An Efficient Parallel Implementation of a Light-weight Data Privacy Method for Mobile Cloud Users

2016 ◽  
Author(s):  
Mehdi Bahrami ◽  
Dong Li ◽  
Mukesh Singhal ◽  
Ashish Kundu
Keyword(s):  
Data Privacy ◽  
Parallel Implementation ◽  
Mobile Cloud ◽  
Light Weight ◽  
Cloud Users ◽  
Weight Data

scholarly journals PLIE- A Light-weight Image Encryption for data Privacy in mobile cloud storage

2018 ◽  
Vol 7 (4.36) ◽  
pp. 368
Author(s):  
M. Sankari ◽  
P. Ranjana
Keyword(s):  
Image Encryption ◽  
Cloud Storage ◽  
Data Privacy ◽  
Image Data ◽  
Mobile Cloud ◽  
Light Weight ◽  
Security Attacks ◽  
Text Data ◽  
Python Language ◽  
Speed Up

Data privacy is the greatest challenge of mobile cloud computing to secure the image data. Traditional encryption techniques are mainly suitable for text data than image data. In this paper, we introduce a method called Privacy-preserving light weight Image Encryption (PLIE) to protect the image data in mobile cloud, maintains the user’s privacy by keeping metadata in mobile. It improves the throughput, speed-up the encryption time in mobile and minimize the complexity. Basically,three processes handled on image data such as split, distribute and scramble (SDS) in mobile for maintaining the user’s privacy and store it in cloud. For our analysis of gathering images, the encryption time of the PLIE method implemented in python language resulted as approximately 50% reduced than AES. We measured the performance analysis of existing method(AES) with the proposed method(PLIE) by various parameters. In addition,we present some security attacks to evaluate the level of security.  

scholarly journals Secure Data-Encryption Strategy for Big-Data in Mobile Cloud

2019 ◽  
Vol 9 (1S) ◽  
pp. 1-4
Keyword(s):  
Big Data ◽  
Data Privacy ◽  
Data Encryption ◽  
Mobile Cloud ◽  
Timing Constraints ◽  
Privacy And Security ◽  
Secure Data ◽  
Consistent Performance ◽  
A New Technique ◽  
High Level

Now-a-days data plays a key role in Information Technology and while coming to privacy of that data it has become a considerable issue to maintain data security at high level. Large amounts of data generated through devices are considered as a major obstacle and also tough to handle in real time scenarios. To meetwith consistent performance applications at present abandon encryptions techniquesbecausethe time for the execution and the completion of encryption techniques plays a key role during processing and transmissions of data. In this paper our moto is to secure data and proposed a new technique called Dynamic Data Encryption Strategy (DDES)which selectively encrypts data and uses some algorithms which provides a perfect encryption strategy for the data packages under some timing constraints. By this method we can achieve data privacy and security for big-data in mobile cloud-computing by using an encryption strategy respective to their requirements during execution time.

A Trust-Aware Access Control Policy for Cloud Data Protection

2013 ◽  
Vol 411-414 ◽  
pp. 40-44
Author(s):  
Xiao Yong Tang ◽  
Jin Wei Li ◽  
Gui Ping Liao
Keyword(s):  
Cloud Computing ◽  
Access Control ◽  
Data Privacy ◽  
Large Scale ◽  
Control Policy ◽  
Trust Model ◽  
Data Encryption ◽  
Access Control Policy ◽  
Cloud Users ◽  
Cloud User

The use of Cloud computing systems to run large-scale scientific, business and consumer based IT applications has increased rapidly in recent years. More and more Cloud users concern the data privacy protection and security in such systems. A natural way to tackle this problem is to adopt data encryption and access control policy. However, this solution is inevitably introduced a heavy computation overhead. In this paper, we first establish a trust model between Cloud servers and Cloud users. Then, we build the trust-aware attribute-based access control policies according to Cloud user trust level and Cloud request attributes. This technique can give different encryption and decryption data to Cloud user and substantive reduce the computation overhead of Cloud computing.

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