A Risk Assessment Framework Proposal Based on Bow-Tie Analysis for Medical Image Diagnosis Sharing within Telemedicine

被引:10
作者
Poleto, Thiago [1 ]
Silva, Maisa Mendonca [2 ]
Clemente, Tharcylla Rebecca Negreiros [3 ]
de Gusmao, Ana Paula Henriques [4 ]
Araujo, Ana Paula de Barros [2 ]
Costa, Ana Paula Cabral Seixas [2 ]
机构
[1] Fed Univ Para, Dept Business Adm, BR-66075110 Belem, Para, Brazil
[2] Univ Fed Pernambuco, Dept Engn Management, BR-50670901 Recife, PE, Brazil
[3] Univ Fed Pernambuco, Dept Management Engn CAA, BR-55002970 Caruaru, Brazil
[4] Univ Fed Sergipe, Dept Engn Management, BR-49100000 Sao Cristovao, Brazil
关键词
image and diagnosis medical security; bow-tie analysis; cyberattack; cybersecurity; decision-making;
D O I
10.3390/s21072426
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
The purpose of this paper is to propose a framework for cybersecurity risk management in telemedicine. The framework, which uses a bow-tie approach for medical image diagnosis sharing, allows the identification, analysis, and assessment of risks, considering the ISO/TS 13131:2014 recommendations. The bow-tie method combines fault tree analysis (FTA) and event tree analysis (ETA). The literature review supported the identification of the main causes and forms of control associated with cybersecurity risks in telemedicine. The main finding of this paper is that it is possible, through a structured model, to manage risks and avoid losses for everyone involved in the process of exchanging medical image information through telemedicine services. Through the framework, those responsible for the telemedicine services can identify potential risks in cybersecurity and act preventively, recognizing the causes even as, in a mitigating way, identifying viable controls and prioritizing investments. Despite the existence of many studies on cybersecurity, the paper provides theoretical contributions to studies on cybersecurity risks and features a new methodological approach, which incorporates both causes and consequences of the incident scenario.
引用
收藏
页数:19
相关论文
共 66 条
[1]  
AHMED Y, 2019, P 2019 13 INT S MED, P1
[2]   Selective medical image encryption using DNA cryptography [J].
Akkasaligar, Prema T. ;
Biradar, Sumangala .
INFORMATION SECURITY JOURNAL, 2020, 29 (02) :91-101
[3]   IoMT-SAF: Internet of Medical Things Security Assessment Framework [J].
Alsubaei, Faisal ;
Abuhussein, Abdullah ;
Shandilya, Vivek ;
Shiva, Sajjan .
INTERNET OF THINGS, 2019, 8
[4]   An improved DWT-SVD domain watermarking for medical information security [J].
Anand, Ashima ;
Singh, Amit Kumar .
COMPUTER COMMUNICATIONS, 2020, 152 :72-80
[5]   Gender difference and employees' cybersecurity behaviors [J].
Anwar, Mohd ;
He, Wu ;
Ash, Ivan ;
Yuan, Xiaohong ;
Li, Ling ;
Xu, Li .
COMPUTERS IN HUMAN BEHAVIOR, 2017, 69 :437-443
[6]   Integrating lean principles and fuzzy bow-tie analysis for risk assessment in chemical industry [J].
Aqlan, Faisal ;
Ali, Ebrahim Mustafa .
JOURNAL OF LOSS PREVENTION IN THE PROCESS INDUSTRIES, 2014, 29 :39-48
[7]   SVD-based robust image steganographic scheme using RIWT and DCT for secure transmission of medical images [J].
Arunkumar, S. ;
Subramaniyaswamy, V ;
Vijayakumar, V. ;
Chilamkurti, Naveen ;
Logesh, R. .
MEASUREMENT, 2019, 139 :426-437
[8]   A new digital image tamper detection algorithm based on integer wavelet transform and secured by encrypted authentication sequence with 3D quantum map [J].
Barani, Milad Jafari ;
Valandar, Milad Yousefi ;
Ayubi, Peyman .
OPTIK, 2019, 187 :205-222
[9]   Recognition of Alzheimer's disease and Mild Cognitive Impairment with multimodal image-derived biomarkers and Multiple Kernel Learning [J].
Ben Ahmed, Olfa ;
Benois-Pineau, Jenny ;
Allard, Michelle ;
Catheline, Gwenaelle ;
Ben Amar, Chokri .
NEUROCOMPUTING, 2017, 220 :98-110
[10]   Cybersecurity education: Evolution of the discipline and analysis of master programs [J].
Cabaj, Krzysztof ;
Domingos, Duke ;
Kotulski, Zbigniew ;
Respicio, Ana .
COMPUTERS & SECURITY, 2018, 75 :24-35