senior Member, IEEE, Keqin Li, Senior Member, IEEE,
and Albert Y. Zomaya, Fellow, IEEE, “DROPS: Division and Replication of Data in
Cloud for Optimal Performance and Security”, IEEE Transactions on Cloud
Computing, 2018