scholarly journals Repeated Attribute Optimization for Big Data Encryption

2022 ◽  
Vol 40 (1) ◽  
pp. 53-64
Author(s):  
Abdalla Alameen
Keyword(s):  
Big Data ◽  
Data Encryption

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.

BigCrypt for big data encryption

2017 ◽  
Author(s):  
Abdullah Al Mamun ◽  
Khaled Salah ◽  
Somaya Al-maadeed ◽  
Tarek R. Sheltami
Keyword(s):  
Big Data ◽  
Data Encryption

scholarly journals Ensure Security for Mapreduce-Hadoop Distributed File System using Encryption Method Over Big Data

2019 ◽  
Vol 8 (10) ◽  
pp. 733-740
Keyword(s):  
Big Data ◽  
File System ◽  
Data Encryption ◽  
Previous Method ◽  
Distributed File System ◽  
Sensitive Data ◽  
Encryption And Decryption ◽  
Hadoop Distributed File System ◽  
Encryption Method ◽  
Mapreduce Paradigm

Big data security is the most focused research issue nowadays due to their increased size and the complexity involved in handling of large volume of data. It is more difficult to ensure security on big data handling due to its characteristics 4V’s. With the aim of ensuring security and flexible encryption computation on big data with reduced computation overhead in this work, framework with encryption (MRS) is presented with Hadoop Distributed file System (HDFS). Development of the MapReduce paradigm needs networked attached storage in addition to parallel processing. For storing as well as handling big data, HDFS are extensively utilized. This proposed method creates a framework for obtaining data from client and after that examining the received data, excerpt privacy policy and after that find the sensitive data. The security is guaranteed in this framework using key rotation algorithm which is an efficient encryption and decryption technique for safeguarding the data over big data. Data encryption is a means to protect data in storage with containing a key encryption saved and accessible to reuse the data while required. The outcome shows that the research method guarantees greater security for enormous amount of data and gives beneficial info to related clients. Therefore the outcome concluded that the proposed method is superior to the previous method. Finally, this research can be applied effectively on the various domains such as health care domains, educational domains, social networking domains, etc which require more security and increased volume of data.

scholarly journals Design and Analysis of a Microstrip Patch Antenna for TV White Space Data Applications

2021 ◽  
Vol 10 (3) ◽  
pp. 1776-1783
Keyword(s):  
Big Data ◽  
Data Encryption ◽  
Tv White Space ◽  
Microstrip Patch ◽  
Java Language ◽  
Expansion Mechanism ◽  
Three Stages ◽  
Number Of Cycles ◽  
Space Data ◽  
Short Time

In the present study, an algorithm for big data encryption has been designed which is concerned with encrypting data in a short time and in a safe manner and difficult to be penetrated by attackers and hackers according to the mechanism used for encryption in this study.The proposed algorithm is a development of an earlier NSCT algorithm. This development is based on adding a key expansion mechanism to generate keys by F-function, and also the number of cycles have been reduced to get less time. The proposed algorithm has been implemented in three stages; the first stage is implemented by FELICS simulation to find out the efficiency of the algorithm. In thesecond stage the proposed algorithm is implemented on the Java language to encrypt the text and to find out the execution time for the encryption. In the last step, the proposed algorithm is implemented on the MATLAB language to encrypt images and to knowthe performance of the algorithm in terms of countering attacks by hackers.After performing these steps and obtaining the results presented in this study, we can say that the proposed algorithm is capable of dealing with big data and that it can be considered safe and free from risks

scholarly journals MapReduced Based: A New Stream Cipher Technique for Data Encryption

2020 ◽  
Vol 9 (5) ◽  
pp. 763-769
Keyword(s):  
Big Data ◽  
Data Security ◽  
Stream Cipher ◽  
Data Encryption ◽  
Mathematical Operation ◽  
Total Size ◽  
Proposed Model ◽  
Xor Operation ◽  
Secure Data ◽  
Modern Era

Nowadays, data keeps increasing; this in turn makes big data one of the hot topics in the modern era of technology. The biggest challenge, however, is big data security and cryptography is one of the most secure techniques. In this proposed model, we use this technique to secure data via a proposed new stream cipher technique to process more than one block by dividing the total size of the block into two parts, and swapping them then, combine and apply XOR operation with key and make some of mathematical operation. This operation is of fifteen rounds which make it very difficult for attacks to guess the plaintext.

scholarly journals Authorization of Data In Hadoop Using Apache Sentry

2018 ◽  
Vol 7 (3.6) ◽  
pp. 234 ◽  
Author(s):  
N Sirisha ◽  
K V.D. Kiran
Keyword(s):  
Big Data ◽  
Data Security ◽  
Data Encryption ◽  
Security Model ◽  
Huge Amount ◽  
Sensitive Data ◽  
Major Drawback ◽  
Security Issues ◽  
On Demand ◽  
Increasing Trend

Big Data has become more popular, as it can provide on-demand, reliable and flexible services to users such as storage and its processing. The data security has become a major issue in the Big data. The open source HDFS software is used to store huge amount of data with high throughput and fault tolerance and Map Reduce is used for its computations and processing. However, it is a significant target in the Hadoop system, security model was not designed and became the major drawback of Hadoop software. In terms of storage, meta data security, sensitive data  and also the data security will be an serious issue in HDFS. With the importance of Hadoop in today's enterprises, there is also an increasing trend in providing a high security features in enterprises. Over recent years, only some level of security in Hadoop such as Kerberos and Transparent Data Encryption(TDE),Encryption techniques, hash techniques are shown for Hadoop. This paper, shows the efforts that are made to present Hadoop Authorization security issues using Apache Sentry in HDFS. 

Research on Big Data Encryption Algorithm Based on Vector Evaluation Genetic Algorithm

2021 ◽  
Author(s):  
Dawei Yun ◽  
Jingxian Yu ◽  
Zhengao Jia ◽  
Xiuyan Zheng ◽  
Jiabin Wang ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Big Data ◽  
Data Encryption ◽  
Encryption Algorithm
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