Security and Privacy Implications of AI-powered Tax Filing Systems: Safeguarding Taxpayers Data in the Age of Automation
DOI:
https://doi.org/10.48001/978-81-966500-6-3-1Keywords:
AI-powered tax filing, Security, Privacy, Data protection, Cyber security, Ethics, Regulatory complianceAbstract
The integration of artificial intelligence (AI) into tax filing systems has revolutionized traditional processes, promising enhanced efficiency and accuracy. However, alongside these benefits there comes a significant security and privacy concerns. This paper examines the multifaceted implications of AI-powered tax filing systems on security and privacy, exploring risks such as data breaches, unauthorized access, and the protection of sensitive taxpayer information. Drawing upon recent case studies and regulatory frameworks, this paper highlights the critical need for robust security measures and privacy safeguards to protect taxpayer data. Furthermore, it presents strategies to mitigate risks while ensuring compliance with legal and ethical standards. By providing insights for policymakers, tax authorities, and developers tasked with designing and implementing AI-driven tax filing systems, this paper aims to contribute to the development of secure and privacy-respecting tax filing solutions in the age of automation.
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References
Calderon, T., McCoskey, M. G., & Colin, O. (2021). Toward a Protocol for Tax Data Security. Journal of Journal of Forensic and Investigative Accounting, 13(1).
Dhayanidhi, G. (2022). Research on IoT Threats Implementation of AI/ML to Address Emerging Cybersecurity Issues in IoT with Cloud Computing. https://doi.org/10.7939/r3-4p3q-wp04
Fidelangeli, A., & Galli, F. (2021). Artificial Intelligence and Tax Law: Perspectives and Challenges. Ceridap, 221(4), 24–58. https://doi.org/10.13130/2723-9195/2021-4-27
Gautam, S., & Mittal, P. (2022). Systematic Analysis of Predictive Modeling Methods in Stock Markets. International Research Journal of Computer Science, 9(11), 377– 385. https://doi.org/10.26562/irjcs.2022.v0911.01
Gupta, S., & Mittal, P. (2015). Base Erosion and Profit Shifting: The New Framework of International Taxation. Journal of Business Management and Information Systems, 2(2), 108–114. https://doi.org/10.48001/jbmis.2015.0202009
Joseph Kuba Nembe, Joy Ojonoka Atadoga, Noluthando Zamanjomane Mhlongo, Titilola Falaiye, Odeyemi Olubusola, Andrew Ifesinachi Daraojimba, & Bisola Beatrice Oguejiofor. (2024). The Role of Artificial Intelligence in Enhancing Tax Compliance and Financial Regulation. Finance Accounting Research Journal, 6(2), 241– 251. https://doi.org/10.51594/farj.v6i2.822
Mittal, P., & Gautam, S. (2023). Logistic Regression and Predictive Analysis in Public Services of AI Strategies. TEM Journal, 12(2), 751–756. https://doi.org/10.18421/TEM122-19
Neupane, A. (2023). Transformation of Public Service: Rise of Technology, AI and Automation. Prashasan: The Nepalese Journal of Public Administration, 55(2), 42– 52. https://doi.org/10.3126/prashasan.v55i2.63538
Nobert, O., David, N., & Robert, O. O. (2020). The challenges affecting tax collection in Nigerian informal economy: Case study of Anambra State. Journal of Accounting and Taxation, 12(2), 61–74. https://doi.org/10.5897/jat2020.0388
Perwej, Y., Qamar Abbas, S., Pratap Dixit, J., Akhtar, D. N., & Kumar Jaiswal, A. (2021). A Systematic Literature Review on the Cyber Security. International Journal of Scientific Research and Management, 9(12), 669–710. https://doi.org/10.18535/ijsrm/v9i12.ec04
Ruiz, M. A. G. (2022). Fiscal Transformations Due To Ai and Robotization: Where Do Recent Changes in Tax Administrations, Procedures and Legal Systems Lead Us? Northwestern Journal of Technology and Intellectual Property, 19(4), 325–363.
SatheeshKumar, M., Srinivasagan, K. G., & UnniKrishnan, G. (2022). A lightweight and proactive rule-based incremental construction approach to detect phishing scam. Information Technology and Management, 23(4), 271–298. https://doi.org/10.1007/s10799-021-00351-7
Singh, I., & Aggarwal, N. (2023). Role of AI Chatbot in Income Tax Prediction in India. VISION: Journal of Indian Taxation, 10(2), 87–117. https://doi.org/10.17492/jpi.vision.v10i2.1022306
Thomas, L., Gondal, I., Oseni, T., & (Sally) Firmin, S. (2022). A framework for data privacy and security accountability in data breach communications. Computers and Security, 116. https://doi.org/10.1016/j.cose.2022.102657
