Enhancement of an Optimized Key for Database Sanitization to Ensure the Security and Privacy of an Autism Dataset

Md Mokhlesur Rahman,Ravie Chandren Muniyandi,Suziyani Mohamed,Shahnorbanun Sahran

doi:10.3390/sym13101912

Abstract

Interrupting, altering, or stealing autism-related sensitive data by cyber attackers is a lucrative business which is increasing in prevalence on a daily basis. Enhancing the security and privacy of autism data while adhering to the symmetric encryption concept is a critical challenge in the field of information security. To identify autism perfectly and for its data protection, the security and privacy of these data are pivotal concerns when transmitting information over the Internet. Consequently, researchers utilize software or hardware disk encryption, data backup, Data Encryption Standard (DES), TripleDES, Advanced Encryption Standard (AES), Rivest Cipher 4 (RC4), and others. Moreover, several studies employ k-anonymity and query to address security concerns, but these necessitate a significant amount of time and computational resources. Here, we proposed the sanitization approach for autism data security and privacy. During this sanitization process, sensitive data are concealed, which avoids the leakage of sensitive information. An optimal key was generated based on our improved meta-heuristic algorithmic framework called Enhanced Combined PSO-GWO (Particle Swarm Optimization-Grey Wolf Optimization) framework. Finally, we compared our simulation results with traditional algorithms, and it achieved increased output effectively. Therefore, this finding shows that data security and privacy in autism can be improved by enhancing an optimal key used in the data sanitization process to prevent unauthorized access to and misuse of data.

Highlights

Diagnostic and Statistical Manual of Mental Disorders 5th ed. (DSM-5) [1,2] defined autism spectrum disorder (ASD) as persistent deficits in two areas of development, namely social communication as well as restricted and repetitive behaviors
The security and privacy of the autism dataset through the sanitizing technique were investigated in this study
An optimal key was produced for concealing the sensitive data, which was selected by the proposed Enhanced Combined particle swarm optimization (PSO)-grey wolf optimizer (GWO) framework and resolved the problems mentioned in introduction

Summary

Introduction

Diagnostic and Statistical Manual of Mental Disorders 5th ed. (DSM-5) [1,2] defined autism spectrum disorder (ASD) as persistent deficits in two areas of development, namely social communication as well as restricted and repetitive behaviors. (DSM-5) [1,2] defined autism spectrum disorder (ASD) as persistent deficits in two areas of development, namely social communication as well as restricted and repetitive behaviors. Children with ASD have a distinct set of deficits but with different levels of severity. DSM-5 has divided ASD into three levels of severity based on the support required by children with ASD in their daily lives. These severity levels range from level one to level three, and are known as requiring support, requiring substantial support, and requiring very substantial support, respectively. Children with ASD demonstrate poor social communication skills, as they have deficits in verbal communication, non-verbal communication, and socialemotional reciprocity. Deficits in verbal communication cause children with ASD to exhibit difficulties in understanding spoken language and the use of inappropriate tone of voice during conversation

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