A Multi-level Intelligent Selective Encryption Control Model for Multimedia Big Data Security in Sensing System with Resource Constraints

2016 ◽  
Author(s):  
Chen Xiao ◽  
Lifeng Wang ◽  
Zhu Jie ◽  
Tiemeng Chen
Keyword(s):  
Big Data ◽  
Data Security ◽  
Resource Constraints ◽  
Control Model ◽  
Selective Encryption ◽  
Multimedia Big Data ◽  
Sensing System ◽  
Multi Level

Managing Multimedia Big Data: Security and Privacy Perspective

2020 ◽  
pp. 1-12
Author(s):  
Gayatri Kapil ◽  
Zaiba Ishrat ◽  
Rajeev Kumar ◽  
Alka Agrawal ◽  
Raees Ahmad Khan
Keyword(s):  
Big Data ◽  
Data Security ◽  
Security And Privacy ◽  
Multimedia Big Data

scholarly journals Big Data Security with Access Control Model and Honeypot in Cloud Computing

2019 ◽  
Vol 178 (33) ◽  
pp. 16-20 ◽  
Author(s):  
Jahanara Akhtar ◽  
Md. Tahzib-Ul-Islam ◽  
Md. Habibullah ◽  
Saiful Islam
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Access Control ◽  
Data Security ◽  
Control Model ◽  
Access Control Model

Big Data Security Challenges and Solution of Distributed Computing in Hadoop Environment: A Security Framework

2020 ◽  
Vol 13 (4) ◽  
pp. 790-797
Author(s):  
Gurjit Singh Bhathal ◽  
Amardeep Singh Dhiman
Keyword(s):  
Big Data ◽  
Data Security ◽  
Data Sets ◽  
Security Framework ◽  
Hadoop Distributed File System ◽  
Current Scenario ◽  
Hadoop Cluster ◽  
Ciphertext Policy ◽  
In Transit ◽  
Hadoop Framework

Background: In current scenario of internet, large amounts of data are generated and processed. Hadoop framework is widely used to store and process big data in a highly distributed manner. It is argued that Hadoop Framework is not mature enough to deal with the current cyberattacks on the data. Objective: The main objective of the proposed work is to provide a complete security approach comprising of authorisation and authentication for the user and the Hadoop cluster nodes and to secure the data at rest as well as in transit. Methods: The proposed algorithm uses Kerberos network authentication protocol for authorisation and authentication and to validate the users and the cluster nodes. The Ciphertext-Policy Attribute- Based Encryption (CP-ABE) is used for data at rest and data in transit. User encrypts the file with their own set of attributes and stores on Hadoop Distributed File System. Only intended users can decrypt that file with matching parameters. Results: The proposed algorithm was implemented with data sets of different sizes. The data was processed with and without encryption. The results show little difference in processing time. The performance was affected in range of 0.8% to 3.1%, which includes impact of other factors also, like system configuration, the number of parallel jobs running and virtual environment. Conclusion: The solutions available for handling the big data security problems faced in Hadoop framework are inefficient or incomplete. A complete security framework is proposed for Hadoop Environment. The solution is experimentally proven to have little effect on the performance of the system for datasets of different sizes.

Call for Special Issue Papers: Multimedia Big Data Analytics for Engineering Education

Big Data ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 87-88
Author(s):  
Priyan Malarvizhi Kumar ◽  
Hari Mohan Pandey ◽  
Gautam Srivastava
Keyword(s):  
Big Data ◽  
Engineering Education ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Special Issue ◽  
Multimedia Big Data

BC-BLPM: A multi-level security access control model based on blockchain technology

2021 ◽  
Vol 18 (2) ◽  
pp. 110-135
Author(s):  
Xiang Yu ◽  
Zhangxiang Shu ◽  
Qiang Li ◽  
Jun Huang
Keyword(s):  
Access Control ◽  
Control Model ◽  
Access Control Model ◽  
Model Based ◽  
Blockchain Technology ◽  
Multi Level
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