Security and Privacy Issues in Analytics - Dumnonia Corporation

Running head: SECURITY AND PRIVACY ISSUES IN ANALYTICS
Security and Privacy Issues in Analytics
(Dumnonia Corporation)
Name of the student:
Name of the university:
Author Note

1SECURITY AND PRIVACY ISSUES IN ANALYTICS
Executive summary
Dumnonia Corporation is a very popular insurance company situated in Australia. The company
sells different insurances. It includes medical, death and travel insurances. It has held various
medical data for customers. This is highly confidential, and the company has required to share-
person to person records so that they can find out who gets subjected to data that are not found out. It
has also released records adhering to k-anonymity. It shows that the document issued comprises if k-
1 additional records for releasing values. These values are no different over sectors that are being
found to appearing external data ever. It is also found out that methods of k-anonymity have been
dealing with problems of privacy that are acquired by Dumnonia. K-anonymity method has ensured
preservations of data and processes that are to be considered by Dumnonia. Further, the report is
useful to find out operational and related issues and expenses for implementing k-anonymity.
Moreover, the report also highlights whether the costs are once-off or ongoing. At last, the report
also examines the areas of applications of anonymity process that is helpful to share data sets taking
place between different organisational entities and governments with the current organisation at
Australia.

2SECURITY AND PRIVACY ISSUES IN ANALYTICS
Table of Contents
1. Introduction:......................................................................................................................................3
2. Discussion on organizational drivers for Dumnonia:........................................................................3
3. Understanding organisational drivers at Dumnonia related to the deployment of k-anonymity:......4
4. Analysis of Technology Solution:.....................................................................................................6
5. Technologies utilised to deploy k-anonymity as a model:................................................................7
6. K-anonymity Implementation Guide:................................................................................................8
7. Conclusion:......................................................................................................................................10
8. References:......................................................................................................................................11

3SECURITY AND PRIVACY ISSUES IN ANALYTICS
1. Introduction:
Different issues regarding privacy and security are found to be originating from controlling,
storing and examining data that are gathered from probable and available sources. In this study, a
demonstration is made on organisational drivers that related to implementing k-anonymity of the
organisation named Dumnonia. Here technologies are outlined, and different methods to achieve k-
anonymity for protecting privacies are also investigated.
2. Discussion on organizational drivers for Dumnonia:
Different cyber-security threats are been faced through big-data systems of the company.
Specifically, Ransomware attacks has left deployment of big data that is subjected towards different
Ransom demands. Further, there are issues regarding unauthorized users who have been gaining
access for big data that is gathered through organization and then selling those precious information.
Vulnerability of the system gives rise to fraud information generation (Prasser et al. 2014).
Moreover, attackers are deliberately undermining quality of big data analysis. It is done by
fabricating information and placing those to various systems of big data systems. Further corrupting
of information in medical department of the Australian company created reports. This was
comprised of different mistaken information that has been trending. Moreover, a distinct lack of
perimeters of cybersecurity is also found for big data. These have ensured that all the points towards
entry and exit for big data systems are been secured. Failure to perimeter-based security is comprised
of networks of big data. This has also been admitted that challenges in cybersecurity and different
other individuals have been aware of those concerns. Besides, there are problems regarding how to
deploy encryptions within Dumnonia’s systems of big data (Dubovitskaya et al. 2015). Apart from
this, encodings from big systems have also been involved in calculating and processing a high