TPISSC

5

Outline: Argumentative Paper on Computer Related Crimes and Computer Forensics

Temeika Williams

American Military University

ISSC351

Professor Yongge Wang

November 14, 2021

Outline: Argumentative Paper on Computer Related Crimes and Computer Forensics

I. Introduction

a. Thesis: Computer forensics needs to be used in big organizations to solve critical crimes committed by using computers like employees internet abuse, intellectual property theft, investigation of fraud activities, and forgeries related matters achieved through computers to reduce losses incurred.

II. Body paragraph 1: Employees' use of the internet in an unhealthy way has contributed to computer-related crimes in the workplace.

a. Supportive Evidence: “…cyberbullying occurs through different ways from aggressive and threatening behavior to social ostracism with severe effects on the general well-being of people whose identity are centrally based on social media ties" (Oksanen et al., 2020).

i. Explanation: This quote alludes that internet use in the workplace without control can cause vital computer crimes related to bullying, which is aggressive behavior threatening social ostracism.

ii. So What? : The quote demonstrates the need for organizations to develop and use computer forensics in the workplace to monitor and control the use of the internet that can increase computer crimes related to workers' internet use.

III. Body paragraph 2: Another computer-related crime that needs to be solved through computer forensics in big data organizations is the issues of data forgeries and fraud activities committed by internal and external personnel in the workplace.

a. Supportive Evidence: The world is going through a significant data cohort, creating a profound paradigm shift in addressing growing cyber threats related to data forgeries and fraud due to an increase in the data files, which has promoted computer crime increase (Mishra, 2020).

i. Explanation: This quote shows that as organizations experience an increase in the size of data stored in the online systems, the challenge of handling and analyzing those increases causes many computer crimes like data forging and other fraud activities to occur, threatening data cohort.

ii. So What? : Showing that data forgeries and fraud are critical computer crimes, organizations dealing with bid data like financial institutions should ensure the use of computer forensic applications and systems to control and manage all their data transactions in relation to forensics laws and regulations.

IV. Body paragraph 3: Finally, organizations dealing with big data are responsible for enhancing their cyber security through the use of computer forensics to control all computer crimes related to intellectual property thefts.

a. Supportive Evidence: “…potential financial benefits have continued to favor data bleaching and collection which has high potentiality on increasing physical damage to critical infrastructure” (Tao et al., 2019).

i. Explanation: This quote shows that the computer-related crime of intellectual property theft has been promoted by some individuals robbing companies' ideas, inventions, and creative expressions shared on their computer systems.

ii. So What? : This quote supports the claim that the intellectual property theft issue contributes to computer crime to most organizations dealing with bid data through explaining how ideas, inventions, and creative expressions of the company are robbed and therefore addressing the need for computer forensic in solving the issue.

V. Conclusion

a. Rephrased Thesis: Computer-related crimes are causing organizations severe losses due to poor management and control of all potential and vital company information. Therefore, corporates need to apply forensic principles in their data management to solve the issues of computer crimes.

b. Strong Closing: The use of computer forensics in the workplace is vital in solving the computer-related crime before the case mounts to an uncontrollable level.

References

Mishra, P. (2020). Big data digital forensic and cybersecurity. In Big data analytics and computing for digital forensic investigations (pp. 183-203). CRC Press.

Oksanen, A., Oksa, R., Savela, N., Kaakinen, M., & Ellonen, N. (2020). Cyberbullying victimization at work: Social media identity bubble approach. Computers in human behavior, 109, 106363.https://doi.org/10.1016/j.chb.2020.106363

Tao, H., Bhuiyan, M. Z. A., Rahman, M. A., Wang, G., Wang, T., Ahmed, M. M., & Li, J. (2019). Economic perspective analysis of protecting big data security and privacy. Future Generation Computer Systems, 98, 660-671.https://doi.org/10.1016/j.future.2019.03.042