Title: An enhanced test case prioritisation with cyber-security detection using CMSANN for banking or finance software

Authors: Durga Praveen Deevi; Naga Sushma Allur; Koteswararao Dondapati; Himabindu Chetlapalli; Thinagaran Perumal

Addresses: O2 Technologies Inc., Irvine, California, USA ' Astute Solutions LLC, Folsom, California, USA ' Everest Technologies, Columbus, Ohio, USA ' 9455868 Canada Inc., Whitby, Ontario, Canada ' Department of Computer Science, University Putra Malaysia, Malaysia

Abstract: In the software development process, software testing executes a program to detect errors. During this process, security attacks may occur, posing significant threats. Incorporating AI into cybersecurity testing processes can help organisations protect sensitive financial data from unauthorised access. So, this research methodology proposed a CMSANN-based cybersecurity prediction for software testing. Initially, the test cases are generated and prioritised using the WW-ArCa-PA approach in the banking or finance application. Then, it enters the data structuring phase. Data are mapped using AKNMHC and reduced using the HS approach in this phase. Then, the features are extracted and given to the cyber-security detection phase. The anomaly dataset is given as input, and pre-processing is performed using MVI, numeralisation, and normalisation. After pre-processing, the features are extracted, and then data are balanced using the ACA-CTSYN approach. The balanced data is given to the CMSANN classifier for cyber security detection.

Keywords: artificial intelligence; AI; convolutional multi-head self-improving attention neural network; CMSANN; waterwheel Arnold's cat plant algorithm; WW-ArCa-PA; agglomerative kernel normalised Mahalanobis hierarchical clustering; AKNMHC; adaptive cover tree synthetic sampling; ADA-CTSYN; cyber security and software testing.

DOI: 10.1504/IJCCBS.2026.153779

International Journal of Critical Computer-Based Systems, 2026 Vol.12 No.1, pp.71 - 97

Received: 09 Aug 2024
Accepted: 05 Nov 2024
Published online: 26 May 2026 *

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