Conference Proceeding

Mathematics in Space and Applied Sciences (ICMSAS-2023)
ICMSAS-2023

Subject Area: Mathematics
Pages: 331
Published On: 03-Mar-2023
Online Since: 04-Mar-2023

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Author(s): Diksha, Meenakshi

Email(s): dikshachouhan1035@gmail.com

Address: Diksha1*, Meenakshi2
1*,2Srinivasa Ramanujan Department Of Mathematics, Central University Of Himachal Pradesh, Dharamshala,176215, Himachal Pradesh, India.
*Corresponding Author

Published In:   Conference Proceeding, Mathematics in Space and Applied Sciences (ICMSAS-2023)

Year of Publication:  March, 2023

Online since:  March 04, 2023

DOI:




Cryptanalysis on Secure ECC based Mutual Authentication Protocol for

Cloud-Assisted TMIS

 

Diksha1*, Meenakshi2

1*,2Srinivasa Ramanujan Department Of Mathematics, Central University Of Himachal Pradesh, Dharamshala,

176215, Himachal Pradesh, India.

*Corresponding Author E-mail: dikshachouhan1035@gmail.com

 

ABSTRACT:

The creation of TMIS (Telecare Medical Information System) makes it simpler for patients to receive healthcare services and opens up options for seeking medical attention and storing medical records with access control. With Wireless Medical Sensor Network and cloud-based architecture, TMIS gives the chance to patients to collect their physical health information from medical sensors and also upload this information to the cloud through their mobile devices. The communication is held through internet connectivity, therefore security and privacy are the main motive aspects of a secure cloud-assisted TMIS. However, because very sensitive data is transmitted between patients and doctors through the cloud server, thus security protection is important for this system. Recently, Kumar et al designed a mutual authentication protocol for cloud-assisted TMIS based on ECC [2]. In this paper, we revisited this scheme and traced out that their scheme has some significant pitfalls like health report revelation attack, and report confidentiality. In this study, we will provide the cryptanalysis of the scheme developed by Kumar et al.

 

KEYWORDS: TMIS, Cloud Computing, Digital signature, Cryptanalysis, ECC.

 

1.     INTRODUCTION:

With the advancement in technology, patients can receive care from medical professionals through the internet. The inaccessibility of remote locations and unavailability of facilities makes modern healthcare facilities difficult and these healthcare facilities are as expert advice, proper diagnosis, clinical tests, etc. Due to poor return on investments, no one is interested to invest in these areas and also doctors are not interested to serve in those areas which are under development. This leads the patients to have to travel long distances and spend a lot of money to get medical treatment. Some patients leave their hopes on their fates or lived with treatments from local health workers. In this case, a platform Telecare Medical Information System (TMIS) facilitates the patients and doctors with the communication between them and provides medical assistance in the patient’s home. At the moment, everyone is paying close attention to cloud computing. It exhibits a significant potential for providing medical services online in TMIS due to its profitable specialties including on-demand self-service, more resilience, and resource sharing.

 

TMIS can gain various financial and functional advantages from cloud-based architecture, including flexible medical data storage, lower costs, better accessibility, and higher standards of care. But it also faces a lot of problems like reliability, privacy, security, and many others. Since the patient’s data is transmitted between the entities over an insecure public channel. Therefore data security, confidentiality, and also its authenticity are major priorities in cloud-based TMIS.

The likelihood of a mischievous insider for consumers of cloud services is increased by the consolidation of IT services and clients under one management domain and the general lack of transparency into provider methods and procedures. A provider could choose to keep secrets about how it supervises personnel and provides them access to physical and digital resources, analyses, and reports on quality management. To further complicate matters, hiring standards and procedures for cloud staff are frequently hidden or not disclosed at all. This type of circumstance presents an interesting opportunity for an enemy, who may be engaged in a nation-state-sponsored attack, organized crime, hobbyist hackers, or even industrial crime. Such an adversary might be able to gather sensitive information or take total control of the cloud services thanks to the level of access allowed with little to no chance of being detected [3].

 

A safe cloud-assisted TMIS has required some important characteristics such as:

a)     Message authentication: The system's users must be able to confirm that a message delivered over an unsecured channel was actually sent to and received by a legitimate recipient without interference from an unauthorised third party.

b)    Patient anonymity: Any of the messages on the public channel should not express the true identity of the patient and anyone can’t estimate and find the patient’s true identity.

c)     Patient unlinkability: Any outsider can’t estimate the relationship between patient and doctor.

d)    Report confidentiality: The sensitive data of the patient should be accessible by only the appointed doctor.

e)     Non-repudiation: The patient, hospital, and doctor cannot contest the veracity of the digital signature they placed on a document or the message they sent.

 

2.     RELATED WORKS:   

In 2012, Patra et al proposed a cloud-based model for making a rural healthcare information system [4]. Furthermore, Chen et al. put forth a cloud-based plan for exchanging medical data. They use the pairing technology with an asymmetric key to encrypt the information in this scheme [5]. But later on, this scheme faced some problems [6]. In 2015, an improved patient-server mutual authentication protocol for TMIS was proposed by Amin et al. [7]. This protocol concerns a biometric-based remote user authentication scheme for TMIS. Wu et al also propose a mutual authentication scheme for this healthcare application [8]. In 2014, Wen et al introduced an anonymous authentication scheme for TMIS [9]. Further, Xu et al provided a secure and effective two-factor mutual authentication and key agreement mechanism for TMIS based on the ECC [10]. Moreover, with the help of WMSN, He et al built a strong anonymous authentication technique for healthcare applications [11]. Later on, a symmetric key-based authentication method for wireless medical sensor networks was proposed by Jangirala et al [12]. Chen et al also put forward a cloud-assisted secure authentication technique for healthcare systems [13]. To address these issues with Chen et al's method, Chiou et al offered a modified authentication scheme in 2016. Chiou et al, however, noted that this framework does not provide message authentication, patient anonymity, etc [14]. Further, Mohit et al reviewed [14] and offered a mutual authentication framework based on cloud for healthcare systems [15] due to some pitfalls in the scheme [14]. Also, a cloud-assisted effective mutual authentication protocol for healthcare systems was introduced by Kumar et al [16]. For the TMIS environment, Li et al proposed a cloud-assisted mutual authentication framework with preserved privacy [1]. In 2018, Kumar et al reviewed Li et al’s scheme and presented a framework for cloud-assisted TMIS with mutual authentication using ECC [2]. But now, we reviewed this protocol and established some design flaws like health report revelation attack, and report confidentiality.

 

The remaining paper is split up into different sections as follows:

Section 3 represents the review of the scheme [2] and the difficulties which are faced by this scheme described in section 4. Lastly, section 5 discusses the conclusion of this paper.

 

3.    REVIEW OF KUMAR ET AL. SCHEME[2]

A mutual authentication and preserved privacy framework for cloud-assisted TMIS is offered by Kumar et al. In their scheme, total five important roles of bodies take place. This programme is divided into four stages: the upload phase for healthcare centre, the patient data upload phase, the treatment phase, and the checkup phase.

1.     H uploads the inspection medical report of P in C in the Healthcare Centre Upload Phase (HUP).

2.     In the Patient data upload phase (PUP), P uploads his/her current medical report from the embedded body sensor to C.

3.     In the treatment phase (TP), D will recommend treatments to C for P of the appropriate body.

4.     P obtains the report from C during the Checkup Phase (CP), as directed by D.     

Notations:

IDx

Entity x’s unique identity                     

NID

Dynamic pseudo random number

snx

Serial number of xth participant

PRx

Private key of x   

PKx

Public key of x   

A

Adversary

mH

Inspection report of P generated by H     

Si(M)

Using key i to sign M

mB

Health report of P from body sensor       

h(.)

Hash function                                           

mD

Medical report of P generated by D        

SKxy

Session-key between x and y

Kx

Computing key of x entity                       

G

Elliptic curve group (additive)

G

Base point of G                                        

Sigx

Signature of entity x

Zp*

Additive group of large prime of order p

Vi(M)

Using key i to verify M

 

HUP:

The registration of P takes place in H, where an NID is allotted or assigned to P by H with      the help of mobile device securely. P’s inspection report mH=(IDP, dataP) is uploaded (in C) by H after mutual authentication between H and C in this phase and this happen with following procedure:

1.)   Initially, H sends a massage which consist of IDH, random number a (from Zp*) and TH1 to C through secure channel.

2.)   After getting this message, C checks the validity of TH1 with TC1 - TH1  ≤ ∆T. Then a random number b (є Zp*) is generated by C and also C computes S1= h(IDH||a||b||TH1), K1= h(IDH||a||TH1) which is used for the encryption of the (b, S1,TC2) to get E1. After that, C sends (E1, TC2) to H via public channel.

3.)   When this message is collected by H, then firstly H verifies TH2-TC2 ≤ ∆T (if not, then the session will be terminated) and ready the key K1’ to decrypt the E1. Where K1’= h(IDH||a||TH1) and E1= EK1(b, S1, TC2). After that, H computes S1’=h(IDH||a||b||TH1) and verifies that S1’=? S1. Then H computes SKHC = h(IDH||S1’||abg||TC1) and key K2 =h(IDP||IDH||NID) to encrypt mH i.e. CH = EK2(mH). Next, H makes digital signature SigH = SPRH(h(mH)), S2 = h(SKHC||CH||SigH||TH3) and encrypts E2 = ESKHC(IDP, S2,CH, NID, SigH, TH3). Sends the message (E2, TH3) to C via public channel.     

4.)   Then C verifies TC3-TH3 ≤ ∆T after collecting the message from H and computes the session key SKCH = h(IDH||S1||abg||TC1) to decrypt E2. Next, C computes S2’ = h(SKCH||CH||SigH||TH3) and check whether S2’= S2 or not. If not then session will stop there otherwise C stores NID, IDP, SigH, CH.

 

PUP:

The embedded sensor in the patient’s body collects the health information mB= (IDP, dataB) and securely sends this information to the patient’s mobile phone. C gives the sequence number snx and mH to P after making the request by P (using his/her IDP and NID) to C.

1.)   P receives a health report from the embedded body sensor in form of mB and sends (IDP, NID, TP1) to C through the trustable channel.

2.)   After receiving this message, C verifies TC4-TP1 ≤ ∆T. Next, C computes I = snx + h(NID||IDP) and generates the random number c (є Zp*). Then C computes the hash value S3 = h(NID||IDP||CH||SigH||c||TC5), encrypts the message (SigH, CH, S3, IDH, c, TC5) using the snx and gets E3. Further, C sends (E3, I, TC5) to P via a public channel.

3.)   P verifies TP2-TC5 ≤ ∆T after getting the message (E3, I, TC5) from C and computes Y = I + h(NID||IDP) to decrypt E3. After that, P computes S3’= h(NID||Y||CH||SigH||c||TC5) and verifies whether S3’ = S3 or not. The session will end there if it does not. Otherwise, P generates random number d (є Zp*) and computes the session key SKPC = h(IDP||IDH||CH||S3’||cdg||TC5). Now, P computes a key K3 = h(IDP||IDH||NID) for decryption of mH* = DK3(CH) and checks mH* = mH. Furthermore, P verifies whether VPKH(SigH) = h(mH) or not. After verification, P computes K4 = h(IDP||IDD||Y) and encrypts CP = EK4(mH, mB). Moreover, P makes the digital signature SigP = SPRP(h(mB)), computes the hash value      S4 = h(SKPC||CP||SigP||S3’||cdg||TP3) and using Y as a key to encrypt E4 =  EY(d, S4, SigP, CP, TP3). Lastly, through a public channel, P communicates the message (E4, TP3) to C.

4.)   On accepting this message, C checks TC6-TP3 ≤ ∆T. If hold, then C decrypts E4 with snx, computes SKCP = h(IDP||IDH||CH||S3||cdg||TC5) and computes S4’ = h(SKCP||CP||SigP||S3||cdg||TP3) to check whether S4 = S4’ or not. In that case, C ends the session. If not, C verifies P and saves CP, IDP, and SigP in the database.

 

TP:

The authentication establishes between D and C in this phase. D takes the report of the patient from C for diagnosis. After that D uploads the treatment report mD = (IDP, dataD) for the respective patient in C.

1.)   D sends a message (IDD, r, TD1) to C through a secure channel. (Where r is the generated random number.)

2.)   After collecting this message, C firstly verifies TC7-TD1 ≤ ∆T, computes J=snx + h(IDD||r), generates the random number s, computes the hash value  S5 = h(IDP||IDD||SigH||SigP||CP||TC8), encrypts (SigP, SigH, IDP, NID, CP, s, S5, TC8) using snx (i.e. E5) and sends the message (E5, J, TC8) to D through the insecure channel.

3.)    D verifies TD2-TC8 ≤ ∆T after receiving this message and computes Z = J + h(IDD||r) to decrypt E5 and gets (NID, IDP, SigP, SigH, s, S5, CP, TC8). After that, D computes S5’ = h(IDP||IDD||SigH||SigP||CP||TC8) and checks S5’ =? S5. After this verification D successfully authenticates C and computes the key K5 = h(IDP||IDH||NID). Moreover, D uses this key K5 to decrypt CP and gets the P’s reports mH, mB. Further, D performs VPKH(SigH) = h(mH) and VPKP(SigP) = h(mB). If it holds, then D diagnoses these reports and makes treatment report mD, using key K5 to encrypt CD = EK5(mH, mB, mD). Next, D makes his/her digital signature SigD = SPRD(h(mD)) and computes S6 = h(IDP||IDD||CD||SigD||SigP||TD3). Also, D computes session key SKDC = h(S6||IDP||IDD||SigD||SigP||rsg||TD3), encrypts E6 = EZ(SigD, CD, S6, TD3) and sends the message (E6, TD3) to C through a public channel.

4.)   Upon receiving this message, C verifies TC9-TD3 ≤ ∆T and decrypts Dsnx(E6). Furthermore, C computes S6’ = h(IDP||IDD||CD||SigD||SigP||TD3) and verifies S6’ =? S6. C authenticates D after only this successful verification, now C computes SKCD = h(S6’||IDP||IDD||SigD||SigP||rsg||TD3). Lastly C stores CD and SigD in its database.

 

CP: 

After Treatment Phase, P collects his/her encrypted report mD = (IDP, dataD) from C after   mutual authentication between them.

1.)   Firstly, P sends the message (IDP, NID, x, snx, TP4) to C through the secure channel. (Where x is the random number taken from Zp*).

2.)   On accepting this message, C verifies TC10-TP4 ≤ ∆T and generates a random number y. Next, C computes S7 = h(SKCP||IDP||IDD||CD||xyg||SigP||TC11) and with the help of session key, C encrypts E7 = ESKCP(IDD, SigD, CD, S7, y, TC11). Lately, C sends (E7, TC11) to P through the public channel. 

3.)   P verifies TP4-TC11 ≤ ∆T and proceeds with the decryption of E7 using the session key. Now P compute S7’ = h(SKPC||IDP||IDD||CD||xyg||SigP||TC11) and verifies S7’ =? S7. P authenticates C after only this successful verification and decrypts the report CD using K4 = h(IDP||IDD||Y). Now P collects all his/her reports mH, mB, mD and verifies the digital signature with the help of the public key of D as VPKD(SigD) =? h(mD). If verification holds, then P again encrypts reports(say CE) with the help of the same key K4 such as CE = EK4(mH, mB, mD), and computes S8=h(SKPC||S7’||CE||SigP||SigD||xyg||TP6). Moreover, P encrypts E8 = ESKPC(CE, S8, TP6) and uses the public channel to deliver the message (E8, TP6) to C.

4.)   After collecting the message, C verifies TC12-TP5 ≤ ∆T and decrypts E8 using session key SKCP. Further, C computes S8’ = h(SKCP||S7’||CE||SigP||SigD||xyg||TP6)  and checks S8 =? S8’. C authenticates P after only this successful verification and stores CE in its database.

 

4.     THE CRYPTANALYSIS OF KUMAR  

Et al’s scheme:                           

4.1    Health report revelation attack:

4.1.1.  Medical report revelation attack in HUP:

When HUP starts, H sends its identity, IDH, and random number m from Zp*.and sends IDH, a, and TH1 to cloud server C through the trustable channel. In this case, H is simply sending its own identity.

And after the third step, H sends E2 together with TH3 to C via insecure channel, where E2 is encrypted by session key SKHC as follows E2 = ESKHC(IDP, NID, S2, CH, SigH, TH3), SKHC=h(IDH||A1'||abg||TC1), K2=h(IDP||IDH||NID), CH = EK2(mH).

 

When C receives all these things, then C checks the time stamp and computes SKHC=h(IDH||S1'||abg||TC1), decrypts E2 with this session key. From this action of C, C gets IDP, NID, CH, S2, SigH, and TH3.

Now the privileged insider of C, (let’s say A) can compute K2, which was used to encrypt mH, and also used for the decryption of CH because A has IDP, NID, IDH. Thus A can decrypt mH = DK2(CH), which contains the inspection report of the patient and the IDP.

 

4.1.2.  Medical report revelation attack in PUP:

After the third step in PUP, P sends E4 together with TP3 to C via an insecure channel, where E4 is encrypted by sequence number Y (= snx) as follows E4 = EY(d, S4, SigP, CP, TP3), and CP = EK4(mH, mB) is encrypted by P with the help of key K4 = h(IDP||IDD||Y). Whereas in TP, D decrypts (mH, mB) = DK5(CP) with K5 = h(IDP||IDH||NID), and this key K5 is the same as K2.

But as in 4.1.1, A already got the key K2, and using this key he/she can decrypt CP. Hence, the inspection report mH together with the health report mB (generated by sensors) will be revealed by A in PUP.

 

4.1.3.  Medical report revelation attack in TP:

Similarly, after the third step in TP, D sends E6 = EZ(= snx)(SigD, CD, S6, TD3) and TD3 to C via a public channel, where CD = EK5(mH, mB, mD) is encrypted with the help of key K5 = h(IDP||IDH||NID). Whereas P decrypts this CD with the help of K4 = h(IDP||IDD||Y) in CP. 

But IDP, IDD is already present in the database of C, and Y(= snx) is engaged by C. Therefore, the Privileged insider of C also has all these contents and hence can compute the key K4 in TP.

Consequently, all reports mH, mB, mD of patients will be revealed by A. 

 

4.2.    Report Confidentiality:

If these health reports are revealed by the privilege insider of C (i.e. A), then the condition for report confidentiality has been contradicted by these action of A.

(Here the condition for report confidentiality is that the medical reports of P should be accessible by only appointed doctor.) 

 

5.  CONCLUSION:

When we looked again at Kumar et al’s scheme which is with the mutual authentication approach, we concluded that it is not capable of securely transmitting medical reports between patients and doctors. Since these reports are made public by a privileged insider of C, the patient's privacy is violated, and as a result, the reports' confidentially is also ruined. As a result, this scheme doesn’t fulfill all the objectives of a secure cloud-assisted Telecare Medical Information System.   

 

6. REFERENCES:

1.         C.-T. Li, D.-H. Shih, C.-C. Wang, Cloud-assisted mutual authentication and privacy preservation protocol for telecare medical information systems, Computer methods and programs in biomedicine 157 (2018) 191–203

2.         Kumar, V., Ahmad, M., Kumari, A., A Secure Elliptic Curve Cryptography Based Mutual Authentication Protocol for Cloud-assisted TMIS, Telematics and Informatics (2018).

3.         CSA, “The notorious nine cloud computing top threats in 2013,” The Notorious Nine Cloud Computing Top Threats in2013: pdf.

4.         Patra, M. R.; Das, R. K.; Padhy, R. P. CRHIS: Cloud Based Rural Healthcare Information System. In Proceedings of the 6th International Conference on Theory and Practice of Electronic Governance; ACM: Albany New York USA, 2012; pp 402–405.

5.         C.-L. Chen, T.-T. Yang, T.-F. Shih, A secure medical data exchange protocol based on cloud environment, Journal of medical systems 38 (9) (2014) 112

6.         C.-T. Li, C.-C. Lee, C.-C. Wang, T.-H. Yang, S.-J. Chen, Design flaws in a secure medical data exchange protocol based on cloud environments, in: International Conference on Algorithms and Architectures for Parallel Processing, Springer, 2015, pp. 435–444.

7.         R. Amin, S. H. Islam, G. Biswas, M. K. Khan, M. S. Obaidat, Design and analysis of an enhanced patient-server mutual authentication protocol for telecare medical information system, Journal of medical systems 39 (11) (2015) 137.

8.         Wu, F., and Xu, L., Security analysis and improvement of a privacy authentication scheme for telecare medical information systems. J. Med. Syst 37(4):1–9, 2012. doi:10.1007/s10916-013-9958-z

9.         Wen, F., and Guo, D., An improved anonymous authentication scheme for telecare medical information systems.J. Med. Syst. 38(5):26, 2014. doi:10.1007/s10916-014-0026-0

10.      Xu, X., Zhu, P., Wen, Q., Jin, Z., Zhang, H., and He, L., A secure and efficient authentication and key agreement scheme based on ecc for telecare medicine information systems. J. Med. Syst. 38(1):9994, 2013. doi:10.1007/s10916-013-9994-8

11.      D. He, N. Kumar, J. Chen, C.-C. Lee, N. Chilamkurti, S.-S. Yeo, Robust anonymous authentication protocol for health-care applications using wireless medical sensor networks, Multimedia Systems 21 (1) (2015) 49–60.

12.      J. Srinivas, D. Mishra, S. Mukhopadhyay, A mutual authentication framework for wireless medical sensor networks, Journal of medical systems 41 (5) (2017) 80

13.      C.-L. Chen, T.-T. Yang, M.-L. Chiang, T.-F. Shih, A privacy authentication scheme based on cloud for medical environment, Journal of medical systems 38 (11) (2014) 143.

14.      S.-Y. Chiou, Z. Ying, J. Liu, Improvement of a privacy authentication scheme based on cloud for medical environment, Journal of medical systems 40 (4) (2016) 101.

15.      P. Mohit, R. Amin, A. Karati, G. Biswas, M. K. Khan, A standard mutual authentication protocol for cloud computing based health care system, Journal of medical systems 41 (4) (2017) 50

16.      V. Kumar, S. Jangirala, M. Ahmad, An efficient mutual authentication framework for healthcare system in cloud computing, Journal of medical systems 42 (8) (2018) 142

17.      C.-T. Li, D.-H. Shih, C.-C. Wang, Cloud-assisted mutual authentication and privacy preservation protocol for telecare medical information systems, Computer methods and programs in biomedicine 157 (2018) 191–203

 




REFERENCES:

1.         C.-T. Li, D.-H. Shih, C.-C. Wang, Cloud-assisted mutual authentication and privacy preservation protocol for telecare medical information systems, Computer methods and programs in biomedicine 157 (2018) 191–203

2.         Kumar, V., Ahmad, M., Kumari, A., A Secure Elliptic Curve Cryptography Based Mutual Authentication Protocol for Cloud-assisted TMIS, Telematics and Informatics (2018).

3.         CSA, “The notorious nine cloud computing top threats in 2013,” The Notorious Nine Cloud Computing Top Threats in2013: pdf.

4.         Patra, M. R.; Das, R. K.; Padhy, R. P. CRHIS: Cloud Based Rural Healthcare Information System. In Proceedings of the 6th International Conference on Theory and Practice of Electronic Governance; ACM: Albany New York USA, 2012; pp 402–405.

5.         C.-L. Chen, T.-T. Yang, T.-F. Shih, A secure medical data exchange protocol based on cloud environment, Journal of medical systems 38 (9) (2014) 112

6.         C.-T. Li, C.-C. Lee, C.-C. Wang, T.-H. Yang, S.-J. Chen, Design flaws in a secure medical data exchange protocol based on cloud environments, in: International Conference on Algorithms and Architectures for Parallel Processing, Springer, 2015, pp. 435–444.

7.         R. Amin, S. H. Islam, G. Biswas, M. K. Khan, M. S. Obaidat, Design and analysis of an enhanced patient-server mutual authentication protocol for telecare medical information system, Journal of medical systems 39 (11) (2015) 137.

8.         Wu, F., and Xu, L., Security analysis and improvement of a privacy authentication scheme for telecare medical information systems. J. Med. Syst 37(4):1–9, 2012. doi:10.1007/s10916-013-9958-z

9.         Wen, F., and Guo, D., An improved anonymous authentication scheme for telecare medical information systems.J. Med. Syst. 38(5):26, 2014. doi:10.1007/s10916-014-0026-0

10.      Xu, X., Zhu, P., Wen, Q., Jin, Z., Zhang, H., and He, L., A secure and efficient authentication and key agreement scheme based on ecc for telecare medicine information systems. J. Med. Syst. 38(1):9994, 2013. doi:10.1007/s10916-013-9994-8

11.      D. He, N. Kumar, J. Chen, C.-C. Lee, N. Chilamkurti, S.-S. Yeo, Robust anonymous authentication protocol for health-care applications using wireless medical sensor networks, Multimedia Systems 21 (1) (2015) 49–60.

12.      J. Srinivas, D. Mishra, S. Mukhopadhyay, A mutual authentication framework for wireless medical sensor networks, Journal of medical systems 41 (5) (2017) 80

13.      C.-L. Chen, T.-T. Yang, M.-L. Chiang, T.-F. Shih, A privacy authentication scheme based on cloud for medical environment, Journal of medical systems 38 (11) (2014) 143.

14.      S.-Y. Chiou, Z. Ying, J. Liu, Improvement of a privacy authentication scheme based on cloud for medical environment, Journal of medical systems 40 (4) (2016) 101.

15.      P. Mohit, R. Amin, A. Karati, G. Biswas, M. K. Khan, A standard mutual authentication protocol for cloud computing based health care system, Journal of medical systems 41 (4) (2017) 50

16.      V. Kumar, S. Jangirala, M. Ahmad, An efficient mutual authentication framework for healthcare system in cloud computing, Journal of medical systems 42 (8) (2018) 142

17.      C.-T. Li, D.-H. Shih, C.-C. Wang, Cloud-assisted mutual authentication and privacy preservation protocol for telecare medical information systems, Computer methods and programs in biomedicine 157 (2018) 191–203



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Author/Editor Information

Dr. Sanjay Kango

Department of Mathematics, Neta Ji Subhash Chander Bose Memorial, Government Post Graduate College, Hamirpur Himachal Pradesh-177 005, INDIA