Preserving the Privacy of Healthcare Data over Social Networks Using Machine Learning

Veeramakali, T.; Shobanadevi, A.; Nayak, Nihar Ranjan; Kumar, Sumit; Singhal, Sunita; Manoharan, S.

doi:10.1155/2022/4690936

Cited by 5 publications

(5 citation statements)

References 36 publications

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“…The extensive demand for electronic health records of a patient in the illegal market aggravated the virtual attacks destroying the reputation and wealth of the medical institutions. 16 Attackers tried injecting malicious payloads into the network. It is extremely challenging for organizations to develop appropriate protection and response measures to give the dynamic environment.…”

Section: Covid-19 and Cyberattackmentioning

confidence: 99%

Cyber Attack - Envenom in Indian Healthcare – A Review

Balaji¹,

Raghunathan²,

V.³

et al. 2023

Int. J. Res. Publ. Rev.

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The year of lockdown in 2019 had drawn attention to the rise in cyberattacks on healthcare organizations in recent years. While embracing digital technology to raise the standard of patient care, healthcare professionals are growing more and more concerned about these cyberattacks. As a result, it is crucial to combat cyberattacks on healthcare systems as a whole and inside them. Cybersecurity, IT networks, and software deployment are all necessary for a successful electronic health record system. The benefits of these safe electronic health records for patients include better healthcare efficiency, which has a substantial positive impact on the standard of treatment and patient safety. The number of phishing attacks in the healthcare industry found to be increasing. Accurate detection of these attacks is one of the major challenges in healthcare organizations. With help of basic security standards and strategies at both organizational and individual levels will help us to rise against cyberattacks. Cybersecurity offers information on the scope of cyberattacks and their effects on employee well-being and makes the case that cybersecurity education for all employees in healthcare organizations has to be improved. Hence the current state of cybersecurity in healthcare facilities should be knocked upon and related safety preventive measures should be evaluated. Therefore, the importance to have protection controls to guard the personal information of human beings has to be sorted and cognizance and awareness amongst people involved in cyber security ought to be created.

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Section: Covid-19 and Cyberattackmentioning

confidence: 99%

Cyber Attack - Envenom in Indian Healthcare – A Review

Balaji¹,

Raghunathan²,

V.³

et al. 2023

Int. J. Res. Publ. Rev.

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“…Computer-Assisted Language Learning (CALL) technology has revolutionized Chinese instruction and learning, addressing this issue [9]. Learners must adapt their methods of instruction to meet the difficulties of rapidly changing knowledge content and tough worldwide competition for highly qualified individuals [10,11]. To be qualified citizens at 21st century, students should not have comprehensive understanding topic matter, study, and problem-solve, analyse independently, and apply information [12].…”

Section: Introductionmentioning

confidence: 99%

Language Dissemination Paths and Modes Aided by Computer Technology

Yanghong Wu

2024

jes

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The expansion of technology and computer science, as well as advancements in language instruction and learning methodologies, has enabled computer-assisted language learning technologies to tackle this challenge. In the field of Chinese learning, a few language learning computerized systems in the country and abroad concentrate mainly on language, grammar acquisition only have one or two assessment indicators as basis of evaluation, that definite functional flaws provide a general assessment to learners' pronunciation. In this manuscript, Language Dissemination Paths and Modes Aided by Computer Technology (LDPM-QICCNN-KOA) are proposed. The input data are collected from Chinese Corpus dataset. Then the data is given into unscented trainable kalman filter for preprocessing the input data. Then the preprocessed data are provided to QICCNN for Language Dissemination. In general, the based Quantum-inspired Complex Convolutional Neural Network doesn’t express adapting optimization approaches to determine optimal parameters to ensure exact identification. Hence, KOA utilized to enhance Quantum-inspired Complex Convolutional Neural Network, which accurately done the Language Dissemination Paths and Modes. The proposed LDPM-QICCNN-KOA method is executed on python. Then performance of proposed technique is analyzed with other existing methods. The proposed technique attains 26.36%, 20.69% and 35.29% higher accuracy; 19.23%, 23.56%, and 33.96% higher F1-Score; 26.28%, 31.26%, and 19.66% higher precision when comparing with the existing methods such as research on network oral English teaching system depend on machine learning (LDPM-DBN), nonlinear network speech recognition structure in deep learning algorithm (LDPM-DNN), research on open oral English scoring system depend on neural network (LDPM-BPNN).

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“…In an effort to enhance patient care and boost healthcare delivery efficiency, several healthcare institutions use electronic health records (EHRs) [1] on a large scale. In automating that data management process in challenging clinical settings, the EHR system speeds up clinician productivity [2] [3].…”

Section: Introductionmentioning

confidence: 99%

A Review on Privacy Preserving Using Machine learning and Deep Learning Techniques

Rajput¹,

Tiwari²

2023

IJRASET

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In order to entice data custodians to provide precise documentation so that data mining can continue with confidence, protecting the confidentiality of healthcare data is crucial. Association rule mining has been extensively used in the past to analyze healthcare data. The majority of applications ignore the drawbacks of specific diagnostic procedures in favor of positive association criteria. Negative association criteria may provide more useful information when bridging disparate diseases and medications than positive ones. In the case of doctors and social groups, this is particularly accurate. Data mining for medical purposes must be done with patient identities protected, especially when working with sensitive data. However, it might be attacked if this information becomes public. In order to perform data mining research, technology that modifies data (data sanitization) that reconstructs aggregate distributions has recently addressed the importance of healthcare data privacy. This study examines data sanitization in healthcare data mining using metaheuristics in order to safeguard patient privacy. Studies on SHM have looked at the uses of IoT &/or Machine Learning (ML) within the field, as well as the architecture, security, & privacy issues. However, no studies have looked into how AI and ubiquity computing technologies have affected SHM systems. The objective of this research is to identify and map the primary technical concepts within the SHM framework.

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Preserving the Privacy of Healthcare Data over Social Networks Using Machine Learning

Cited by 5 publications

References 36 publications

Cyber Attack - Envenom in Indian Healthcare – A Review

Cyber Attack - Envenom in Indian Healthcare – A Review

Language Dissemination Paths and Modes Aided by Computer Technology

A Review on Privacy Preserving Using Machine learning and Deep Learning Techniques

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