An enhance the data security performance using an optimal cloud network security for big data cloud framework

Author(s):  
B. Venkatesan ◽  
S. Chitra
2017 ◽  
Vol 10 (2) ◽  
pp. 338-344
Author(s):  
Sunil Kumar ◽  
Maninder Singh

Network security, data security and several other security types such as the computer security collectively compose the word “Cloud Security”. Cloud computing posses a new challenge because traditional security mechanism is being followed are insufficient to safeguard the cloud resources. Cloud computing can easily be targeted by the attackers. A group of malicious users or illegitimate users can attack on system which may lead to denial the services of legitimate users. Such kinds of attacks are performed by the malicious (zombie) attackers. The zombie attack will degrade the network performance to large extend. Traditional techniques are not easily capable to detect the zombie attacker in the cloud network. So in this paper we have proposed a technique which is the enhancement of the mutual authentication scheme in order to detect and isolate zombie attack for the efficient performance of the network.


2020 ◽  
Vol 13 (4) ◽  
pp. 790-797
Author(s):  
Gurjit Singh Bhathal ◽  
Amardeep Singh Dhiman

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.


2014 ◽  
Vol 30 ◽  
pp. 116-126 ◽  
Author(s):  
Xiangjian He ◽  
Thawatchai Chomsiri ◽  
Priyadarsi Nanda ◽  
Zhiyuan Tan

2018 ◽  
Vol 1 (4) ◽  
pp. e13 ◽  
Author(s):  
Rongxin Bao ◽  
Zhikui Chen ◽  
Mohammad S. Obaidat

Sign in / Sign up

Export Citation Format

Share Document