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Volume 2020 |Article ID 8829595 | https://doi.org/10.1155/2020/8829595

Xucheng Huang, Shah Nazir, "Evaluating Security of Internet of Medical Things Using the Analytic Network Process Method", Security and Communication Networks, vol. 2020, Article ID 8829595, 14 pages, 2020. https://doi.org/10.1155/2020/8829595

Evaluating Security of Internet of Medical Things Using the Analytic Network Process Method

Academic Editor: Amir Anees
Received23 Jun 2020
Revised02 Jul 2020
Accepted24 Jul 2020
Published01 Sep 2020

Abstract

Internet of Medical Things (IoMT) plays an important role in healthcare. Different devices such as smart sensors, wearable devices, handheld, and many other devices are connected in a network in the form of Internet of Things (IoT) for the smooth running of communication in healthcare. Security of these devices in healthcare is important due to its nature of functionality and efficiency. An efficient and robust security system is in dire need to cope with the attacks, threats, and vulnerability. The security evaluation of IoMT is an issue since couple of years. Therefore, the aim of the proposed study is to evaluate the security of IoMT by using the analytic network (ANP) process. The proposed approach is applied using ISO/IEC 27002 (ISO 27002) standard and some other important features from the literature. The results of the proposed research demonstrate the effective IoMT components which can further be used as secure IoMT.

1. Introduction

Internet of Things has several applications in the daily life and has made life very easy. From industry to education, healthcare, and other places, the IoT is mostly used. Internet of Medical Things is the advanced version of IoT which has a key role in healthcare. Devices such as wearable, handheld, sensors, actuator, and others are connected for communication through Internet. For the smooth communication of these devices, security is important to run in an effective and efficient way. Security is the protection from unauthorized access of illegal users. In healthcare, the devices are sometimes connected through heterogeneous environment with the support of different IoT devices. So, the security evaluation is important for them to ensure that the communication is safe and secure. IoMT plays an important role in remote exchange data processes. The IoT devices have limited capabilities due to low processing, tiny memory, and limited storage, so implementing security will be a challenging task. The security and privacy in IoMT devices are vital due to a number of reasons as IoMT devices are ubiquitous and their applications are employed in health. For this purpose, reinforcing a security mechanism is indispensable to cope with these attacks, vulnerabilities, and security and privacy challenges. Security can be one of the important factors for IoHT [16].

The existing research regarding the security of IoMT covers different aspects. However, there is a lack of knowledge that how to evaluate the security of IoMT based on security attributes and features. So, to overcome this limitation, the proposed research presents the ANP approach for the evaluation of security of IoMT in term of the ISO/IEC 27002 (ISO 27002) standard, and some other important features identified from the literature. The ANP method incorporates the criteria given for achieving the goal based on the available alternatives. This method helps in situation when complexity arises.

The organization of the paper is as follows: Section 2 presents the related work to the security evaluation of IoMT, along with the existing approaches for security evaluations are discussed. In Section 3, the research method is briefly described. Section 4 concludes the paper.

Several approaches have been used by researchers for the evaluation security. The basic security requirements are defined in confidentiality, integrity, and availability (the CIA model) [712]. The IoMT devices are vulnerable to several threats of security, attacks, and vulnerabilities. IoMT devices suffer from enormous security threats due to low cost and power unlike traditional desktop and mobile devices. The malware can replicates itself by compromising the connection that links IoT devices [13]. Different frameworks, models, reviews, surveys, and analysis pertaining to the security of IoT-based systems for security analysis are used. Frustaci et al. [14] evaluated IoT security issues at three different layers of IoT such as perception, transportation, and application. Leister et al. [15] evaluated the security of IoT in e-health by presenting a scenario-based framework. Alrawi et al. [16] proposed component-based analysis such as IoT device, mobile application, communication channel, and cloud end points for the home-based IoT system. Tekeoglu and Tosun [17] presented a layer-based packet capturing framework for investigating security and privacy of IoT devices. Cherneyshev and Hannay [18] evaluated IoT security by using two smart TVs against the multisurface attacks. Ali and Awad [19] assessed the security of IoT smart home in terms of vulnerability. Mazhelis and Tyrväinen [20] evaluated IoT platforms from application provider perspectives. Apart from these approaches, several other approaches are being available in the literature [2124].

Similarly, mobile computing services can be used in IoT by using services of mobile phones and apps or through the M-Health care system. The M-Health contributes to the IoT by furnishing various services such as compactness, IP connectivity, consumption of low power, and security [25]. Recently, many applications have been developed to deliver mobile-based services to the users in healthcare. The applications of smart phone enable the patients to know about their diseases after the analysis in the field of gynaecology and paediatrics [26].

The purpose of this section is to study the existing literature to know about the work done in the area of security evaluation. For this purpose, the popular libraries including ACM, IEEE, ScienceDirect, and Springer were searched. Different types of information were obtained, and the details are given in figures and tables in this section. Figure 1 shows the type of publication along with the total number of papers published in the ACM library.

Figure 2 shows the content type along with the total number of publications.

The purpose of searching different libraries was to know more about the research done in the area. For this purpose, the IEEE library was also searched. Figure 3 shows the type of publication along with the total number of papers published in the IEEE library.

Figure 4 shows the publication topic in the area along with the total number of papers published.

The library of ScienceDirect was also searched to know about the security-related work published in the area. Figure 5 shows the total number of publications in the given year in the ScienceDirect library.

Figure 6 shows the number of publications along with the type of publication.

Figure 7 shows the publication title along with the number of publications.

Finally, the library of Springer was searched for the detail information in the area. Figure 8 shows the number of publications with the type of publications in the Springer library.

Figure 9 shows the article topic along with the total number of publications.

3. Applications of the Analytic Network Process for Evaluating Security of Internet of Medical Things

The analytic network process has several applications in different areas [11, 24, 2729]. The reason behind using this method was to evaluate the security of IoMT, as this method works very well in situation where complexity exists. In the proposed research work, the analytic network process approach is used for security evaluation of Internet of Medical Things. The ANP method incorporates the criteria given for achieving the goal based on the available alternatives. This method helps in situation when complexity arises. The method adopted the ISO standard of security along with the identified security features from the literature. The ANP method consists of three parts: (a) the goal, (b) criteria, and (c) alternatives. Details regarding the ANP can be found in [30]; however, the following are the main steps:(a)A particular phenomenon is to be divided into subparts(b)A qualitative scale of measure is applied while this can be converted into a quantitative scale between 1 and 9(c)The pairwise comparison is done for all the criteria along with alternatives(d)The relative importance is found by finding the principal eigenvalue and the related eigenvector of the comparison matrix(e)The consistency of matrix is measured

Priority vector “” is calculated as follows:

λmax is the major eigenvalue of the matrix “A,” and “” is its eigenvector. The value of “λ” is obtained by summing the column of the original matrix multiplied by the normalized EV. The principal EV is obtained by the sum of all “λ”.

The “consistency index (CI)” and “consistency random (CR)” of the pairwise comparison matrix are computed by the following equation:

The random consistency index (RI) table is given by Saaty and is shown in Table 1 [30].


123456789101112131415

RI000.580.91.121.241.321.411.451.491.511.481.561.571.59

The value of CR should be less than 0.1.
(f)Construction of the supermatrix(g)Conversion of the weighted supermatrix into the limit matrix for making the decision(h)Deciding the most appropriate alternative from the limit matrix

Figure 10 shows the goal, criteria, and alternatives of the proposed research.

(i)Identification of attributes and scoring process: the process of identification of attributes was very tricky due to the reason that important attribute should be missed. For this purpose, the literature was searched and finally the attributes of the International Standard Organization (ISO) information security standard such as ISO/IEC 27000-series (ISO/IEC, 2018) along with 8 important attributes from the literature were identified. ISO/IEC 27000-series (ISO/IEC, 2018) is a well-known standard and widely accepted standard [12].

Table 2 shows the list of selected attributes.


Requirements[7][8][9][10][11][12][31][32][33][34][35][36][37][38][39][40][41][42]

Confidentiality
Authentication
Integrity
Availability
Authorization
Physical security
Continuity
Trustworthiness
Auditing
Network monitoring
Secure key management
Access control
Nonrepudiation

After selecting the attributes for security evaluation, these attributes were shared with the experts in the field. The reason of sharing was to gather appropriate score for each component with respect to the defined attribute. Assigning the score to the relevant attribute was based on the expertise of the expert. Table 3 shows the comparison with respect to IoMT1.


AvailabilityAuthenticationConfidentialitySafetyStabilityContinuityTrustworthinessAuditingNetwork monitoringSecure key managementAccess controlNon-repudiationEV

Availability11/223423272950.167
Authentication2124332535720.189
Confidentiality1/21/213222272750.130
Safety1/31/41/311/223535350.104
Stability1/41/31/22122232720.090
Continuity1/21/31/21/21/213322350.082
Trustworthiness1/31/21/21/31/21/31232430.064
Auditing1/21/51/21/51/21/31/2123320.051
Network monitoring1/71/31/71/31/31/21/31/212220.036
Secure key management1/21/51/21/51/21/21/21/31/21220.038
Access control1/91/71/71/31/71/31/41/31/21/2120.022
Non-repudiation1/51/21/51/51/21/51/31/21/21/21/210.028

CR = 0.985.

Table 4 shows the comparison with respect to IoMT2.


AvailabilityAuthenticationConfidentialitySafetyStabilityContinuityTrustworthinessAuditingNetwork monitoringSecure key managementAccess controlNon-repudiationEV

Availability1322423272520.179
Authentication1/3124332535720.167
Confidentiality1/21/213222272750.132
Safety1/21/41/311/223235350.099
Stability1/41/31/22122232720.092
Continuity1/21/31/21/21/212322350.080
Trustworthiness1/31/21/21/31/21/21232440.068
Auditing1/21/51/21/21/21/31/2123320.055
Network monitoring1/71/31/71/31/31/21/31/212220.035
Secure key management1/21/51/21/51/21/21/21/31/21220.039
Access control1/51/71/71/31/71/31/41/31/21/2120.023
Non-repudiation1/21/21/51/51/21/51/41/21/21/21/210.031

CR = 0.994.

Table 5 shows the comparison with respect to IoMT3.


AvailabilityAuthenticationConfidentialitySafetyStabilityContinuityTrustworthinessAuditingNetwork monitoringSecure key managementAccess controlNon-repudiationEV

Availability1323425232750.192
Authentication1/3124352535720.173
Confidentiality1/21/213222272750.132
Safety1/31/41/311/223533350.098
Stability1/41/31/22122232720.089
Continuity1/21/51/21/21/213322320.073
Trustworthiness1/51/21/21/31/21/31232230.059
Auditing1/21/51/21/51/21/31/2123320.054
Network monitoring1/31/31/71/31/31/21/31/212220.039
Secure key management1/21/51/21/31/21/21/21/31/21220.040
Access control1/71/71/71/31/71/31/21/31/21/2120.023
Non-repudiation1/51/21/51/51/21/21/31/21/21/21/210.028

CR = 0.10.

Table 6 shows the comparison with respect to IoMT.


IMT1IMT2IMT3EV

IMT11340.623
IMT21/3120.239
IMT31/41/210.137

CR = 0.022.

The rest of the calculations for the remaining attributes to IoMT were done the same as Table 6. After pairwise comparisons, all the calculations were brought together into the weighted supermatrix for the purpose to convert it into the limit matrix for decision-making about security evaluation. Table 7 shows the weighted supermatrix.


Node labelCriteria for evaluating security of Internet of Medical ThingsAvailable component
AvailabilityAuthenticationConfidentialitySafetyStabilityContinuityTrustworthinessAuditingNetwork monitoringSecure key managementAccess controlNonr-epudiationIoMT1IoMT2IoMT3

Criteria for evaluating security of Internet of Medical ThingsAvailability0.000.000.000.000.000.000.000.000.000.000.000.000.170.180.19
Authentication0.000.000.000.000.000.000.000.000.000.000.000.000.190.170.17
Confidentiality0.000.000.000.000.000.000.000.000.000.000.000.000.130.130.13
Safety0.000.000.000.000.000.000.000.000.000.000.000.000.100.100.10
Stability0.000.000.000.000.000.000.000.000.000.000.000.000.090.090.09
Continuity0.000.000.000.000.000.000.000.000.000.000.000.000.080.080.07
Trustworthiness0.000.000.000.000.000.000.000.000.000.000.000.000.060.070.06
Auditing0.000.000.000.000.000.000.000.000.000.000.000.000.050.050.05
Network monitoring0.000.000.000.000.000.000.000.000.000.000.000.000.040.040.04
Secure key management0.000.000.000.000.000.000.000.000.000.000.000.000.040.040.04
Access control0.000.000.000.000.000.000.000.000.000.000.000.000.020.020.02
Non-repudiation0.000.000.000.000.000.000.000.000.000.000.000.000.030.030.03

Available componentIoMT10.620.540.630.580.580.650.680.570.520.490.620.650.000.000.00
IoMT20.240.300.170.190.310.230.200.290.330.310.240.230.000.000.00
IoMT30.140.160.190.230.110.120.120.140.140.200.140.120.000.000.00

The weighted matrix was converted into the limit matrix by taking the power of the weighted matrix. This process was done till all the elements of each row become the same. The reason was to make decision based on the limit matrix. Table 8 shows the limit matrix.


Node labelCriteria for evaluating security of Internet of Medical ThingsAvailable component
AvailabilityAuthenticationConfidentialitySafetyStabilityContinuityTrustworthinessAuditingNetwork monitoringSecure key managementAccess controlNon-repudiationIoMT1IoMT2IoMT3

Criteria for evaluating security of Internet of Medical ThingsAvailability0.170.170.170.170.170.170.170.170.170.170.170.170.000.000.00
Authentication0.180.180.180.180.180.180.180.180.180.180.180.180.000.000.00
Confidentiality0.130.130.130.130.130.130.130.130.130.130.130.130.000.000.00
Safety0.100.100.100.100.100.100.100.100.100.100.100.100.000.000.00
Stability0.090.090.090.090.090.090.090.090.090.090.090.090.000.000.00
Continuity0.080.080.080.080.080.080.080.080.080.080.080.080.000.000.00
Trustworthiness0.060.060.060.060.060.060.060.060.060.060.060.060.000.000.00
Auditing0.050.050.050.050.050.050.050.050.050.050.050.050.000.000.00
Network monitoring0.040.040.040.040.040.040.040.040.040.040.040.040.000.000.00
Secure key management0.040.040.040.040.040.040.040.040.040.040.040.040.000.000.00
Access control0.020.020.020.020.020.020.020.020.020.020.020.020.000.000.00
Non-repudiation0.030.030.030.030.030.030.030.030.030.030.030.030.000.000.00

Available componentIoMT10.000.000.000.000.000.000.000.000.000.000.000.000.600.600.60
IoMT20.000.000.000.000.000.000.000.000.000.000.000.000.250.250.25
IoMT30.000.000.000.000.000.000.000.000.000.000.000.000.160.160.16

Based on the limit matrix, we conclude that IoMT1 is the most secure component followed by IoMT2 and then IoMT3. Figure 12 shows the ranking of IoMT components.

4. Conclusion

The Internet of Medical Things is considered to be a significant part of healthcare which plays an important role. Communication among different devices such as smart sensors, wearable devices, handheld, and many other devices are connected in a network is possible due to the success of Internet of Things. For efficient and smooth running of healthcare, the security of different devices connected is mandatory. An efficient and robust security system is in dire need to cope with the attacks, threats, and vulnerability. The security evaluation of IoMT is an issue since the last few years. The proposed study is an endeavor toward the evaluation of the security of IoMT and using the analytic network process. The approach is applied using the ISO/IEC 27002 (ISO 27002) standard with the collection of some other important features from the literature. The results of the proposed research demonstrate the effective IoMT components which can further be used as secure IoMT.

Data Availability

No data were used to support the study.

Conflicts of Interest

The authors declare no conflicts of interest regarding this paper.

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Copyright © 2020 Xucheng Huang and Shah Nazir. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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