Data Security Assignment: Protecting Data and Ethical Concerns

This assignment delves into crucial aspects of data security, beginning with the proactive measures organizations can implement to safeguard against data breaches and the theft of account data. It emphasizes the importance of system updates, user authentication, and the implementation of robust security policies. The assignment then transitions to the continuous monitoring of information systems, outlining various indicators and methodologies to ensure data security, including the utilization of secondary data and checklists. Furthermore, the assignment critically examines the ethical implications of sharing customer information for marketing and data mining purposes, highlighting concerns about data privacy, transparency, and potential biases inherent in data mining practices. The student emphasizes the necessity of informed consent and the potential for data mining to perpetuate inequalities, providing a comprehensive overview of data security challenges and ethical considerations.

Running head: DATA SECURITY
DATA SECURITY
Name of Student
Name of University
Author’s Note

1DATA SECURITY
What can organizations do to protect themselves from hackers looking to steal account
data?
Organizations can undertake numerous steps for the purpose of protecting their
business from multiple hackers who aspire to steal account data (Rahman, Daud &
Mohamad, 2016). Some of the steps that could be undertaken by organizations include
keeping their systems up to date, not revealing their data to any unauthorized user or an
outsider. Some more steps include they must always authenticate as well as verify the user
who tends to access the data, implement policies that could help them as well as employees in
securing their account data (Rahman, Daud & Mohamad, 2016). One of the most crucial step
that should be provided more concentration include securing the organizational website, this
would it only secure the account data that belongs to the customers but also help organization
in preventing any sort of data leak internally or externally.
What would you do to continually monitor your information systems to ensure that data
is secure?
For the purpose of monitoring the information system continuously in order ensure
that data is secured, numerous indicators like output indicators, objective indicators, activity
indicators that had been established in the framework must be accessed or measured in the
entire process (Rao & Selvamani, 2015). Secondary data, as well as checklists, should be
utilized to measure various activity indicators regularly. For the purpose of monitoring output
as well as objective indicators, numerous samples of households that had received support
besides which baseline data is accessible would be chosen (Thompson, Ravindran & Nicosia,
2015). After that, they would be interviewed at specific periods with the use of proper tools
for monitoring that are available in the framework to measure indicators.

2DATA SECURITY
Typically, organizations may share information about their customers, a form of
marketing and data- mining. Do you think this is an ethical practice?
Sharing customer information for the purpose of marketing as well as data mining
cannot be considered as an ethical practice (Guzzo, Fink & King, 2015). Data mining tends to
possess a threat to data privacy, and this is because mostly the data relevant to individuals or
groups are freely accessible by the websites or organizations. Sharing of data tends to amplify
subtle as well as complicated questions regarding the interpretation, collaboration,
transparency as well as trust, which are basics of ethical concerns (Chen, Ramamurthy &
Wen, 2015). The individuals should be informed regarding the purpose for which the data is
being accessed and who would be the recipient of the information, the implications along
with the related data (Li, Gai & Ming, 2016). Data mining has the ability to replicate much
systematic inequality with the help of discovering numerous patterns. These patterns were
relevant to bias which had been present but were not accounted for a specific database
architecture.

3DATA SECURITY
References
Chen, Y. A. N., Ramamurthy, K. R. A. M., & Wen, K. W. (2015). Impacts of comprehensive
information security programs on information security culture. Journal of Computer
Information Systems, 55(3), 11-19.
Guzzo, R. A., Fink, A. A., King, E., Tonidandel, S., & Landis, R. S. (2015). Big data
recommendations for industrial–organizational psychology. Industrial and
Organizational Psychology, 8(4), 491-508.
Li, Y., Gai, K., Ming, Z., Zhao, H., & Qiu, M. (2016). Intercrossed access controls for secure
financial services on multimedia big data in cloud systems. ACM Transactions on
Multimedia Computing, Communications, and Applications (TOMM), 12(4s), 67.
Rahman, A. F. A., Daud, M., & Mohamad, M. Z. (2016, March). Securing sensor to cloud
ecosystem using internet of things (iot) security framework. In Proceedings of the
International Conference on Internet of things and Cloud Computing (p. 79). ACM.
Rao, R. V., & Selvamani, K. (2015). Data security challenges and its solutions in cloud
computing. Procedia Computer Science, 48, 204-209.
Thompson, N., Ravindran, R., & Nicosia, S. (2015). Government data does not mean data
governance: Lessons learned from a public sector application audit. Government
information quarterly, 32(3), 316-322.