Energy Big Data Security Threats in IoT-Based Smart Grid Communications

Background: The data is one of the prime assets in today’s world. The continuous data generation ultimately creates huge volume of data that cannot be processed or stored by a normal relational database management system. This problem is addressed by a new concept: Big Data. Apart from the size of data, security and privacy of data are the more challenging issues in Big data technology. Objective: The primary objective of the research is to identify the potential security threats of different big data computing technologies and provide a defense mechanism to mitigate the issues. Methods: To identify the security issues different existing big data systems are thoroughly analysed and observed. Security systems are completely dependent on the system architecture. This can be a single architecture (dependent on one computing technology) or multi architecture type (dependent on multiple computing technologies). The internal mechanism of different technologies is observed and how the attacks change the behavioural pattern of the systems are the main backbone of the research. Based on the behaviour of dissimilar attacks, a comprehensive defense mechanism is identified. Security and privacy challenges of mobile healthcare are also considered as a case study. Results: The complete lists of big data computing security threats in different layers of the systems are identified. Through this research the remedial measures of the different attacks are found. The security challenges of mobile healthcare technology and its predictive measurements are sorted out. The changes of big data security systems behaviour based on its architecture are of the major findings of this research. Conclusion: The integration of mobile healthcare along with Internet of Things (IoT) and blockchain computing can enhance the system level and hence security threats can be minimized.

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Big Data Security Threats and Prevention Measures in Cloud and Hadoop

Data Management, Analytics and Innovation - Advances in Intelligent Systems and Computing ◽

10.1007/978-981-13-1402-5_11 ◽

2018 ◽

pp. 143-156 ◽

Cited By ~ 1

Author(s):

Manoranjan Behera ◽

Akhtar Rasool

Keyword(s):

Big Data ◽

Data Security ◽

Security Threats ◽

Prevention Measures

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Issues in security and privacy of big data

International Journal of Advanced Research in Computer Science and Software Engineering ◽

10.23956/ijarcsse.v7i12.482 ◽

2018 ◽

Vol 7 (12) ◽

pp. 1

Author(s):

Shaveta Bhatia

Keyword(s):

Cloud Computing ◽

Big Data ◽

Approximate Method ◽

Biomedical Research ◽

Cyber Security ◽

Data Science ◽

Third Party ◽

Security And Privacy ◽

Security Threats ◽

The Third

The epoch of the big data presents many opportunities for the development in the range of data science, biomedical research cyber security, and cloud computing. Nowadays the big data gained popularity. It also invites many provocations and upshot in the security and privacy of the big data. There are various type of threats, attacks such as leakage of data, the third party tries to access, viruses and vulnerability that stand against the security of the big data. This paper will discuss about the security threats and their approximate method in the field of biomedical research, cyber security and cloud computing.

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

Recent Advances in Computer Science and Communications ◽

10.2174/2213275912666190822095422 ◽

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.

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Classification of Cloud Systems Cyber-security Threats and Solutions Directives

Application and Theory of Computer Technology ◽

10.22496/atct20170227147 ◽

2017 ◽

Vol 2 (3) ◽

pp. 1

Author(s):

Hanane Bennasar ◽

Mohammad Essaaidi ◽

Ahmed Bendahmane ◽

Jalel Benothmane

Keyword(s):

Cloud Computing ◽

Cyber Security ◽

Data Security ◽

Denial Of Service ◽

Security Threats ◽

Huge Number ◽

Open Problems ◽

Long Period ◽

Near Future

Cloud computing cyber security is a subject that has been in top flight for a long period and even in near future. However, cloud computing permit to stock up a huge number of data in the cloud stockage, and allow the user to pay per utilization from anywhere via any terminal equipment. Among the major issues related to Cloud Computing security, we can mention data security, denial of service attacks, confidentiality, availability, and data integrity. This paper is dedicated to a taxonomic classification study of cloud computing cyber-security. With the main objective to identify the main challenges and issues in this field, the different approaches and solutions proposed to address them and the open problems that need to be addressed.

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