Skip to main content

A new enhanced cyber security framework for medical cyber physical systems

SICS Software-Intensive Cyber-Physical Systems volume 35, pages 159–183 (2021)Cite this article

Abstract

Medical Cyber-Physical Systems (MCPS) are complex, location-aware, networked systems of medical devices that can be used as a piece of the healing center to give the best medical care to patients. Hence, they integrate human, cyber, and physical elements. Since MCPSs are life-critical and context-aware, they are significant to the healthcare industry, which is prone to data breaches and cyber-attacks. As an emerging research area, MCPS faces several challenges with respect to system reliability, assurance, autonomy and security, and privacy. In this paper, we initially examine the state-of-the-arts of MCPS over the last few decades (1998–2020) and subsequently propose a new framework considering security/privacy for MPCS that incorporates several models that depict various domains of security. An interaction between various models followed with a qualitative assessment of the framework has been carried out to present a detailed description of the proposed framework. It is useful in various healthcare industries like health care services, manufacturing, pharmaceuticals, etc. that utilize smart devices. Additionally, the framework may be applied to enhance security in the Internet of Things (IoT) environment. It may be also useful to deploy efficient workflow operations for patients under the consideration framework. The framework will also lay out the foundation for implementing cybersecurity infrastructures in many healthcare applications.

This is a preview of subscription content, access via your institution.

Access options

Buy single article

Instant access to the full article PDF.

USD 39.95

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

References

  1. Lee I, Sokolsky O (2010) Medical cyber physical systems. In: Design automation conference (DAC) 2010, 743–748.

  2. Lee I, Sokolsky O, Chen S, Hatcliff J, Jee E, Kim B, Venkatasubramanian KK (2012) Challenges and research directions in medical cyber–physical systems. In: Proceedings of the IEEE 100(1):75–90.

  3. Norman G (2016) Drugs and devices: comparison of European and U.S. Approval Processes. JACC 1(5): 399–412. https://doi.org/10.1016/j.jacbts.2016.06.003.

  4. Dey N, Ashour AS, Shi F, Fong SJ, Tavares JMR (2018) Medical cyber-physical systems: a survey. J Med Syst 42(4):74

    Article  Google Scholar 

  5. Haque SA, Aziz SM, Rahman M (2014) Review of cyber-physical system in healthcare. Int J Distrib Sens Netw 10(4):217–415

    Article  Google Scholar 

  6. Williams PA, Woodward AJ (2015) Cybersecurity vulnerabilities in medical devices: a complex environment and multifaceted problem. Med Devices (Auckland, NZ) 9:305

    Google Scholar 

  7. Baheti R, Gill H Cyber physical systems. In: IEEE Control Systems Society 2011, 1–6. www.ieeecss.org.

  8. Denning T, Fu K, Kohno T (2008) Absence makes the heart grow fonder: new directions for implantable medical device security. In: HotSec 2008

  9. Ferguson N, Schneier B, Kohno T (2010) Cryptography engineering: design principles and practical applications. John Wiley & Sons 2010.

  10. Halperin D, Heydt-Benjamin TS, Fu K, Kohno T, Maisel WH (2008) Security and privacy for implantable medical devices. IEEE Pervasive Comput 7(1):29–39

    Article  Google Scholar 

  11. Lin C, Zeadally S, Chen T, Chang C (2012) Enabling cyber physical systems with wireless sensor networking technologies. Int J Distributed Sensor Netw 1–21, https://doi.org/10.1155/2012/489794.

  12. Guerrero-Higueras ÁM, DeCastro-García N, Rodríguez-Lera FJ, Matellán V (2017) Empirical analysis of cyber-attacks to an indoor real time localization system for autonomous robots. Comput Security 70:422–435

    Article  Google Scholar 

  13. Mazoit JX, Butscher K, Samii K (2007) Morphine in postoperative patients: pharmacokinetics and pharmacodynamics of metabolites. Anesth Analg 105(7):70–78

    Article  Google Scholar 

  14. Hicks RW, Sikirica V, Nelson W, Schein JR, Cousins DD (2008) Medication errors involving patient-controlled analgesia. Am J Health Syst Pharm 65(5):429–440

    Article  Google Scholar 

  15. Happ MB (1998) Treatment interference in acutely and critically ill adults. Am J Crit Care 7(3):224

    Article  Google Scholar 

  16. Jin Z, Oresko J, Huang S, Cheng AC (2009) HeartToGo: a personalized medicine technology for cardiovascular disease prevention and detection. In: Life science systems and applications workshop, 2009. LiSSA 2009. IEEE/NIH, 80–8

  17. Sung M, Marci C, Pentland A (2005) Wearable feedback systems for rehabilitation. J Neuroeng Rehabil 2(1):17

    Article  Google Scholar 

  18. Di Rienzo M, Rizzo F, Parati G, Brambilla G, Ferratini M, Castiglioni P (2005) MagIC system: a new textile-based wearable device for biological signal monitoring. applicability in daily life and clinical setting. In: Engineering in medicine and biology society, 2005. IEEE-EMBS 2005. 27th Annual International Conference, 7167–7169.

  19. Wood A, Virone G, Doan T, Cao Q, Selavo L, Wu Y, Stankovic J (2006) ALARM-NET: wireless sensor networks for assisted-living and residential monitoring. Univ Virginia Comput Sci Dept Tech Rep 2:17

    Google Scholar 

  20. Mundt CW, Montgomery KN, Udoh UE, Barker VN, Thonier GC, Tellier AM, Ruoss SJ (2005) A multiparameter wearable physiologic monitoring system for space and terrestrial applications. IEEE Trans Inf Technol Biomed 9(3):382–391

    Article  Google Scholar 

  21. Hughes J, Cybenko G (2014) Three tenets for secure cyber-physical system design and assessment. Cyber Sens Int Soc Opt Photonics 9(7):909–970

    Google Scholar 

  22. Penna R, Amaral M, Espíndola D, Botelho S, Duarte N, Pereira CE, Frazzon EM (2014) Visualization tool for cyber-physical maintenance systems. In: Industrial informatics (INDIN), 2014 12th IEEE international conference, July IEEE, 566–571.

  23. Larson BR et al. (2013) Open patient-controlled analgesia infusion pump system requirements. Int Workshop Softw Eng Health Care 28–34 https://doi.org/10.1109/SEHC.2013.6602474.

  24. Hahanov V, Gharibi W, Kudin AP, Hahanov I, Cristopher N, Yeve T, Priymak A (2014) Cyber physical social systems-future of Ukraine. In Design & Test Symposium (EWDTS) September, IEEE, 1–15.

  25. Zhang L (2014) Designing big data driven cyber physical systems based on AADL. In: Systems, man and cybernetics (SMC), 2014 IEEE international conference, October, 3072–3077.

  26. O’Keeffe DT, Maraka S, Basu A, Keith-Hynes P, Kudva YC (2015) Cybersecurity in artificial pancreas experiments. Diabetes Technol Ther 17(9):664–666

    Article  Google Scholar 

  27. Ray A, Cleaveland R (2015) Security assurance cases for medical cyber-physical systems. IEEE Design Test 32(5):56–65

    Article  Google Scholar 

  28. Sabău-Popa D, Bradea I, Boloș M, Delcea C (2015) The information confidentiality and cybersecurity in medical institutions. The Annals of the University of Oradea, 855.

  29. Ivanov R, Weimer J, Lee I (2018) Context-aware detection in medical cyber-physical systems. In: Proceedings of the 9th ACM/IEEE international conference on cyber-physical systems, April, IEEE Press, 232–241.

  30. Dogaru DI, Dumitrache I (2015) Cyber-physical systems in healthcare networks. In: E-health and bioengineering conference (EHB), November, IEEE, 1–4.

  31. Reddy YB (2015) Security and design challenges in cyber-physical systems. In: Information technology-new generations (ITNG), 2015 12th international conference, April, IEEE, 200–205.

  32. Quadri I, Bagnato A, Brosse E, Sadovykh A (2015) Modeling methodologies for cyber-physical systems: research field study on inherent and future challenges. ADA USER 36(4):246

    Google Scholar 

  33. Kanjee MR, Liu H (2016) Authentication and key relay in medical cyber-physical systems. Security Commun Netw 9(9):874–885

    Article  Google Scholar 

  34. Chen S, Sokolsky O, Weimer J, Lee I (2016) Data-driven adaptive safety monitoring using virtual subjects in medical cyber-physical systems: a glucose control case study. J Comput Sci Eng 10(3):75

    Article  Google Scholar 

  35. Majhi SK, Patra G, Dhal SK (2016) Cyber physical systems & public utility in India: state of art. Proc Comput Sci 78:777–781

    Article  Google Scholar 

  36. Kruse CS, Frederick B, Jacobson T, Monticone DK (2017) Cybersecurity in healthcare: a systematic review of modern threats and trends. Technol Health Care 25(1):1–10

    Article  Google Scholar 

  37. Meng W, Li W, Xiang Y, Choo KKR (2017) A Bayesian inference-based detection mechanism to defend medical smartphone networks against insider attacks. J Netw Comput Appl 78:162–169

    Article  Google Scholar 

  38. Bricon-Souf N, Newman C (2007) Context awareness in health care: a review. Int J Med Inform 76(1):2–12

    Article  Google Scholar 

  39. Gu L, Zeng D, Guo S, Barnawi A, Xiang Y (2017) Cost efficient resource management in fog computing supported medical cyber-physical system. IEEE Trans Emerging Topics Comput 5(1):108–119

    Article  Google Scholar 

  40. García-Valls M, Herrasti N, Jouvray C, Armentia A (2017) Flexible and timely on-line integration of medical services using iLand middleware. ACM Sigbed Rev 14(2):53–60

    Article  Google Scholar 

  41. Pawlick J, Zhu Q (2017) Strategic trust in cloud-enabled cyber-physical systems with an application to glucose control. IEEE Trans Inf Forensics Secur 12(12):2906–2919

    Article  Google Scholar 

  42. Cecil J (2017) Internet of things (IoT)‐based cyber–physical frameworks for advanced manufacturing and medicine. Internet of Things and Data Analytics Handbook, 545–561.

  43. Nithya S, Sangeetha M, Prethi KA (2018) Role of cyber physical systems in health care and survey on security of medical data. Int J Pharma Res Health Sci 6(1):75–80

    Google Scholar 

  44. Nissim N, Mahler T, Shalom E, Goldenberg I, Hasman G, Makori A, Shahar Y (2018) Know your enemy: characteristics of cyber-attacks on medical imaging devices arXiv preprint arXiv: 1801.05583.

  45. Croasdell D, Elste J, Hill A (2018) Cyber clinics: re-imagining cybersecurity awareness. In: Proceedings of the 51st Hawaii international conference on system sciences, 4283–4288.

  46. Li GC, Chen CL, Chen HC, Lin F, Gu C (2018) Design of a secure and effective medical cyber-physical system for ubiquitous telemonitoring pregnancy. Concurrency Comput 30(2):52–61

    Google Scholar 

  47. Malathi S, Priadarsini M, Dharshana M, Agathiya T (2018) Big data and CPS (Cyber Physical System) used in pharmacy to alert on expiration of medicine. Int J Eng Sci, 16946.

  48. Ivanov R, Weimer J, Simpao A, Rehman M, Lee I (2015) Early detection of critical pulmonary shunts in infants. In: Proceedings of the ACM/IEEE sixth international conference on cyber-physical systems, April, ACM, 110–119.

  49. Rushanan M, Rubin AD, Kune DF, Swanson CM (2014) SoK: security and privacy in implantable medical devices and body area networks. In: Security and privacy (SP), 2014 IEEE symposium IEEE. 524–539.

  50. Gunes V, Peter S, Givargis T, Vahid F (2014) A survey on concepts, applications, and challenges in cyber-physical systems. KSII Trans Internet Inform Syst 8(12):4242–4268

    Google Scholar 

  51. Finnegan A, McCaffery F (2014) A security argument pattern for medical device assurance cases. In: Software reliability engineering workshops (ISSREW), 2014 IEEE international symposium, IEEE, pp 220–225.

  52. Sametinger J, Rozenblit J, Lysecky R, Ott P (2015) Security challenges for medical devices. Commun ACM 58(4):74–82

    Article  Google Scholar 

  53. AlTawy R, Youssef AM (2016) Security tradeoffs in cyber physical systems: a case study survey on implantable medical devices. IEEE Access 4:959–979

    Article  Google Scholar 

  54. Mashkoor A, Sametinger J (2016) Rigorous modeling and analysis of interoperable medical devices. In: Proceedings of the modeling and simulation in medicine symposium, society for computer simulation international, 5.

  55. Kocabas O, Soyata T, Aktas MK (2016) Emerging security mechanisms for medical cyber physical systems. IEEE/ACM Trans Comput Biol Bioinf 13(3):401–416

    Article  Google Scholar 

  56. Mackey TK, Nayyar G (2016) Digital danger: a review of the global public health, patient safety and cybersecurity threats posed by illicit online pharmacies. Br Med Bull 118(1):110–126

    Article  Google Scholar 

  57. He H, Maple C, Watson T, Tiwari A, Mehnen J, Jin Y, Gabrys B (2016) The security challenges in the IoT enabled cyber-physical systems and opportunities for evolutionary computing & other computational intelligence. In: Evolutionary computation (CEC), 2016 IEEE congress IEEE, 1015–1021.

  58. Carroll N, Richardson I (2016) Software-as-a-medical device: demystifying connected health regulations. J Syst Inform Technol 18(2):186–215

    Google Scholar 

  59. Mohan A (2014) Cybersecurity for personal medical devices internet of things. In: Distributed computing in sensor systems (DCOSS), 2014 IEEE international conference, IEEE, 372–374.

  60. Arney D, Plourde J, Schrenker R, Mattegunta P, Whitehead SF, Goldman JM (2014) Design pillars for medical cyber-physical system middleware. In: OASIcs-OpenAccess Series in Informatics, SchlossDagstuhl-Leibniz-ZentrumfuerInformatik, 36:124–132.

  61. Adyanthaya S, Ara HA, Bastos J, Behrouzian A, Sánchez RM, Van Pinxten J, Frijns R (2017) xCPS: a tool to explore cyber physical systems. ACM SIGBED Rev 14(1):81–95

    Article  Google Scholar 

  62. Arney D, Venkatasubramanian KK, Sokolsky O, Lee I (2011) Biomedical devices and systems security. In: Engineering in medicine and biology society, EMBC, 2011 annual international conference of the IEEE, August, IEEE, 2376–2379.

  63. Burns AJ, Johnson ME, Honeyman P (2016) A brief chronology of medical device security. Commun ACM 59(10):66–72

    Article  Google Scholar 

  64. Celdrán AH, Pérez G, Clemente FJG, Pérez GM (2018) Sustainable securing of medical cyber-physical systems for the healthcare of the future. Sustain Comput 19:138–146

    Google Scholar 

  65. Grispos G, Glisson WB, Choo KKR (2017) Medical cyber-physical systems development: a forensics-driven approach. In: Connected health: applications, systems and engineering technologies (CHASE), 2017 IEEE/ACM international conference IEEE, 108–113.

  66. Heartfield R, Loukas G, Budimir S, Bezemskij A, Fontaine JR, Filippoupolitis A, Roesch E (2018) A taxonomy of cyber-physical threats and impact in the smart home. Comput Security 78:398–428

    Article  Google Scholar 

  67. Li W, Meng W, Su C, Kwok LF (2018) Towards false alarm reduction using fuzzy if-then rules for medical cyber physical systems. IEEE Access 6:6530–6539

    Article  Google Scholar 

  68. Lyapustina S, Armstrong K (2018) Regulatory considerations for cybersecurity and data privacy in digital health and medical applications and products. CSC Publishing, 1–8.

  69. Mahler T et al. (2018) Know your enemy: characteristics of cyber-attacks on medical imaging devices. Cornell University Library 2018, 1–6.

  70. Hanacek N (2018) NIST cybersecurity framework. https://www.nist.gov/cyberframework

  71. Zheng G et al (2017) Ideas and challenges for securing wireless implantable medical devices: a review. IEEE Sens J 17(3):562–576

    Article  Google Scholar 

  72. Tyagi A (2016) Cyber physical systems (CPSs)—opportunities and challenges for improving cyber security. Int J Comput Appl 137(14):19–27

    Google Scholar 

  73. Jahanian F (2011) The growing imperative and transformative impact of cyber-physical systems. Natl Sci Foundation, 1–53.

  74. Wang E et.al. (2010) Security issues and challenges for cyber physical system. In: 2010 International conference on green computing and communications physical and social computing, IEEE/ACM, 733–738.

  75. Ofori A, Abdulai J, Katsriku F (2018) Cybercrime and risks for cyber physical systems: a review 1–26, https://doi.org/10.20944/preprints201804.0066.v1.

  76. Corpuz M (2010) Limitations of the information security management system assessment approaches in the context of information security policy assessment. Information Security Institute, Queensland University of Technology, 1–3

  77. Haufe K, Palacios R, Dzombeta S, Brandis K, Stantchev V (2016) A process framework for information security management. Int J Inform Syst Project Manag, 27–47.

  78. Copeland JB Implementing NIST CSF? read this first Retrieved June 19, 2017, from https://www.fairinstitute.org/blog/implementing-nist-csf-read-this-first.

  79. Hoyme K, Abrahamson S, Englert P (2017) Medical device risk management and assessment methods. Healthcare Information and Management Systems Society (HIMSS), 1–56.

  80. Bradley M (2018) Five typical cyber attack techniques used against business travelers, Retrieved July 23, 2018, From https://www.securitymagazine.com/articles/89255-five-typical-cyber-attack-techniques-used-against-business-travelers

  81. Ashford W (2019) Orangeworm cyber attack group targets health sector, Retrieved Jan 2019, From https://www.computerweekly.com/news/252439782/Orangeworm-cyber-attack-group-targeting-health-sector

  82. Bezemskij A, Loukas G, Anthony RJ, Gan D (2016) Behaviour-based anomaly detection of cyber-physical attacks on a robotic vehicle. In: 2016 15th international conference on ubiquitous computing and communications and 2016 international symposium on cyberspace and security (IUCC-CSS), 61–68.

  83. Priyadarshini I (2017) Cybersecurity risks in robotics, detecting and mitigating robotic cyber security risks. IGI Global

  84. Kruegel C, Vigna G (2003) Anomaly detection of web-based attacks. In: Proceedings of the 10th ACM conference on computer and communications security ACM, 251–261.

  85. Goud N (2019) Healthcare alert- Medical devices are more prone to cyber attacks, Retrieved Jan 24, 2019, From https://www.cybersecurity-insiders.com/healthcare-alert-medical-devices-are-more-prone-to-cyber-attacks/

  86. Palmer D (2018) What is ransomware? Everything you need to know about one of the biggest menaces on the web, Retrieved August 22, 2018, From https://Www.Zdnet.Com/Article/Ransomware-An-Executive-Guide-To-One-Of-The-Biggest-Menaces-On-The-Web/

  87. Voss S (2018) Could you recover from a destructive cyber-attack?—Dell Technologies. Retrieved July 30, 2018, from https://www.delltechnologies.com/en-us/perspectives/could-you-recover-from-a-destructive-cyber-attack

  88. Fisher N (2018) 5 identity attacks that exploit your broken authentication, Retrieved March 14, 2018, from https://www.okta.com/security-blog/2018/03/5-identity-attacks-that-exploit-your-broken-authentication/

  89. McConnachie L (2018) 10 cyber security threats in 2017 that you can't just ignore [How Vulnerable Are You?]”, Retrieved August 27, 2018, from https://purplegriffon.com/blog/10-cyber-security-threats-in-2017.

  90. NeSmith B (2018) Avoid These Top Five Cyberattacks, Retrieved May 4, 2018, from https://www.forbes.com/sites/forbestechcouncil/2018/05/04/avoid-these-top-five-cyberattacks/#21265d6c7cc9

  91. Ashibani Y, Mahmoud QH (2017) Cyber physical systems security: analysis, challenges and solutions. Comput Security 68:81–97

    Article  Google Scholar 

  92. Ali M, Son LH, Khan M, Tung NT (2018) Segmentation of dental X-ray images in medical imaging using neutrosophic orthogonal matrices. Expert Syst Appl 91:434–441

    Article  Google Scholar 

  93. Ali M, Son LH, Thanh ND, Van Minh N (2018) A neutrosophic recommender system for medical diagnosis based on algebraic neutrosophic measures. Appl Soft Comput 71:1054–1071

    Article  Google Scholar 

  94. Anand M, Cronin E, Sherr M, Blaze M, Ives Z, Lee I (2006) Security challenges in next generation cyber physical systems. Beyond SCADA: Networked Embedded Control for Cyber Physical Systems. 41

  95. Haque SA, Aziz SM, Rahman M (2014) Review of cyber-physical system in healthcare. Int J Distrib Sens Netw 10(4):217415

    Article  Google Scholar 

  96. Hemanth DJ, Anitha J, Son LH, Mittal M (2018) Diabetic retinopathy diagnosis from retinal images using modified hopfield neural network. J Med Syst 42(12):247

    Article  Google Scholar 

  97. Jersey C (2016) ThreatModeler redefines threat modeling by allowing non-security experts to build threat models in minutes, Retrieved July 13, 2016, from https://www.prweb.com/releases/2016/07/prweb13546377.htm.

  98. Lee I, Sokolsky O (2010) Medical cyber physical systems. In: Design automation conference (DAC), 2010 47th ACM/IEEE, IEEE, 743–748.

  99. Lee I et al (2012) Challenges and research directions in medical cyber–physical systems. Proc IEEE 100(1):75–90

    Article  Google Scholar 

  100. Meyer D, Haase J, Eckert M, Klauer B (2016) A threat-model for building and home automation. In: IEEE 14th international conference on industrial informatics (INDIN), 860–866. https://doi.org/10.1109/INDIN.2016.7819280.

  101. Ngan RT, Ali M, Son LH (2018) δ-equality of intuitionistic fuzzy sets: a new proximity measure and applications in medical diagnosis. Appl Intell 48(2):499–525

    Article  Google Scholar 

  102. Ngan RT, Cuong BC, Tuan TM, Son LH (2018) Medical diagnosis from images with intuitionistic fuzzy distance measures. In: International joint conference on rough sets 2018, Springer, Cham, 479–490.

  103. Ngan TT, Tuan TM, Son LH, Minh NH, Dey N (2016) Decision making based on fuzzy aggregation operators for medical diagnosis from dental X-ray images. J Med Syst 40(12):280

    Article  Google Scholar 

  104. Son LH, Phong PH (2016) On the performance evaluation of intuitionistic vector similarity measures for medical diagnosis. J Intell Fuzzy Syst 31(3):1597–1608

    Article  MATH  Google Scholar 

  105. Son LH, Tuan TM, Fujita H, Dey N, Ashour AS, Ngoc VTN, Chu DT (2018) Dental diagnosis from X-ray images: an expert system based on fuzzy computing. Biomed Signal Process Control 39:64–73

    Article  Google Scholar 

  106. Son LH, Thong NT (2015) Intuitionistic fuzzy recommender systems: an effective tool for medical diagnosis. Knowl-Based Syst 74:133–150

    Article  Google Scholar 

  107. Son LH, Tuan TM (2016) A cooperative semi-supervised fuzzy clustering framework for dental X-ray image segmentation. Expert Syst Appl 46:380–393

    Article  Google Scholar 

  108. Son LH, Tuan TM (2017) Dental segmentation from X-ray images using semi-supervised fuzzy clustering with spatial constraints. Eng Appl Artif Intell 59:186–195

    Article  Google Scholar 

  109. Stevens M (2017) Cybersecurity risk: a thorough definition, Retrieved January 10, 2017, from https://www.bitsighttech.com/blog/cybersecurity-risk-thorough-definition.

  110. Thanh ND, Ali M, Son LH (2017) A novel clustering algorithm in a neutrosophic recommender system for medical diagnosis. Cognit Comput 9(4):526–544

    Article  Google Scholar 

  111. Thanh ND, Son LH, Ali M (2017) Neutrosophic recommender system for medical diagnosis based on algebraic similarity measure and clustering. In: Fuzzy systems (FUZZ-IEEE), 2017 IEEE international conference July, IEEE, 1–6.

  112. The European Union Agency for Network and Information Security (ENISA), Risk Management, ISMS Cybersecurity Framework, Retrieved November 20, 2009, from https://www.enisa.europa.eu/topics/threat-risk-management/risk-management/current-risk/risk-management-inventory/rm-isms/framework.

  113. Thong NT, Son LH (2015) HIFCF: An effective hybrid model between picture fuzzy clustering and intuitionistic fuzzy recommender systems for medical diagnosis. Expert Syst Appl 42(7):3682–3701

    Article  Google Scholar 

  114. Tuan TM, Ngan TT, Son LH (2016) A novel semi-supervised fuzzy clustering method based on interactive fuzzy satisficing for dental X-ray image segmentation. Appl Intell 45(2):402–428

    Article  Google Scholar 

  115. Tuan TM, Duc NT, Van Hai P, Son LH (2017) Dental diagnosis from X-Ray images using fuzzy rule-based systems. Int J Fuzzy Syst Appl (IJFSA) 6(1):1–16

    Google Scholar 

  116. Thanh ND, Ali M, Son LH (2017) A novel clustering algorithm in a neutrosophic recommender system for medical diagnosis. Cogn Comput 9:526–544

    Article  Google Scholar 

  117. Venkatasubramanian KK, Gupta SKS, Jetley RP, Jones PL (2010) Interoperable medical devices. IEEE Pulse 1(2):16–27

    Article  Google Scholar 

  118. Doss S, Nayyar A, Suseendran G, Tanwar S, Khanna A, Thong PH (2018) APD-JFAD: accurate prevention and detection of jelly fish attack in MANET. IEEE Access 6:56954–56965

    Article  Google Scholar 

  119. Gonzalez E, Pena R, Avila A, Rosales C, Rodrigues D (2017) A systematic review on recent advances in health systems: deployment architecture for emergency response. J Healthcare Eng 20(17):13–21

    Google Scholar 

  120. Fink G, Edgar T, Rice T, MacDonald D, Crawford C (2017) Security and privacy in cyber-physical systems, Foundations, Principles and Applications Intelligent Data-Centric Systems, 129–141.

  121. Su L, Ye D (2018) A cooperative detection and compensation mechanism against denial-of-service attack for cyber-physical systems. Inf Sci 444:122–134

    Article  MathSciNet  Google Scholar 

  122. Lee I, Sokolsky O, Chen S, Hatcliff J, Jee E (2012) Challenges and research directions in medical cyber-physical systems, 2012. Proc IEEE 100(1):75–90

    Article  Google Scholar 

  123. Priyadarshini I, Cotton C (2018) Features and architecture of modern cyber range: a qualitative analysis and survey, University of Delaware.

  124. Priyadarshini I, Cotton C (2019) Some cyber psychological techniques to distinguish human and robot authentication. Advances in Intelligent Systems, Springer.

  125. Ramapantulu L, Teo YM, Chang EC (2017). A conceptural framework to federate testbeds for cybersecurity. In: 2017 winter simulation conference (WSC) (pp 457–468). IEEE.

  126. Shen L (2014) The NIST cybersecurity framework: overview and potential impacts. Scitech Lawyer 10(4):16

    Google Scholar 

  127. Gonzalez CP, Hunting B, Burgess J, Jensen LH CIS critical security controls.

  128. Powell C, Hauck K, Sanghvi AD, Hasandka A, Van Natta J, Reynolds TL (2019). Guide to the distributed energy resources cybersecurity framework (No. NREL/TP-5R00–75044). National Renewable Energy Lab (NREL), Golden, CO (United States).

  129. Ilhan I, Karaköse M (2019) Cybersecurity framework for requirements of repair, update, and renovation in industry 4.0. In: 2019 1st international informatics and software engineering conference (UBMYK) (pp 1–4). IEEE.

  130. Min D (2013) Medical cyber physical systems and bigdata platforms.

  131. Qiu H, Qiu M, Liu M, Memmi G (2019) Privacy-preserving health data sharing for medical cyber-physical systems. arXiv preprint arXiv: 1904.08270.

  132. Jimenez JI, Jahankhani H, Kendzierskyj S (2020) Health care in the cyberspace: medical cyber-physical system and digital twin challenges. In: Digital twin technologies and smart cities (pp 79–92). Springer, Cham.

  133. Haidegger T, Virk GS, Herman C, Bostelman R, Galambos P, Györök G, Rudas IJ (2020) Industrial and medical cyber-physical systems: Tackling user requirements and challenges in robotics. In: Recent advances in intelligent engineering (pp 253–277). Springer, Cham.

  134. Shishvan OR, Zois DS, Soyata T (2020) Incorporating artificial intelligence into medical cyber physical systems: a survey. In: Connected Health in Smart Cities (pp 153–178). Springer, Cham.

  135. Zhao S, Rengasamy PV, Zhang H, Bhuyan S, Nachiappan NC, Sivasubramaniam A, ... Das C (2019). Understanding energy efficiency in iot app executions. In: 2019 IEEE 39th international conference on distributed computing systems (ICDCS) (pp 742–755). IEEE.

  136. Martín-Lopo MM, Boal J, Sánchez-Miralles Á (2020) A literature review of iot energy platforms aimed at end users. Computer Networks, 107101.

  137. Ueki M, Takeuchi K, Yamamoto T, Tanabe A, Ikarashi N, Saitoh M, ... Masuzaki K (2015) Low-power embedded ReRAM technology for IoT applications. In: 2015 symposium on VLSI technology (VLSI Technology) (pp T108–T109). IEEE.

  138. Mohammad K, Tekeste T, Mohammad B, Saleh H, Qurran M (2019) Embedded memory options for ultra-low power IoT devices. Microelectron J 93:104634

    Article  Google Scholar 

  139. Zali Z, Hashemi MR, Saidi H (2012) Real-time attack scenario detection via intrusion detection alert correlation. In: 2012 9th international ISC conference on information security and cryptology (pp 95–102). IEEE.

  140. Clotet X, Moyano J, León G (2018) A real-time anomaly-based ids for cyber-attack detection at the industrial process level of critical infrastructures. Int J Crit Infrastruct Prot 23:11–20

    Article  Google Scholar 

  141. Irwin, L. (2019, December 17). How long does it take to detect a cyber attack? Retrieved from https://www.itgovernanceusa.com/blog/how-long-does-it-take-to-detect-a-cyber-attack

Download references

Funding

This research has no funding source.

Author information

Authors and Affiliations

  1. University of Delaware, Newark, DE, USA

    Ishaani Priyadarshini

  2. Department of Computer Science and Engineering, GIET University, Gunupur, India

    Raghvendra Kumar

  3. Hanoi University of Home Affairs, Hanoi, Vietnam

    Le Minh Tuan

  4. VNU Information Technology Institute, Vietnam National University, Hanoi, Vietnam

    Le Minh Tuan & Le Hoang Son

  5. Division of Computational Mathematics and Engineering, Institute for Computational Science, Ton Duc Thang University, Ho Chi Minh City, Vietnam

    Hoang Viet Long

  6. Faculty of Mathematics and Statistics, Ton Duc Thang University, Ho Chi Minh City, Vietnam

    Hoang Viet Long

  7. Department of Electronics & Communication Engineering, Faculty of Engineering and Technology, SRM Institute of Science and Technology, NCR Campus, Delhi - NCR Campus,Delhi - Meerut Road, Modinagar, Ghaziabad, UP, India

    Rohit Sharma

  8. Department of Computer Science and Engineering, LNCT University, Bhopal, MP, India

    Sakshi Rai

Authors
  1. Ishaani Priyadarshini
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Raghvendra Kumar
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Le Minh Tuan
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Le Hoang Son
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Hoang Viet Long
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Rohit Sharma
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Sakshi Rai
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hoang Viet Long.

Ethics declarations

Conflict of interest

Authors declare that there is no conflict of interest about the research.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 9 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Priyadarshini, I., Kumar, R., Tuan, L.M. et al. A new enhanced cyber security framework for medical cyber physical systems. SICS Softw.-Inensiv. Cyber-Phys. Syst. 35, 159–183 (2021). https://doi.org/10.1007/s00450-021-00427-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00450-021-00427-3

Keywords

  • Medical cyber-physical systems
  • Cyber security
  • Medical control systems
  • Security and privacy issues
  • Smart health