Extract Compliance-Related Evidence Using Machine Learning

This paper discusses the intersection between cybersecurity and machine learning. Machine learning is able to read documents and automatically extract, evaluate, and check if they meet the expected evidence value based on trained algorithms. Cybersecurity compliance assessment requires massive docum...

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Bibliographic Details
Main Authors: Alattas, Hussain Talal, Almassary, Fatema Mohammed, AlMahasheer, Noof Rashed, Alammari, Reema Mubarak, Alswaidan, Huda Ayad, Nagy, Naya Marius, Almoqbel, Munirah Ali, Alharthi, Saad Abdulrahman
Format: Conference Proceeding
Language:English
Subjects:
assessment
compliance
Computational modeling
Costs
Information retrieval
Machine learning
Machine learning algorithms
Regulation
Training
Online Access:Request full text
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Summary:This paper discusses the intersection between cybersecurity and machine learning. Machine learning is able to read documents and automatically extract, evaluate, and check if they meet the expected evidence value based on trained algorithms. Cybersecurity compliance assessment requires massive documents check and image reviews and is often assessed by concerned parties manually. Automating the compliance assessment process using machine learning has huge benefits in the regards of time, speed as well as costs. The paper's objective is to analyze and assess the procedures of previously proposed models, datasets, and their results within the specified scope. The major aim of this research paper is to summarize the current compliance automation algorithms using machine learning.
ISSN:2472-7555
DOI:10.1109/CICN56167.2022.10008324