Modeling OTP Delivery Notification Status through a Causality Bayesian Network

https://doi.org/10.22146/ijccs.90030

Novendri Isra Asriny(1*), Chandra Kusuma Dewa(2), Ahmat Luthfi(3)

(1) Universitas Islam Indonesia
(2) Universitas Islam Indonesia
(3) Universitas Islam Indonesia
(*) Corresponding Author

Abstract


Digital money is the fundamental driving factor behind today's modern economy. Credit/debit cards, e-wallets, and other contactless payment options are widely available nowadays. This also raises the security risk associated with passwords in online transactions. One-time passwords (OTPs) are another option for mitigating this. A one-time password (OTP) serves as an additional password authentication or validation technique for each user authentication session. Failures in transmitting OTP passwords through SMS can arise owing to operator network faults or technological concerns.To minimize the risk value that arises in online transactions, it is necessary to evaluate the causality of the OTP SMS sending transaction status category by determining the main factors for successful OTP SMS sending and identifying the causes of failure when sending OTP SMS using the Bayesian Network method. According to data analysis, online transactions occur more frequently in the morning, with status summaries such as no delay, unknown status, and others. Furthermore, there is causality with at least three variables in the principal status summary, including no delay, uncertain summary, long delay, normal, likely operator issues, abnormal, and more. With a high accuracy rate of around 90% in forecasting the likelihood of recurrence.

Keywords


online transaction;one-time password; SMS transaction;machine learning;bayesian network

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References

L. H. Lin, F. C. Lin, C. K. Lien, T. C. Yang, Y. K. Chuang, and Y. W. Hsu, “Electronic Payment Behaviors of Consumers under Digital Transformation in Finance—A Case Study of Third-Party Payments,” J. Risk Financ. Manag., vol. 16, no. 8, 2023, doi: 10.3390/jrfm16080346.

Xendit, “e-Wallet Payments usage and trends in Indonesia,” Xendit, 2022. .

D. Permatasari, “Tantangan Cyber Security di Era Revolusi Industri 4.0,” Kementerian Keuangan Republik Indonesia, 2021. .

Badan Siber dan Sandi Negara, “Lanskap Keamanan Siber Indonesia 2022,” Indonesia, 2022.

L. E. Almeida, B. A. Fernández, D. Zambrano, A. I. Almachi, H. B. Pillajo, and S. G. Yoo, A Complete One-Time Passwords (OTP) Solution Using Microservices: A Theoretical and Practical Approach, no. September. Springer Nature Switzerland, 2023.

M. H. S. Abousteit, A. F. Tammam, and A. M. Wahdan, “A novel approach for generating one-time password with secure distribution,” Proc. World Conf. Smart Trends Syst. Secur. Sustain. WS4 2020, pp. 461–466, 2020, doi: 10.1109/WorldS450073.2020.9210322.

J. Díaz-Ramírez, “Machine Learning and Deep Learning,” Ingeniare, vol. 29, no. 2, pp. 182–183, 2021, doi: 10.4067/S0718-33052021000200180.

T. Lu, L. Wang, and X. Zhao, “Review of Anomaly Detection Algorithms for Data Streams,” Appl. Sci., vol. 13, no. 10, 2023, doi: 10.3390/app13106353.

G. Briganti, M. Scutari, and R. J. Mcnally, “A tutorial on Bayesian Networks for psychopathology researchers). Network theory comes with,” COS (Center Open Sci., 2013.

L. Vojković, A. K. Skelin, D. Mohovic, and D. Zec, “The development of a bayesian network framework with model validation for maritime accident risk factor assessment,” Appl. Sci., vol. 11, no. 22, 2021, doi: 10.3390/app112210866.

N. L. Ackerman, C. E. Freer, and D. M. Roy, “On the computability of conditional probability,” J. ACM, vol. 66, no. 3, 2019, doi: 10.1145/3321699.

A. Y. Alin, K. Kusrini, and K. A. Yuana, “The Effect of Data Augmentation in Deep Learning with Drone Object Detection,” IJCCS (Indonesian J. Comput. Cybern. Syst., vol. 17, no. 3, p. 237, 2023, doi: 10.22146/ijccs.84785.

C. A. Bahri and L. H. Suadaa, “Aspect-Based Sentiment Analysis in Bromo Tengger Semeru National Park Indonesia Based on Google Maps User Reviews,” IJCCS (Indonesian J. Comput. Cybern. Syst., vol. 17, no. 1, p. 79, 2023, doi: 10.22146/ijccs.77354.



DOI: https://doi.org/10.22146/ijccs.90030

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