LinkedIn

 آمار

تعداد نشریات20
تعداد شماره‌ها1,149
تعداد مقالات10,518
تعداد مشاهده مقاله45,416,124
تعداد دریافت فایل اصل مقاله11,291,838
Rabeifar, Fatemeh, Radfar, Reza, Toloie Eshlaghy, Abbas. (1400). Security in Telemedicine based IoT. سامانه مدیریت نشریات علمی, 8(3), 200-209. doi: 10.30476/jhmi.2022.92061.1091
Fatemeh Rabeifar; Reza Radfar; Abbas Toloie Eshlaghy. "Security in Telemedicine based IoT". سامانه مدیریت نشریات علمی, 8, 3, 1400, 200-209. doi: 10.30476/jhmi.2022.92061.1091
Rabeifar, Fatemeh, Radfar, Reza, Toloie Eshlaghy, Abbas. (1400). 'Security in Telemedicine based IoT', سامانه مدیریت نشریات علمی, 8(3), pp. 200-209. doi: 10.30476/jhmi.2022.92061.1091
Rabeifar, Fatemeh, Radfar, Reza, Toloie Eshlaghy, Abbas. Security in Telemedicine based IoT. سامانه مدیریت نشریات علمی, 1400; 8(3): 200-209. doi: 10.30476/jhmi.2022.92061.1091

Security in Telemedicine based IoT

Health Management & Information Science
مقاله 7، دوره 8، شماره 3، مهر 2021، صفحه 200-209    اصل مقاله (912.12 K)
نوع مقاله: Original Article
شناسه دیجیتال (DOI): 10.30476/jhmi.2022.92061.1091
نویسندگان
Fatemeh Rabeifar1؛ Reza Radfar* 2؛ Abbas Toloie Eshlaghy3
1Ph.D candidate, Department of Information Technology Management, Science and Research Branch, Islamic Azad University, Tehran, Iran.
2Professor, Department of Technology Management, Science and Research Branch, Islamic Azad University, Tehran, Iran.
3Professor, Department of Information Technology Management, Science and Research Branch, Islamic Azad University, Tehran, Iran.
چکیده
Introduction: Internet of Things is an extensive network of interconnected objects across the world, in which each thing has a unique address. IoT is considered as the future innovation in the field of wireless technologies, which would be used in certain areas such as healthcare services, medical operations, etc. Hence, security requirements are very essential in these technologies. This study aims at finding the most effective model of IoT to improve Security for managing telemedicine. Following its widespread applicability, security have attracted a lot of attention and also have brought about some new challenges over security, confidence, and privacy areas.
Methods: In this study, previous literature on how to improve the security in various layers of IoT protocol and resistance against the certain attacks in any layer for the telemedicine have been considered. Relying on previous studies made on the field of research, The Recommended Architecture of IoT for Telemedicine is the three-layer : perception, network, and application.
Results: Data Security along with how data are received completely in receivers with a minimum delay, which can influence the network, is a vital challenge one may find in telemedicine. The recommended method was RPL protocol in which telemedicine systems are used.
Conclusion: We need to pay more attention to the connection points employed to transfer data among all things, cloud and networks over the telemedicine and make them secure as much as possible.
 
 
کلیدواژه‌ها
Internet of Things؛ Medical Informatics؛ Mobile Health؛ Telehealth؛ Telemedicine؛ ز
مراجع
1. Tuckson RV, Edmunds M, Hodgkins ML. Telehealth. N Engl J Med. 2017;377(16):1585-92. doi: 10.1056/NEJMsr1503323.
2. Qureshi A, Shih E, Fan I, Carlisle J, Brezinski D, Kleinman M, et al. Improving patient care by unshackling telemedicine: adaptively aggregating wireless networks to facilitate continuous collaboration. AMIA Annu Symp Proc. 2010;2010:662-6.
3. Dhanvijay MM, Patil SC. Internet of Things: A survey of enabling technologies in healthcare and its applications. Computer Networks. 2019;153:113-31. doi: 10.1016/j.comnet.2019.03.006.
4. Johns ML. The CIO and IRM (information resources management) alliance: maneuvering for the competitive edge in hospital information management. Top Health Rec Manage.1990;11(1):1-7.
5. Friedman C, Wyatt J. Evaluation methods in medical informatics. New York: Springer; 1997.
6. Choi H, Park IH, Yoon HG, Lee HM. Wireless patient monitoring system for patients with nasal obstruction. Telemed J E Health. 2011;17(1):46-9. doi: 10.1089/tmj.2010.0105.
7. Shams R, KHAN FH, SALEEM F. Internet of things in telemedicine: a discussion regarding to several implementation. Journal of Information Communication Technologies and Robotic Applications. 2018:17-26.
8. Sheikh A, Ambhaikar A. Quality of Services Parameters for Architectural Patterns of IoT. Journal of Information Technology Management. 2021;13:36-53.
9. Qi J, Yang P, Min G, Amft O, Dong F, Xu L. Advanced internet of things for personalised healthcare systems: A survey. Pervasive and Mobile Computing. 2017;41:132-49. doi: 10.1016/j.pmcj.2017.06.018.
10. Wallgren L, Raza S, Voigt T. Routing attacks and countermeasures in the RPL-based internet of things. International Journal of Distributed Sensor Networks. 2013;9(8):794326. doi: 10.1155/2013/794326.
11. Hassanalieragh M, Page A, Soyata T, Sharma G, Aktas M, Mateos G, et al., editors. Health monitoring and management using Internetof-Things (IoT) sensing with cloud-based processing: Opportunities and challenges. June 27-July 2, 2015. New York: IEEE International Conference on Services Computing. doi: 10.1109/SCC.2015.47.
12. Alami H, Gagnon M-P, Fortin J-P. Telehealth in light of cloud computing: clinical, technological, regulatory and policy issues. Journal of the International Society for Telemedicine and eHealth. 2016;4:e5.

13. Lee JD, Yoon TS, Chung SH, Cha HS. Service-Oriented Security Framework for Remote Medical Services in the Internet of Things Environment. Healthc Inform Res. 2015;21(4):271-82. doi: 10.4258/hir.2015.21.4.271.
14. Masood I, Wang Y, Daud A, Aljohani NR, Dawood H. Towards smart healthcare: Patient data privacy and security in sensor-cloud infrastructure. Wireless Communications and Mobile Computing. 2018;2018. doi: 10.1155/2018/2143897.
15. Dubey H, Monteiro A, Mahler L, Akbar U, Sun Y, Yang Q, et al. FogCare: fog-assisted internet of things for smart telemedicine. Future Generation Computer Systems. 2016.
16. Patel KK, Patel SM. Internet of things-IOT: definition, characteristics, architecture, enabling technologies, application & future challenges. International journal of engineering science and computing. 2016;6(5):6122-31.
17. Aman MN, Sikdar B, Chua KC, Ali A. Low power data integrity in IoT systems. IEEE Internet of Things Journal. 2018;5(4):3102-13. doi: 10.1109/JIOT.2018.2833206.
18. Madakam S. Internet of things: smart things. International journal of future computer and communication. 2015;4(4):250. doi: 10.7763/IJFCC.2015.V4.395.
19. Collins K, Bowns I, Walters S. General practitioners’ perceptions of asynchronous telemedicine in a randomized controlled trial of teledermatology. J Telemed Telecare. 2004;10(2):94-8. doi: 10.1258/135763304773391530.
20. Abdelhak M. Health information: management of a strategic resource. 2nd Ed. Philadelphia: Saunders; 2001.
21. Salunke P, Nerkar R. IoT driven healthcare system for remote monitoring of patients. International journal for modern trends in science and technology. 2017;3(6):100-3.
22. IEEE Standard for Local and metropolitan area networks. Part 15.4. Low-Rate Wireless Personal Area Networks (LRWPANs 802.15 standard), 2011.
23. IEEE Standard for Local and metropolitan area networks. Part 15.4. Low-Rate Wireless Personal Area Networks (LR-WPANs 802.15.4e standard);2012.
24. Akyildiz IF, Su W, Sankarasubramaniam Y, Cayirci E. Wireless sensor networks: a survey. Computer networks. 2002;38(4):393-422. doi: 10.1016/S1389-1286(01)00302-4.

25. Carmo JP, Dias NS, Silva HR, Mendes PM, Couto C, Correia JH. A 2.4-GHz lowpower/low-voltage wireless plug-and-play module for EEG applications. IEEE Sensors Journal. 2007;7(11):1524-31. doi: 10.1109/JSEN.2007.908238.
26. Hu YC, Wang HJ. Location Privacy in Wireless Networks. Hong Kong: ACM SIGCOMM Asia Workshop; 2015. p. 1-5.
27. Adjie-Winoto W, Schwartz E, Balakrishnan H, Lilley J, editors. The design and implementation of an intentional naming system. New York: Proceedings of the seventeenth ACM symposium on Operating systems principles; 1999. p. 186-201. doi: 10.1145/319344.319164.
28. Seskar I, Nagaraja K, Nelson S, Raychaudhuri D. MobilityFirst future internet architecture project. New York: Proceedings of the 7th Asian Internet Engineering Conference; Bangkok, Thailand: Association for Computing Machinery; 2011. p.1–3. doi: 10.1145/2089016.2089017.
29. Ziemba G, Reed D, Traina P. Security considerations for IP fragment filtering. 1995;RFC 1858:1-10. doi: 10.17487/rfc1858.
30. Ptacek TH, Newsham TN. Insertion, evasion, and denial of service: Eluding network intrusion detection. Alberta: Secure Networks INC Calgary, 1998.
31. Hummen R, Hiller J, Wirtz H, Henze M, Shafagh H, Wehrle K, editors. 6LoWPAN fragmentation attacks and mitigation mechanisms. Budapest: Proceedings of the sixth ACM conference on Security and privacy in wireless and mobile networks (WiSec 2013); 2013. p. 55-66. doi: 10.1145/2462096.2462107.
32. Winter T. RPL: IPv6 routing protocol for low power and lossy networks. RFC6550. 2012.
33. International Organization for Standardization, Information Processing Systems. Open Systems Interconnection Reference Model. Security Architecture, ISO Standard 7498-2, 1988.
34. Tsao T, Alexander R, Dohler M, Daza V, Lozano A. A Security Threat Analysis for Routing over Low-Power and Lossy Networks. Internet-Draft–work in progress 03, IETF, 2013. doi: 10.17487/rfc7416.
35. Dvir A, Buttyan L, editors. VeRA-version number and rank authentication in RPL. 17-22 Oct. 2011.Valencia: IEEE Eighth International Conference on Mobile Ad-Hoc and Sensor Systems; 2011. p.709-14. doi: 10.1109/MASS.2011.76.

36. Mayzaud A, Sehgal A, Badonnel R, Chrisment I, Schönwälder J. Mitigation of topological inconsistency attacks in RPL‐based low‐power lossy networks. International Journal of Network Management. 2015;25(5):320-39. doi: 10.1002/nem.1898.
37. O’Connor M, Asdornwised U, Dempsey ML, Huffenberger A, Jost S, Flynn D, et al. Using Telehealth to Reduce All-Cause 30-Day Hospital Readmissions among Heart Failure Patients Receiving Skilled Home Health Services. Appl Clin Inform. 2016;7(2):238-47. doi: 10.4338/ACI-2015-11-SOA-0157.
38. Harvey JB, Valenta S, Simpson K, Lyles M, McElligott J. Utilization of Outpatient Telehealth Services in Parity and Nonparity States 2010-2015. Telemed J E Health. 2019;25(2):132-6. doi: 10.1089/tmj.2017.0265.
39. Hashem IAT, Yaqoob I, Anuar NB, Mokhtar S, Gani A, Khan SU. The rise of “big data” on cloud computing: Review and open research issues. Information systems. 2015;47:98-115. doi: 10.1016/j.is.2014.07.006.
40. Voruganti S. Map Reduce a Programming Model for Cloud Computing Based On Hadoop Ecosystem. International Journal of Computer Science and Information Technologies. 2014.
41. Alyass A, Turcotte M, Meyre D. From big data analysis to personalized medicine for all: challenges and opportunities. BMC Med Genomics. 2015;8:33. doi: 10.1186/s12920-015-0108-y.
42. Zhu H, Yuan Y, Chen Y, Zha Y, Xi W, Jia B, et al. A secure and efficient data integrity verification scheme for cloud-IoT based on short signature. IEEE Access. 2019;7:90036-44. doi: 10.1109/ACCESS.2019.2924486.
43. Verma H, Chahal K, editors. A review on security problems and measures of Internet of Things. 15-16 June 2017. Madurai: 2017 International Conference on Intelligent Computing and Control Systems (ICICCS); 2017. p. 71-6. doi: 10.1109/ICCONS.2017.8250560.
44. Suciu G, Suciu V, Martian A, Craciunescu R, Vulpe A, Marcu I, et al. Big Data, Internet of Things and Cloud Convergence--An Architecture for Secure E-Health Applications. J Med Syst. 2015;39(11):141. doi: 10.1007/s10916-015-0327-y.
45. Khan S, Shakil KA, Alam M. Cloud-based big data analytics—a survey of current research and future directions. Big data analytics. 2018:595-604. doi: 10.1007/978-981-10-6620-7_57.
46. Khan ZA, Herrmann P. Recent advancements in intrusion detection systems for the Internet of Things. Security and Communication Networks. 2019;2019. doi: 10.1155/2019/4301409.

47. Bakhsh ST, Alghamdi S, Alsemmeari RA, Hassan SR. An adaptive intrusion detection and prevention system for Internet of Things. International Journal of Distributed Sensor Networks. 2019;15(11):1550147719888109. doi: 10.1177/1550147719888109.
48. Sokiyna MY, J Aqel M, Naqshbandi OA. Cloud computing technology algorithms capabilities in managing and processing big data in business organizations: Mapreduce, hadoop, parallel programming. Journal of Information Technology Management. 2020;12(3):100-13.
49. Yang C, Huang Q, Li Z, Liu K, Hu F. Big Data and cloud computing: innovation opportunities and challenges. International Journal of Digital Earth. 2017;10(1):13-53. doi: 10.1080/17538947.2016.1239771.
50. Noraziah A, Fakherldin MAI, Adam K, Majid MA. Big Data Processing in Cloud Computing Environments. Advanced Science Letters. 2017;23(11):11092-5. doi: 10.1166/asl.2017.10227.
51. Bormann C, Castellani AP, Shelby Z. Coap: An application protocol for billions of tiny internet nodes. IEEE Internet Computing. 2012;16(2):62-7. doi: 10.1109/MIC.2012.29.
52. Luo M, Zhao H. An authentication and key agreement mechanism for multi-domain wireless networks using certificateless public-key cryptography. Wireless Personal Communications. 2015;81(2):779-98. doi: 10.1007/s11277-014-2157-5.
53. Tsai J-L, Lo N-W. Provably secure and efficient anonymous ID-based authentication protocol for mobile devices using bilinear pairings. Wireless Personal Communications. 2015;83(2):1273-86. doi: 10.1007/s11277-015-2449-4.
54. Lee C, Zappaterra L, Choi K, Choi H-A, editors. Securing smart home: Technologies, security challenges, and security requirements. San Francisco: 2014 IEEE Conference on Communications and Network Security; 2014. doi: 10.1109/CNS.2014.6997467.
55. Lin CH, Lai YY. A flexible biometrics remote user authentication scheme. Computer Standards & Interfaces. 2004;27(1):19-23. doi: 10.1016/j.csi.2004.03.003.
56. Das AK, Goswami A. A robust anonymous biometric-based remote user authentication scheme using smart cards. Journal of King Saud University-Computer and Information Sciences. 2015;27(2):193-210. doi: 10.1145/1031154.1031165.

57. Huang X, Xiang Y, Chonka A, Zhou J, Deng RH. A generic framework for three-factor authentication: Preserving security and privacy in distributed systems. IEEE Transactions on Parallel and Distributed Systems. 2010;22(8):1390-7. doi: 10.1109/TPDS.2010.206.
58. Jiang Q, Kumar N, Ma J, Shen J, He D, Chilamkurti N. A privacy‐aware two‐factor authentication protocol based on elliptic curve cryptography for wireless sensor networks. International Journal of Network Management. 2017;27(3):e1937. doi: 10.1002/nem.1937.
59. Kothmayr T, Schmitt C, Hu W, Brünig M, Carle G, editors. A DTLS based end-to-end security architecture for the Internet of Things with two-way authentication. Clearwater: 37th Annual IEEE Conference on Local Computer Networks-Workshops; 2012. doi: 10.1109/LCNW.2012.6424088.
60. Guanglei Z, editor. A novel mutual authentication scheme for Internet of Things. Modeling, Identification9 and Control (ICMIC),
Proceedings of 2011 International Conference on IEEE; 2011.
61. Bodei C, Degano P, Ferrari G-L, Galletta L. Tracing where IoT data are collected and aggregated. arXiv preprint arXiv:161008419.2016;13(3). doi: 10.23638/LMCS-13(3:5)2017.
62. Bodei C, Degano P, Ferrari G-L, Galletta L. Sustainable precision agriculture from a process algebraic perspective: A smart vineyard. IRIS. 2018;125(4):39–44. doi: 10.2424/ASTSN.M.2018.6.
63. Bodei C, Galletta L, editors. Tracking sensitive and untrustworthy data in IoT. Venice: 2017 The Italian Conference on Cybersecurity (ITASEC17).

64. Bodei C, Degano P, Galletta L, Tuosto E. Tool supported analysis of IoT. arXiv preprint arXiv:171111210. 2017;261:37-56. doi: 10.4204/EPTCS.261.6.
65. Wright SP, Hall Brown TS, Collier SR, Sandberg K. How consumer physical activity monitors could transform human physiology
research. Am J Physiol Regul Integr Comp Physiol. 2017;312(3):R358-R67. doi: 10.1152/ajpregu.00349.2016.
66. Muneer A, Fati SM, Fuddah S. Smart health monitoring system using IoT based smart fitness mirror. Telkomnika. 2020;18(1):317-31. doi:10.12928/telkomnika.v18i1.12434.
67. Vanrenterghem J, Nedergaard NJ, Robinson MA, Drust B. Training Load Monitoring in Team Sports: A Novel Framework Separating Physiological and Biomechanical Load-Adaptation Pathways. Sports Med. 2017;47(11):2135-42. doi: 10.1007/s40279-017-0714-2.
68. Triloka J, Senanayake SA, Lai D. Neural computing for walking gait pattern identification based on multi-sensor data fusion of lower limb muscles. Neural Computing and Applications. 2017;28(1):65-77. doi: 10.1007/s00521-016-2312-x.
69. Guo M, Wang Z, Yang N, Li Z, An T. A multisensor multiclassifier hierarchical fusion model based on entropy weight for human activity recognition using wearable inertial sensors. IEEE Transactions on Human-Machine Systems. 2018;49(1):105-11. doi: 10.1109/THMS.2018.2884717.
70. Garai Á, Péntek I, Adamkó A. Revolutionizing healthcare with IoT and cognitive, cloudbased
telemedicine. Acta Polytechnica Hungarica. 2019;16(2):163-81. doi: 10.12700/APH.16.2.2019.2.10.

آمار
تعداد مشاهده مقاله: 3,026
تعداد دریافت فایل اصل مقاله: 1,770


سامانه مدیریت نشریات علمی. قدرت گرفته از سیناوب