scholarly journals A Novel Approach based on Bucketization for Privacy Preserving Access Control Mechanism for Relational Data

2018 ◽  
Vol 182 (6) ◽  
pp. 15-18
Author(s):  
Anuja A. ◽  
A. B.
2014 ◽  
Vol 26 (4) ◽  
pp. 795-807 ◽  
Author(s):  
Zahid Pervaiz ◽  
Walid G. Aref ◽  
Arif Ghafoor ◽  
Nagabhushana Prabhu

2020 ◽  
Vol 8 (5) ◽  
pp. 2390-2396

With the increased development of cloud computing, access control is of paramount importance as a security concern. Numerous access control approaches exist in various published works. Among such prevalent approaches, Role Based Access Control (RBAC) model for enterprise cloud is scope of the present study. Nowadays, resource management, along with the primary aspect of security concern, is also addressed by the access control policies through restricting the allocation of the computing resources based on the roles assigned to the users. Keeping in view of the upcoming peak-load requirements or certain constraints, the policies may have ineffective resource allocation which leads to over/under-utilization of the resources over a period of time. So, an adaptive access control mechanism is desired that can vary their policies dynamically for resource allocation depending upon the ongoing requirements, for its efficient utilization. This is presented in the form of an adaptive access control mechanism (AACM) that aims to effectively utilize the computing resources in the enterprise cloud. It will aid in identifying the over- and under-allocation of the computing resources defined as access control policies and redefine these policies so as to ensure efficient and effective usage of the enterprise cloud resources. In this paper, this novel approach to access control mechanism for the enterprise cloud is represented using ontologies developed in Protégé. This is developed by identification of the underlying concepts and their interrelationships through properties, in the enterprise cloud. The presented ontology is for the sake of knowledge representation to represent knowledge and facts.


2021 ◽  
Vol 13 (6) ◽  
pp. 0-0

The extensive use of digital devices by individuals generates a significant amount of private data which creates challenges for investigation agencies to protect suspects' privacy. Existing digital forensics models illustrate the steps and actions to be followed during an investigation, but most of them are inadequate to investigate a crime with all the processes in an integrated manner and do not protect suspect's privacy. In this paper, we propose the development of a privacy-preserving digital forensics (P2DF) framework, which facilitates investigation through maintaining confidentiality of the suspects through various privacy standards and policies. It includes an access control mechanism which allows only authorized investigators to access private data and identified digital evidences. It is also equipped with a digital evidence preservation mechanism which could be helpful for the court of law to ensure the authenticity, confidentiality, and reliability of the evidences, and to verify whether privacy of the suspect was preserved during the investigation process.


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