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A secure electronic medical record authorization system for smart device application in cloud computing environments

Abstract

As cloud computing technology matures, along with an increased application of distributed networks, increasingly larger amounts of data are being stored in the cloud, and are thus available for pervasive application. At the same time, current independent medical record systems tend to be inefficient, and most previous studies in this field fail to meet the security requirements of anonymity and unlinkability. Some proposed schemes are even vulnerable to malicious impersonation attacks. The scheme proposed in this study, therefore, combines public and private clouds in order to more efficiently and securely preserve and manage electronic medical records (EMR). In this paper, a new secure EMR authorization system is proposed, which uses elliptic curve encryption and public-key encryption, providing a health care system with both public and private cloud environments with a message authentication mechanism, allowing the secure sharing of medical resources. The analysis shows that the proposed scheme prevents known attacks, such as replay attacks, man-in-the-middle attacks and impersonation attacks, and provides user anonymity, unlinkability, integrity, non-repudiation, forward and backward security.

Introduction

Medical technology and health care have both improved significantly in recent years, as people have begun to eat more healthy and nutritious foods. According to the World Health Organization (WHO), the top two causes of death globally are ischemia heart disease and stroke [1]. Although knowledge and technology exist to treat and even cure many kinds of diseases, the time of diagnosis is also very important. Thus early access to comprehensive electronic medical record (EMR) data is crucial in combatting sudden onset diseases. To this end, this study proposes a unified database sharing data between multiple hospitals in order to increase access to such data, as well as the details available to health workers. Nowadays, the privacy of patients and the lack of security between one hospital and another are the top two issues in EMR sharing. In view of this, a positive step forward would be the development of a secure method for preserving and sharing of EMR data [2, 3]. This necessary requires proper data management via a medical resources sharing system. The combination of public and private clouds is an efficient way to achieve this [4]: if patients’ EMR data is stored in a private cloud, any doctor authorized to access that data can do so via authentication [5]. This method also ensures the consistency of health data [6].

The security of medical health care systems has been the topic of a number of recent studies. Chatterjee et al. [7] proposed a secure biometric-assisted access control protocol with an appropriate authentication structure that uses both a user password and biometric to provide better security as compared to other password-based authentication schemes. Amin et al. [8] suggested an anonymous user authentication framework to achieve patient unlinkability with anonymity preserving for electronic healthcare systems, and an anonymous user authentication scheme to monitor patient health using wireless medical sensor networks. Moreover, Islam et al. [9] presented a two-factor authentication protocol for an integrated patient data information system. Wazid et al. [10] suggested a three-factor authentication and key agreement framework with anonymity preservation for healthcare systems. Sutrala et al. [11] designed a secure RSA-assisted authentication protocol with patient anonymity. In 2014, Chen [12] proposed a cloud-based medical data exchange protocol that included privacy protection. However, Chen et al.’s scheme [12] did not offer a real-time-monitoring facility and non-disapproval conformation diagnosis. Chiou et al. [13] proposed an upgrade agreement to solve the shortcomings of Chen et al.’s scheme. Moreover, Mohit et al. [14] found in 2017 that Chiou et al.’s scheme [13] could not support patient anonymity, or ensure that even if a patient’s mobile device was stolen, the device could not be used for a malicious attack. Kumar et al. [15] proposed an effective mutual authentication framework for cloud computing healthcare systems. Li et al. [16] showed that Mohit et al.’s scheme [14] fails to protect patient anonymity, fails to protect patient accessibility, and lacks medical records. Li et al. proposed cloud-based authentication and privacy protection schemes.

After analyzing the related works, this study identified some flaws to be addressed. For example, the schemes proposed by Chiou et al. [13], Mohit et al. and Li et al. [16] did not support patient anonymity and unlinkability, nor did they support smart and convenient authorization, and they were vulnerable to impersonation attacks.

According to the above analyses, how to use a smart device to achieve a secure electronic medical sharing [17,18,19,20] is a worthy research issue for health care systems [21,22,23,24]. This study proposes a secure electronic medical record (EMR) authorization system for smart device applications in cloud computing environments [25,26,27,28]. The security requirements met by the proposed model include mutual authentication, anonymity, unlinkability, data integrity, data non-repudiation, and forward and backward security [29, 30] while being secure against known attacks, such as replay attacks, man-in-the-middle attacks and impersonation attacks [31, 32].

The remainder of this paper is arranged as follows: In “Preliminary” section, we gives a brief description of the security requirements and the elliptic curve group. In “The proposed scheme” section, we also describes the proposed scheme. Next, in “Security analysis” section, the security analyses are conducted. In “Discussion” section, the detailed results of the security comparison and computation cost are discussed. Finally, conclusions are offered in “Conclusions” section.

Preliminary

Security requirements

In this paper, we assume the following assumptions based on the threat model mentioned in [33,34,35,36]. Therefore, the following list is the security requirements for a secure electronic medical record authorization system for smart device applications in cloud computing environments.

Mutual authentication

The message receiver should authenticate the legality of the message sender during the information transmission process. Therefore, in a secure electronic medical record authorization system for smart device applications in cloud computing environments, each party should authenticate the legality of the other party. If each other’s legality of the two parties is confirmed, then it achieves mutual authentication.

User anonymity and unlinkability

Malicious attacks may also attempt to determine a person’s physical location by tracing their personal mobile reader. Thus, a secure electronic medical record authorization system for smart device applications in cloud computing environments must prevent such positional tracking.

Integrity

When the message transferred through an insecure network environment, it is susceptible to the malicious attack that the attacker modifies the original message. Thus, the message received by the receiver may not the original message sent from the sender. It ensures the integrity of the transmitted data and also protects against tampering in transmission.

Non-repudiation

The message receiver must be able to verify the legality of the message sender during the information transmission process. Once the receiver confirms that the message was sent from the sender, the sender can’t deny the message that he/she had sent. The sender uses his/her private key to sign the message, and the receiver can verify the digital signature from the sender.

Forward and backward security

The session key is established between the message sender and the message receiver. If it is compromised by an attacker at any point, he/she may use the session key for future communications, or use it to obtain previous messages.

Confidentiality

If the data is intercepted by a malicious attacker during transmission, the unencrypted data content will be exposed, which violates the principle of confidentiality of information security. In order to prevent disclosure of data, sensitive data must be encrypted during transmission and storage.

Availability

A secure and reliable information system must use data encryption and identity verification technology, in order to ensure that data is not accessed by illegal users. Simultaneously, it must be ensured that legitimate users can correctly obtain the plain text of the transmitted message within an acceptable time, which meets the availability of the system.

Prevent replay attack

The attacker can intercept the messages transmitted between the sender and the receiver by malicious attacks. Then, the attacker impersonates a legitimate transmitter so as to send the same messages again to the intended receiver. The situation causes a serious security risk, and that must be prevented.

Prevent man-in-the-middle attack

This attack means the attacker intercepts the message during the communication phase and counterfeits the message. Then, the attacker sends this counterfeit message to other communication parties. The situation causes a serious security risk, and that must be prevented in a secure electronic medical record authorization system for smart device applications in cloud computing environments.

Prevent impersonation attack

This attack means an illegal user wants to disguise as the legal user to log into the server or to communicate with other legal users. The situation causes a serious security risk, thus a secure electronic medical record authorization system for smart device applications in cloud computing environments must prevent such attacks.

Elliptic curve group

\(E/F_{q}\) is an elliptic curve defined over a prime finite field \(F_{q}\). \(P\) is a generator for a cyclic additive group of composite order \(q\) [37]. \(G\) is a cyclic additive group of the composite order \(q\). A point on \(E/F_{q}\) together with an extra point \(Q\) is called the point at infinity from a group \(G = \{ (x,y):x,y \in E/F_{q} \} \cup \{ Q\}\). The scalar multiplication over \(E/F_{q}\) is calculated by the Eq. 1 as:

$$tP = P + P + \cdots + P,\;t\quad {\text{times}}.$$
(1)

Computational Diffie–Hellman (CDH) problem and Decisional Diffie–Hellman (DDH) problem exist for the elliptic curve group. The details are as follows:

Computational Diffie–Hellman (CDH) problem

\(a,b \in R\), \(Z \times q\) and \(P\) are the generators of \(G\). Given \(aP\) and \(bP\), the value \(abP\) can be computed.

Decisional Diffie–Hellman (DDH) problem

\(a,b,c \in R\), \(Z \times q\) and \(P\) are the generator of \(G\). Given \(aP\), \(bP\), and \(cP\), the value \(abP\) can be computed. Confirming that \(cP = abP\) is equal to confirming that \(c = ab\bmod q\).

The proposed scheme

System architecture

This study proposes a distributed EMR storage and sharing scheme. Figure 1 shows the proposed system architecture. There are four parties in the proposed system, including the patient, the doctor, the hospital’s private cloud, and the public cloud. Each party is described in detail below.

Fig. 1
figure1

The architecture of the proposed distributed EMR storage and sharing scheme

  1. 1.

    Patient (P): The patient takes a smart device when they visit a doctor. They authenticate their identity with the smart device by entering their biometric password.

  2. 2.

    Doctor (D): The doctor verifies the EMR of the patient and the legality of the hospital’s private cloud. In the EMR search phase, the doctor collects messages from both sides and then makes a professional diagnosis.

  3. 3.

    Hospital’s private cloud (HPC): The hospital’s private cloud is the cloud in which the patient’s EMR is stored. It authenticates the legality of the doctor and then provides them with the correct EMR.

  4. 4.

    Public cloud (PC): A public cloud plays the role of generating secret keys. Every party gets a secret parameter from the public cloud during the registration phase. It stores the index of the patient’s medical data during the EMR search phase. By checking the secret key given by the public cloud, the doctor can authenticate their patients. The public cloud and the private cloud form a medical union cloud. The medical union cloud achieves EMR sharing by authenticating each other.

The following is a description of the four steps process of a patient visiting a doctor:

Step 1::

All parties are registered to the public cloud. The public cloud calculates secret keys by n elliptic curve. The cloud then issues the secret keys to parties.

Step 2::

The patient visits the doctor. The doctor authenticates the patient, and the patient sends their biomedical signal to the doctor.

Step 3::

The doctor receives the index of the patient from the public cloud and then obtains the EMR from the hospital’s private cloud.

Step 4::

The doctor makes a diagnosis according to the EMR and the patient’s current condition. Finally, the doctor sends the diagnosis messages to the public cloud.

Notation

The notations used in this paper are shown in Table 1.

Table 1 Notation

Registration phase

All parties register in the cloud to get the secret key. The registration phase is divided into three parts which are the patient, the hospital’s private cloud, and the doctor register with the public cloud.

The patient registers with the public cloud

This process consists of three steps, as shown in Fig. 2a.

Fig. 2
figure2

a Flow chart of the patient registering with the public cloud, b flow chart of the hospital’s private cloud registering with the public cloud

Step 1::

The patient selects an identity \(ID_{P}\) and a biometric password \(B_{P}\). They then send both to the public cloud via a secure channel.

Step 2::

When the public cloud receives the message, it selects a random number \(r_{1}\), and uses it to multiply by the generator, the elliptic group, \(P\) to compute \(R_{P1}\) by using the Eq. 2, and then to compute \(S_{P}\) by using the Eq. 3, as follows:

$$R_{P1} = r_{1} P,$$
(2)
$$S_{P} = r_{1} + H \left(ID_{P} ||B_{P} ||R_{P1} \right)s.$$
(3)

The public cloud then sends \(R_{P1}\) and \(S_{P}\) to the patient via a secure channel.

Step 3::

Upon receiving the message from the public cloud, the patient verifies by using the Eq. 4 as follows:

$$S_{P} P\mathop = \limits^{?} R_{P1} + H \left(ID_{P} ||B_{P} ||R_{P1} \right)PK.$$
(4)

If it holds, then the patient stores \(\left(R_{P1} ,S_{P} \right)\).

The hospital’s private cloud registers with the public cloud

This process consists of three steps, as illustrated in Fig. 2b.

Step 1::

The hospital’s private cloud selects an identity \(ID_{HPC}\), and then sends its identity \(ID_{HPC}\) to the public cloud via a secure channel.

Step 2::

When the public cloud receives the message, it selects a random number \(r_{2}\) and uses it with the generator for the elliptic group \(P\) to compute \(R_{HPC1}\) by using the Eq. 5. The public cloud computes \(S_{HPC}\) by using the Eq. 6. \(R_{HPC1}\) and \(S_{HPC}\) as follows:

$$R_{HPC1} = r_{2} P.$$
(5)
$$S_{HPC} = r_{2} + h\left(ID_{HPC} ||R_{HPC1} \right)s.$$
(6)

The public cloud sends \(R_{HPC1}\) and \(S_{HPC}\) to the hospital’s private cloud via a secure channel.

Step 3::

Upon receiving the message, the hospital’s private cloud verifies by using the Eq. 7 as follows:

$$S_{HPC} P\mathop = \limits^{?} R_{HPC1} + h \left(ID_{HPC} ||R_{HPC1} \right)PK.$$
(7)

If it holds, then the hospital’s private cloud stores \(\left(R_{HPC1} ,S_{HPC} \right)\).

The doctor registers with the public cloud

This process also consists of three steps, as shown in Fig. 3.

Fig. 3
figure3

The doctor registers with the public cloud

Step 1::

The doctor selects an identity \(ID_{D}\) and their doctor’s certificate \(Cert_{D}\) and s both to the public cloud via a secure channel.

Step 2::

When the public cloud receives the messages, it verifies whether \(Cert_{D}\) is legal. If \(Cert_{D}\) is illegal, the public cloud will terminate the registration phase. If it is legal, it selects a random number \(r_{3}\) and uses it multiply by the generator for the elliptic group \(P\) to compute \(R_{D1}\) by using the Eq. 8, and to then compute \(S_{D}\) by using the Eq. 9 as follows:

$$R_{D1} = r_{3} P,$$
(8)
$$S_{D} = r_{3} + H \left(ID_{D} ||Cert_{D} ||R_{D1} \right)s.$$
(9)

The public cloud sends \(R_{D1}\) and \(S_{D}\) to the doctor via a secure channel.

Upon receiving the message from the public cloud, the doctor verifies by using the Eq. 10 as follows:

$$S_{D} P\mathop = \limits^{?} R_{D1} + h \left(ID_{D} ||Cert_{D} ||R_{D1} \right)PK.$$
(10)

If it holds, then the doctor stores \(\left(R_{D1} ,S_{D} \right)\).

Patient visiting doctor (consultation) phase

In this phase, the patient goes to the doctor for a medical consultation. They bring their smart device with them in order to first authenticate the doctor. This section describes how the patient logs into the medical system, and how they achieve authentication with the doctor. This phase consists of four steps, as shown in Fig. 4.

Fig. 4
figure4

Patient visiting doctor phase

The patient inputs their biometric password \(B_{P}\) and selects a random number \(r_{5}\), and uses \(r_{5}\) and \(P\) to compute \(R_{P2}\) by using the Eq. 11 as follows:

$$R_{P2} = r_{5} P.$$
(11)

He/She then uses the doctor’s public key \(PUK_{D}\) to encrypt \(\left(ID_{P} ||B_{P} ||R_{P1} ||R_{P2} ||T_{P1} \right)\) into \(C_{P1}\) by using the Eq. 12 as follows.

$$C_{P1} = E_{{PUK_{D} }} \left(ID_{P} ||B_{P} ||R_{P1} ||R_{P2} ||T_{P1} \right).$$
(12)

The patient then uses their private key \(PRK_{P}\) to generate their signature \(Sig_{P1}\) by using the Eq. 13 as follows:

$$Sig_{P1} = S_{{PRK_{P} }} \left(R_{P1} ||ID_{P} ||R_{P2} ||B_{P} ||PK||T_{P1} \right).$$
(13)

Finally, the patient sends \(\left(C_{P1} ,Sig_{P1} ,T_{P1} \right)\) to the doctor, where \(T_{P1}\) is the timestamp.

Step 1::

Upon receiving \(\left(C_{P1} ,Sig_{P1} ,T_{P1} \right)\), the doctor checks if \(T_{P1}^{\prime } - T_{P1} \le \Delta T\). If \(\Delta T\) is not valid, the doctor will terminate the communication. The doctor then decrypts \(C_{P1}\) and verifies \(Sig_{P1}\) by using the Eqs. 14 and 15 as follows:

$$\left(ID_{P} ||B_{P} ||R_{P1} ||R_{P2} ||T_{P1} ) = D_{{PRK_{D} }} (C_{P1} \right),$$
(14)
$$\left(R_{P1} ||ID_{P} ||R_{P2} ||B_{P} ||PK||T_{P1} )\mathop = \limits^{?} V_{{PUK_{P} }} (Sig_{P1} \right).$$
(15)

He/She then uses the random number \(r_{6}\) with the generator for the elliptic group \(P\) to compute \(R_{D2}\), and calculate a session key by using the Eqs. 16 and 17 as follows:

$$R_{D2} = r_{6} P,$$
(16)
$$SEK_{1} = h \left((S_{D} R_{P2} + r_{6} (R_{P1} + H(ID_{P} ||B_{P} ||R_{P1} )PK))||r_{6} R_{P2} \right).$$
(17)

The doctor uses patient’s public key \(PUK_{P}\) to encrypt \(\left(ID_{D} ||Cert_{D} ||R_{D1} ||R_{D2} ||SEK_{1} ||T_{D1} \right)\) into \(C_{D1}\) by using the Eq. 18 as follows:

$$C_{D1} = E_{{PUK_{P} }} \left(ID_{D} ||Cert_{D} ||R_{D1} ||R_{D2} ||SEK_{1} ||T_{D1} \right),$$
(18)

then uses their private key \(PRK_{D}\) to generate their signature \(Sig_{D1}\) by using the Eq. 19  as follows:

$$Sig_{D1} = S_{{PRK_{D} }} \left(R_{D2} ||ID_{D} ||T_{D1} ||Cert_{D} ||SEK_{1} ||PK \right).$$
(19)

Finally, the doctor sends \(\left(C_{D1} ,Sig_{D1} ,T_{D1} \right)\) to the patient. Where \(T_{D1}\) is the timestamp.

Step 2::

Upon receiving \(\left(C_{D1} ,Sig_{D1} ,T_{D1} \right)\), the patient checks if \(T_{D1}^{\prime } - T_{D1} \le \Delta T\). If \(\Delta T\) is not valid, the communication is terminated. The patient decrypts \(C_{D1}\) by using the Eq. 20 as follows:

$$\left(ID_{D} ||Cert_{D} ||R_{D1} ||R_{D2} ||SEK_{1} ||T_{D1} ) = D_{{PRK_{P} }} (C_{D1} \right),$$
(20)

and verifies if \(Cert_{D}\) is legal or not. And then the patient verifies \(Sig_{D1}\) by using the Eq. 21 as follows:

$$\left(R_{D2} ||ID_{D} ||T_{D1} ||Cert_{D} ||SEK_{1} ||PK)\mathop = \limits^{?} V_{{PUK_{P} }} (Sig_{D1} \right).$$
(21)

The patient then calculates a session key and verifies it by using the Eq. 22 as follows:

$$SEK_{1} \mathop = \limits^{?} h \left((S_{P} R_{D2} + r_{5} (R_{D1} + h(ID_{D} ||R_{D1} )PK))||r_{5} R_{D2} \right)$$
(22)

and uses the session key \(SEK_{1}\) to encrypt \((M_{SD} ,ID_{P} ,T_{P2} )\) into \(C_{P2}\) by using the Eq. 23 as follows:

$$C_{P2} = E_{{SEK_{1} }} \left(M_{SD} ,ID_{P} ,T_{P2} \right).$$
(23)

Finally, the patient sends \(C_{P2}\) and \(T_{P2}\) to the doctor.

Step 3::

Upon receiving \(\left(C_{P2} ,T_{P2} \right)\), the doctor checks if the timestamp \(T_{P2}^{\prime } - T_{P2} \le \Delta T\), then decrypts \(C_{P2}\) via session key \(SEK_{1}\) by using the Eq. 24 as follows:

$$\left(M_{SD} ,ID_{P} ,T_{P2} ) = D_{{SEK_{1} }} (C_{P2} \right).$$
(24)

EMR search phase

The purpose of this phase is to search the EMR of the patient for information relevant to the current diagnosis process. The doctor contacts the hospital’s private cloud to obtain the EMR of the patient, and thus needs to be authenticated with the private cloud. This phase consists of seven steps, as shown in Fig. 5.

Fig. 5
figure5

EMR search phase

Step 1::

The doctor uses the public key of the public cloud \(PUK_{PC}\) to encrypt \(\left(ID_{P} ||T_{D2} ||ID_{D} ||Cert_{D} ||ID_{DE} \right)\) into \(C_{D2}\) by using the Eq. 25 as follows:

$$C_{D2} = E_{{PUK_{PC} }} \left(ID_{P} ||T_{D2} ||ID_{D} ||Cert_{D} ||ID_{DE} \right).$$
(25)

He/She then uses their private key to generate their signature \(Sig_{D2}\) by using the Eq. 26 as follows:

$$Sig_{D2} = S_{{PRK_{D} }} \left(S_{D} ||T_{D2} ||ID_{P} ||ID_{DE} ||ID_{D} \right).$$
(26)

Finally, the doctor sends \(\left(C_{D2} ,Sig_{D2} ,T_{D2} \right)\) to the public cloud.

Upon receiving \(\left(C_{D2} ,Sig_{D2} ,T_{D2} \right)\), the public cloud checks if \(T_{D2}^{\prime } - T_{D2} \le \Delta T\), then the public cloud decrypts \(C_{D2}\) and verifies whether \(Cert_{D}\) is legal by using the Eq. 27 :

$$\left(ID_{P} ||T_{D2} ||ID_{D} ||Cert_{D} ||ID_{DE} ) = D_{{PRK_{PC} }} (C_{D2} \right).$$
(27)

The public cloud also uses the doctor’s public key to verify the signature \(Sig_{D2}\) by using the Eq. 28 as follows:

$$\left(S_{D} ||T_{D2} ||ID_{P} ||ID_{DE} ||ID_{D} )\mathop = \limits^{?} V_{{PUK_{D} }} (Sig_{D2} \right).$$
(28)

It also verifies whether \(Cert_{D}\) is legal. Then the public cloud searches the patient’s index record in its database according to \(ID_{P}\) and \(ID_{DE}\). After this, it uses the doctor’s public key \(PUK_{D}\) to encrypt \(\left(ID_{HPC} ||ID_{DE} ||T_{C} \right)\) into \(C_{C}\) by using the Eq. 29 as follows, where \(ID_{DE}\) is the hospital department’s identity.

$$C_{C} = E_{{PUK_{D} }} (ID_{HPC} ||ID_{DE} ||T_{C} ).$$
(29)

The public cloud then uses its private key \(PRK_{C}\) to generate the public cloud signature \(Sig_{C}\) by using the Eq. 30 as follows:

$$Sig_{C} = S_{{PRK_{C} }} (ID_{DE} ||S_{SD} ||ID_{HPC} ||T_{C} ).$$
(30)

After this, the public cloud stores \((h(ID_{P} ||ID_{DE} ),(ID_{CHPC} ||ID_{D} ) \oplus h(s))\).

Finally, the public cloud sends \((C_{C} ,Sig_{C} ,T_{C} )\) to the doctor.

Step 2::

Upon receiving \((C_{C} ,Sig_{C} ,T_{C} )\), the doctor checks if \(T_{C}^{\prime } - T_{C} \le \Delta T\). The doctor then decrypts \(C_{C}\) and verifies \(Sig_{C}\) by using the Eqs. 31 and 32 as follows:

$$(ID_{HPC} ||ID_{DE} ||T_{C} ) = D_{{PRK_{D} }} (C_{C} ),$$
(31)
$$(ID_{DE} ||S_{SD} ||ID_{HPC} ||T_{C} )\mathop = \limits^{?} V_{{PUK_{C} }} (Sig_{C} ).$$
(32)

Then the doctor uses the random number \(r_{7}\) with the generator for the elliptic group \(P\) to compute \(R_{D3}\) by using the Eq. 33. They then use the public key of the hospital’s private cloud \(PUK_{HPC}\) to encrypt \((Cert_{D} ||T_{D3} ||ID_{D} ||R_{D3} ||R_{D1} )\) into \(C_{D3}\) by using the Eq. 34 as follows:

$$R_{D3} = r_{7} P,$$
(33)
$$C_{D3} = E_{{PUK_{HPC} }} (Cert_{D} ||T_{D3} ||ID_{D} ||R_{D3} ||R_{D1} ).$$
(34)

The doctor then uses their private key to generate their signature \(Sig_{D3}\) by using the Eq. 35 as follows:

$$Sig_{D3} = S_{{PRK_{D} }} (PK||T_{D3} ||ID_{P} ||R_{D3} ||R_{D1} ).$$
(35)

Finally, the doctor sends \((C_{D3} ,Sig_{D3} ,T_{D3} )\) to the hospital’s private cloud.

Step 3::

Upon receiving \((C_{D3} ,Sig_{D3} ,T_{D3} )\), the hospital’s private cloud checks if \(T_{D3}^{\prime } - T_{D3} \le \Delta T\). It then decrypts \(C_{D3}\) by using the Eq. 36 as follows:

$$(Cert_{D} ||T_{D3} ||ID_{D} ||R_{D3} ||R_{D1} ) = D_{{PRK_{HPC} }} (C_{D3} ),$$
(36)

and verifies whether \(Cert_{D}\) is legal. It then verifies \(Sig_{D3}\) by using the Eq. 37 as follows:

$$(PK||T_{D3} ||ID_{P} ||R_{D3} ||R_{D1} )\mathop = \limits^{?} V_{{PUK_{D} }} (Sig_{D3} ).$$
(37)

The private cloud then uses the random number \(r_{8}\) with the generator for the elliptic group \(P\) to compute \(R_{HPC2}\), and calculates a session key by using the Eqs. 38 and 39 as follows:

$$R_{HPC2} = r_{8} P,$$
(38)
$$SEK_{2} = h((S_{HPC} R_{D3} + r_{8} (R_{D1} + h(ID_{D} ||Cert_{D} ||R_{D1} )PK))||r_{8} R_{D3} ).$$
(39)

It then uses the doctor’s public key \(PUK_{D}\) to encrypt \((ID_{HPC} ||SEK_{2} ||T_{HPC1} ||R_{HPC2} )\) into \(C_{HPC1}\) by using the Eq. 40 as follows:

$$C_{HPC1} = E_{{PUK_{D} }} (ID_{HPC} ||SEK_{2} ||T_{HPC1} ||R_{HPC2} ).$$
(40)

It uses the private cloud’s own private key to generate its signature \(Sig_{HPC1}\) by using the Eq. 41 as follows:

$$Sig_{HPC1} = S_{{PRK_{HPC} }} (PK||T_{HPC1} ||ID_{HPC} ).$$
(41)

Finally, the private cloud sends \((C_{HPC1} ,Sig_{HPC1} ,T_{HPC1} )\) to the doctor.

Step 4::

Upon receiving \((C_{HPC1} ,Sig_{HPC1} ,T_{HPC1} )\), the doctor checks if \(T_{HPC1}^{\prime } - T_{HPC1} \le \Delta T\), decrypts \(C_{HPC1}\), and verifies \(Sig_{HPC1}\) by using the Eqs. 42 and 43 as follows:

$$(ID_{HPC} ||SEK_{2} ||T_{HPC1} ||R_{HPC2} ) = D_{{PRK_{D} }} (C_{HPC1} ),$$
(42)
$$(PK||T_{HPC1} ||ID_{HPC} )\mathop = \limits^{?} S_{{PRK_{HPC} }} (Sig_{HPC1} ).$$
(43)

He/She verifies the session key by using the Eq. 44 as follows:

$$SEK_{2} \mathop = \limits^{?} h((S_{D} R_{HPC2} + r_{7} (R_{HPC1} + h(ID_{HPC} ||R_{HPC1} )PK))||r_{7} R_{HPC2} ),$$
(44)

and then use the session key \(SEK_{2}\) to encrypt \((ID_{P} ||ID_{D} ||T_{D4} ||Cert_{D} )\) into \(C_{D4}\) by using the Eq. 45 as follows:

$$C_{D4} = E_{{SEK_{2} }} (ID_{P} ||ID_{D} ||T_{D4} ||Cert_{D} ).$$
(45)

Finally, the doctor sends \((C_{D4} ,T_{D4} )\) to the private cloud.

Step 5::

Upon receiving \(C_{D4}\), the private cloud checks the timestamps to determine if \(T_{D4}^{\prime } - T_{D4} \le \Delta T\), and then decrypts \(C_{D4}\) by using the Eq. 46 as follows:

$$(ID_{P} ||ID_{D} ||T_{D4} ||Cert_{D} ) = D_{{SEK_{2} }} (C_{D4} ).$$
(46)

It verifies whether \(Cert_{D}\) is legal, and then uses the session key \(SEK_{2}\) to encrypt \((M_{EMR} ||T_{HPC2} )\) into \(C_{HPC2}\) by using the Eq. 47 as follows:

$$C_{HPC2} = E_{{SEK_{2} }} (M_{EMR} ||T_{HPC2} ).$$
(47)

Finally, the hospital’s private cloud sends \((C_{HPC2} ,T_{HPC2} )\) to the doctor.

Step 6::

When the doctor receives \(C_{HPC2}\), they check the timestamp to determine if \(T_{HPC2}^{\prime } - T_{HPC2} \le \Delta T\), and then decrypt \(C_{HPC2}\) by using the Eq. 48 as follows:

$$(M_{EMR} ||T_{HPC2} ) = D_{{SEK_{2} }} (C_{HPC2} ).$$
(48)

Diagnosis phase

Once the doctor receives the patient’s EMR and the sensing message \(M_{SD}\) from the patient’s smart device, the doctor uses the patient’s EMR from the hospital’s private cloud and the \(M_{SD}\) to make a professional medical diagnosis. After this, they inform the patient of the diagnosis result. Figure 6 is the diagnosis phase of the proposed scheme.

Fig. 6
figure6

Diagnosis phase

First, the doctor uses the session key \(SEK_{1}\) to encrypt \((M_{DINF} ||Cert_{D} ||T_{D5} )\) into \(C_{D5}\) by using the Eq. 49 as follows:

$$C_{D5} = E_{{SEK_{1} }} (M_{DINF} ||Cert_{D} ||T_{D5} ).$$
(49)

Then the doctor sends \((C_{D5} ,T_{D5} )\) to the patient.

Step 1::

When the patient receives \((C_{D5} ,T_{D5} )\), the patient checks the timestamps to determine if \(T_{D5}^{\prime } - T_{D5} \le \Delta T\), then decrypts CD5 by using the Eq. 50 as follows:

$$(M_{DINF} ||Cert_{D} ||T_{D5} ) = D_{{SEK_{1} }} (C_{D5} ).$$
(50)

The patient then verifies that \(Cert_{D}\) is legal.

Security analysis

This section analyzes the security issues of mutual authentication, anonymity, unlinkability, data integrity, data non-repudiation, and forward and backward security in the proposed scheme. It also analyzes the proposed scheme’s security against replay attacks, man-in-the-middle attacks, and impersonation attacks.

Mutual authentication

There are four parties in the proposed scheme, namely the patient, the hospital’s private cloud, the public cloud, and the doctor. This paper uses BAN logic [38] to prove that the proposed scheme achieves mutual authentication.

Goals

The following goals must be derived step by step so that all parties are able to authenticate each other. Goals are listed as G1 to G16 as follows:

G1\(D| \equiv D\mathop \leftrightarrow \limits^{{SEK_{1} }} P\)
G2\(D| \equiv P| \equiv D\mathop \leftrightarrow \limits^{{SEK_{1} }} P\)
G3\(P| \equiv D\mathop \leftrightarrow \limits^{{SEK_{1} }} P\)
G4\(P| \equiv D| \equiv D\mathop \leftrightarrow \limits^{{SEK_{1} }} P\)
G5\(HPC| \equiv HPC\mathop \leftrightarrow \limits^{{SEK_{2} }} D\)
G6\(HPC| \equiv D| \equiv HPC\mathop \leftrightarrow \limits^{{SEK_{2} }} D\)
G7\(D| \equiv HPC\mathop \leftrightarrow \limits^{{SEK_{2} }} D\)
G8\(D| \equiv HPC| \equiv HPC\mathop \leftrightarrow \limits^{{SEK_{2} }} D\)
G9\(D| \equiv ID_{P}\)
G10\(D| \equiv P| \equiv ID_{P}\)
G11\(P| \equiv ID_{D}\)
G12\(P| \equiv D| \equiv ID_{D}\)
G13\(HPC| \equiv ID_{D}\)
G14\(HPC| \equiv D| \equiv ID_{D}\)
G15\(D| \equiv ID_{HPC}\)
G16\(D| \equiv HPC| \equiv ID_{HPC}\)

Messages delivered between parties

The messages are numbered for the purposes of proving the proposed scheme, as follows:

M1\((\{ R_{P1} ||ID_{P} ||R_{P2} ||B_{P} ||PK||T_{P1} \}_{{PRK_{P} }} ,\{ M_{SD} ||ID_{P} ||T_{P2} \}_{{SEK_{1} }} )\)
M2\((\{ R_{D2} ||ID_{D} ||T_{D1} ||Cert_{D} ||SEK_{1} ||PK\}_{{PRK_{D} }} ,\{ M_{DINF} ||Cert_{D} ||T_{D5} \}_{{SEK_{1} }} )\)
M3\((\{ PK||T_{D3} ||ID_{P} ||R_{D3} ||R_{D1} \}_{{PRK_{D} }} ,\{ ID_{P} ||ID_{D} ||T_{D4} ||Cert_{D} \}_{{SEK_{2} }} )\)
M4\((\{ PK||T_{HPC1} ||ID_{HPC} \}_{{PRK_{HPC} }} ,\{ M_{EMR} ||T_{HPC2} \}_{{SEK_{2} }} )\)

Assumptions

The following assumptions are made to help achieve the goals:

A1\(D| \equiv \# (T_{P1} )\)
A2\(P| \equiv \# (T_{P1} )\)
A3\(D| \equiv \# (T_{D1} )\)
A4\(P| \equiv \# (T_{D1} )\)
A5\(HPC| \equiv \# (T_{D3} )\)
A6\(D| \equiv \# (T_{D3} )\)
A7\(HPC| \equiv \# (T_{HPC1} )\)
A8\(D| \equiv \# (T_{HPC1} )\)
A9\(D| \equiv \# SEK_{1}\)
A10\(P| \equiv \# SEK_{1}\)
A11\(HPC| \equiv \# SEK_{2}\)
A12\(D| \equiv \# SEK_{2}\)
A13\(P| \equiv |\mathop \to \limits^{{PUK_{P} }} D\)
A14\(D| \equiv |\mathop \to \limits^{{PUK_{P} }} D\)
A15\(P| \equiv |\mathop \to \limits^{{PUK_{D} }} P\)
A16\(D| \equiv |\mathop \to \limits^{{PUK_{D} }} P\)
A17\(D| \equiv |\mathop \to \limits^{{PUK_{OHPC} }} D\)
A18\(HPC| \equiv |\mathop \to \limits^{{PUK_{OHPC} }} D\)
A19\(D| \equiv |\mathop \to \limits^{{PUK_{D} }} HPC\)
A20\(HPC| \equiv |\mathop \to \limits^{{PUK_{D} }} HPC\)
A21\(D| \equiv P| \Rightarrow D\mathop \leftrightarrow \limits^{{SEK_{1} }} P\)
A22\(P| \equiv D| \Rightarrow D\mathop \leftrightarrow \limits^{{SEK_{1} }} P\)
A23\(HPC| \equiv D| \Rightarrow HPC\mathop \leftrightarrow \limits^{{SEK_{2} }} D\)
A24\(D| \equiv HPC| \Rightarrow HPC\mathop \leftrightarrow \limits^{{SEK_{2} }} D\)
A25\(D| \equiv P| \Rightarrow ID_{P}\)
A26\(P| \equiv D| \Rightarrow ID_{D}\)
A27\(HPC| \equiv D| \Rightarrow ID_{D}\)
A28\(D| \equiv HPC| \Rightarrow ID_{HPC}\)

The doctor authenticates the patient

The doctor’s authentication of the patient can be proved by the assumptions and BAN logic, as follows:

By M1 and the seeing rule, the following Statement 1 can be derived:

$$({\text{Statement}}\;1)\quad D \triangleleft (\{ R_{P1} ||ID_{P} ||R_{P2} ||B_{P} ||PK||T_{P1} \}_{{PRK_{P} }} ,\{ M_{SD} ||ID_{P} ||T_{P2} \}_{{SEK_{1} }} ).$$

By A1, A2 and the freshness rule, the following Statement 2 can be derived:

$$({\text{Statement}}\;2)\quad D| \equiv \# (\{ R_{P1} ||ID_{P} ||R_{P2} ||B_{P} ||PK||T_{P1} \}_{{PRK_{P} }} ,\{ M_{SD} ||ID_{P} ||T_{P2} \}_{{SEK_{1} }} ).$$

By Statement 1, A9, A13, A14 and the message meaning rule, the following Statement 3 can be derived:

$$({\text{Statement}}\;3)\quad D| \equiv P|\sim \# (\{ R_{P1} ||ID_{P} ||R_{P2} ||B_{P} ||PK||T_{P1} \}_{{PRK_{P} }} ,\{ M_{SD} ||ID_{P} ||T_{P2} \}_{{SEK_{1} }} ).$$

By Statement 2, Statement 3 and the verification rule, the following Statement 4 can be derived:

$$({\text{Statement}}\;4)\quad D| \equiv P| \equiv (\{ R_{P1} ||ID_{P} ||R_{P2} ||B_{P} ||PK||T_{P1} \}_{{PRK_{P} }} ,\{ M_{SD} ||ID_{P} ||T_{P2} \}_{{SEK_{1} }} ).$$

By Statement 4 and the belief rule, the following Statement 5 can be derived:

$$({\text{Statement}}\;5)\quad D| \equiv P| \equiv D\mathop \leftrightarrow \limits^{{SEK_{1} }} P.$$

By Statement 4, A21 and the jurisdiction rule, the following Statement 6 can be derived:

$$({\text{Statement}}\;6)\quad D| \equiv D\mathop \leftrightarrow \limits^{{SEK_{1} }} P.$$

By Statement 6 and the belief rule, the following Statement 7 can be derived:

$$({\text{Statement}}\;7)\quad D| \equiv P| \equiv ID_{P} .$$

By Statement 6, A25 and the belief rule, the following Statement 8 can be derived:

$$({\text{Statement}}\;8)\quad D| \equiv ID_{P} .$$

According to Statement 6 and Statement 8, we prove that the doctor can surely authenticate the patient by using the Eq. 15 as follows:

$$(R_{P1} ||ID_{P} ||R_{P2} ||B_{P} ||PK||T_{P1} )\mathop = \limits^{?} V_{{PUK_{P} }} (Sig_{P1} ).$$
(15)

The patient authenticates the doctor

The patient’s authentication of the doctor can be shown by the assumptions and BAN logic, as follows:

By M2 and the seeing rule, the following Statement 9 can be derived:

$$({\text{Statement}}\;9)\quad P \triangleleft (\{ R_{D2} ||ID_{D} ||T_{D1} ||Cert_{D} ||SEK_{1} ||PK\}_{{PRK_{D} }} ,\{ M_{DINF} ||Cert_{D} ||T_{D5} \}_{{SEK_{1} }} ).$$

By A3, A4 and the freshness rule, the following Statement 10 can be derived:

$$({\text{Statement}}\;10)\quad P| \equiv \# (\{ R_{D2} ||ID_{D} ||T_{D1} ||Cert_{D} ||SEK_{1} ||PK\}_{{PRK_{D} }} ,\{ M_{DINF} ||Cert_{D} ||T_{D5} \}_{{SEK_{1} }} ).$$

By Statement 9, A10, A15, A16 and the message meaning rule, the following Statement 11 can be derived:

$$({\text{Statement}}\;11)\quad P| \equiv D|\sim \# (\{ R_{D2} ||ID_{D} ||T_{D1} ||Cert_{D} ||SEK_{1} ||PK\}_{{PRK_{D} }} ,\{ M_{DINF} ||Cert_{D} ||T_{D5} \}_{{SEK_{1} }} ).$$

By Statement 10, Statement 11 and the verification rule, the following Statement 12 can be derived:

$$({\text{Statement}}\;12)\quad P| \equiv D| \equiv (\{ R_{D2} ||ID_{D} ||T_{D1} ||Cert_{D} ||SEK_{1} ||PK\}_{{PRK_{D} }} ,\{ M_{DINF} ||Cert_{D} ||T_{D5} \}_{{SEK_{1} }} ).$$

By Statement 12 and the belief rule, the following Statement 13 can be derived:

$$({\text{Statement}}\;13)\quad P| \equiv D| \equiv D\mathop \leftrightarrow \limits^{{SEK_{1} }} P.$$

By Statement 13, A22 and the jurisdiction rule, the following Statement 14 can be derived:

$$({\text{Statement}}\;14)\quad P| \equiv D\mathop \leftrightarrow \limits^{{SEK_{1} }} P.$$

By Statement 14 and the belief rule, the following Statement 15 can be derived:

$$({\text{Statement}}\;15)\quad P| \equiv D| \equiv ID_{D} .$$

By Statement 15, A26 and the belief rule, the following Statement 16 can be derived:

$$({\text{Statement}}\;16)\quad P| \equiv ID_{D} .$$

According to Statements 14 and 16, the patient’s authentication of the doctor can be proved by using the Eq. 21 as follows:

$$(R_{D2} ||ID_{D} ||T_{D1} ||Cert_{D} ||SEK_{1} ||PK)\mathop = \limits^{?} V_{{PUK_{P} }} (Sig_{D1} ).$$
(21)

The hospital’s private cloud authenticates the doctor

The private cloud’s authentication of the doctor can be shown by the assumptions and BAN logic as follows:

By M3 and the seeing rule, the following Statement 17 can be derived:

$$({\text{Statement}}\;17)\quad HPC \triangleleft (\{ PK||T_{D3} ||ID_{P} ||R_{D3} ||R_{D1} \}_{{PRK_{D} }} ,\{ ID_{P} ||ID_{D} ||T_{D4} ||Cert_{D} \}_{{SEK_{2} }} ).$$

By A5, A6 and the freshness rule, the following Statement 18 can be derived:

$$({\text{Statement}}\;18)\quad HPC| \equiv \# (\{ PK||T_{D3} ||ID_{P} ||R_{D3} ||R_{D1} \}_{{PRK_{D} }} ,\{ ID_{P} ||ID_{D} ||T_{D4} ||Cert_{D} \}_{{SEK_{2} }} ).$$

By Statement 17, A11, A17, A18 and the message meaning rule, the following Statement 19 can be derived:

$$({\text{Statement}}\;19)\quad HPC| \equiv D|\sim \# (\{ PK||T_{D3} ||ID_{P} ||R_{D3} ||R_{D1} \}_{{PRK_{D} }} ,\{ ID_{P} ||ID_{D} ||T_{D4} ||Cert_{D} \}_{{SEK_{2} }} ).$$

By Statements 18 and 19, and the verification rule, the following Statement 20 can be derived:

$$({\text{Statement}}\;20)\quad HPC| \equiv D| \equiv (\{ PK||T_{D3} ||ID_{P} ||R_{D3} ||R_{D1} \}_{{PRK_{D} }} ,\{ ID_{P} ||ID_{D} ||T_{D4} ||Cert_{D} \}_{{SEK_{2} }} ).$$

By Statement 20 and the belief rule, the following Statement 21 can be derived:

$$({\text{Statement}}\;21)\quad HPC| \equiv D| \equiv HPC\mathop \leftrightarrow \limits^{{SEK_{2} }} D.$$

By Statement 21, A23 and the jurisdiction rule, the following Statement 22 can be derived:

$$({\text{Statement}}\;22)\quad HPC| \equiv HPC\mathop \leftrightarrow \limits^{{SEK_{2} }} D.$$

By Statement 22 and the belief rule, the following Statement 23 can be derived:

$$({\text{Statement}}\;23)\quad HPC| \equiv D| \equiv ID_{D} .$$

By Statement 23, A27 and the belief rule, the following Statement 24 can be derived:

$$({\text{Statement}}\;24)\quad HPC| \equiv ID_{D} .$$

According to Statements 22 and 24, the doctor’s authentication of the patient can be proved by using the Eq. 37 as follows:

$$(PK||T_{D3} ||ID_{P} ||R_{D3} ||R_{D1} )\mathop = \limits^{?} V_{{PUK_{D} }} (Sig_{D3} ).$$
(37)

The doctor authenticates the hospital’s private cloud

The doctor’s authentication of the private cloud can be shown by the assumptions and BAN logic as follows:

By M4 and the seeing rule, the following Statement 25 can be derived:

$$({\text{Statement}}\;25)\quad D \triangleleft (\{ PK||T_{HPC1} ||ID_{HPC} \}_{{PRK_{HPC} }} ,\{ M_{EMR} ||T_{HPC2} \}_{{SEK_{2} }} ).$$

By A7, A8 and the freshness rule, the following Statement 26 can be derived:

$$({\text{Statement}}\;26)\quad D| \equiv \# (\{ PK||T_{HPC1} ||ID_{HPC} \}_{{PRK_{HPC} }} ,\{ M_{EMR} ||T_{HPC2} \}_{{SEK_{2} }} ).$$

By Statement 25, A12, A19, A20 and the message meaning rule, the following Statement 27 can be derived:

$$({\text{Statement}}\;27)\quad D| \equiv HPC|\sim \# (\{ PK||T_{HPC1} ||ID_{HPC} \}_{{PRK_{HPC} }} ,\{ M_{EMR} ||T_{HPC2} \}_{{SEK_{2} }} ).$$

By Statements 26 and 27, and the verification rule, the following Statement 28 can be derived:

$$({\text{Statement}}\;28)\quad D| \equiv HPC| \equiv (\{ PK||T_{HPC1} ||ID_{HPC} \}_{{PRK_{HPC} }} ,\{ M_{EMR} ||T_{HPC2} \}_{{SEK_{2} }} ).$$

By Statement 28 and the belief rule, the following Statement 29 can be derived:

$$({\text{Statement}}\;29)\quad D| \equiv HPC| \equiv HPC\mathop \leftrightarrow \limits^{{SEK_{2} }} D.$$

By Statement 29, A24 and the jurisdiction rule, the following Statement 30 can be derived:

$$({\text{Statement}}\;30)\quad D| \equiv HPC\mathop \leftrightarrow \limits^{{SEK_{2} }} D.$$

By Statement 30 and the belief rule, the following Statement 31 can be derived:

$$({\text{Statement}}\;31)\quad D| \equiv HPC| \equiv ID_{HPC} .$$

By Statement 31, A28 and the belief rule, the following Statement 32 can be derived:

$$({\text{Statement}}\;32)\quad D| \equiv ID_{HPC} .$$

According to Statements 30 and 32, the doctor’s authentication of the patient can be proved by using the Eq. 43 as follows:

$$(PK||T_{HPC1} ||ID_{HPC} )\mathop = \limits^{?} S_{{PRK_{HPC} }} (Sig_{HPC1} ).$$
(43)

User anonymity and unlinkability

During the patient visiting doctor (consultation) phase, the EMR search phase, and the diagnosis phase, information is transmitted via a public channel, and it is crucial that a patient’s identity is secured against malicious attack. The proposed scheme encrypts these messages using public key operations by using the following Eqs. 1218, 25, 29, 34 and 40 as follows:

$$C_{P1} = E_{{PUK_{D} }} (ID_{P} ||B_{P} ||R_{P1} ||R_{P2} ||T_{P1} ),$$
(12)
$$C_{D1} = E_{{PUK_{P} }} (ID_{D} ||Cert_{D} ||R_{D1} ||R_{D2} ||SEK_{1} ||T_{D1} ),$$
(18)
$$C_{D2} = E_{{PUK_{PC} }} (ID_{P} ||T_{D2} ||ID_{D} ||Cert_{D} ||ID_{DE} ),$$
(25)
$$C_{C} = E_{{PUK_{D} }} (ID_{HPC} ||ID_{DE} ||T_{C} ),$$
(29)
$$C_{D3} = E_{{PUK_{HPC} }} (Cert_{D} ||T_{D3} ||ID_{D} ||R_{D3} ||R_{D1} ),$$
(34)
$$C_{HPC1} = E_{{PUK_{D} }} (ID_{HPC} ||SEK_{2} ||T_{HPC1} ||R_{HPC2} ),$$
(40)

and encrypts the transmitted messages by session keys by using the following Eqs. 23 and 45 as follows:

$$C_{P2} = E_{{SEK_{1} }} (M_{SD} ,ID_{P} ,T_{P2} ),$$
(23)
$$C_{D4} = E_{{SEK_{2} }} (ID_{P} ||ID_{D} ||T_{D4} ||Cert_{D} ).$$
(45)

Because the messages are encrypted by public keys or session keys, attackers cannot obtain a patient’s identity by intercepting the messages transmitted via a public channel. In addition, all messages have timestamps that change every session, thus encrypted messages with different timestamps can be identified, ensuring that malicious attackers cannot trace users. The proposed scheme, therefore, offers user anonymity and unlinkability.

Integrity

The patient visiting doctor (consultation) phase

The patient’s signature \(Sig_{P1}\) can be verified by its public key by using the following Eqs. 13 and 15 as follows:

$$Sig_{P1} = S_{{PRK_{P} }} (R_{P1} ||ID_{P} ||R_{P2} ||B_{P} ||PK||T_{P1} ),$$
(13)
$$(R_{P1} ||ID_{P} ||R_{P2} ||B_{P} ||PK||T_{P1} )\mathop = \limits^{?} V_{{PUK_{P} }} (Sig_{P1} ).$$
(15)

Thus, the doctor can ensure the integrity of the messages.

Meanwhile, the doctor’s signature \(Sig_{D1}\) can be verified by its public key by using the following Eqs. 19 and 21 as follows:

$$Sig_{D1} = S_{{PRK_{D} }} (R_{D2} ||ID_{D} ||T_{D1} ||Cert_{D} ||SEK_{1} ||PK),$$
(19)
$$(R_{D2} ||ID_{D} ||T_{D1} ||Cert_{D} ||SEK_{1} ||PK)\mathop = \limits^{?} V_{{PUK_{P} }} (Sig_{D1} ).$$
(21)

Thus, the patient can ensure the integrity of the messages.

The EMR search phase

The doctor’s signature \(Sig_{D2}\) can be verified by its public key by using the following Eqs. 26 and 28 as follows:

$$Sig_{D2} = S_{{PRK_{D} }} (S_{D} ||T_{D2} ||ID_{P} ||ID_{DE} ||ID_{D} ),$$
(26)
$$(S_{D} ||T_{D2} ||ID_{P} ||ID_{DE} ||ID_{D} )\mathop = \limits^{?} V_{{PUK_{D} }} (Sig_{D2} ).$$
(28)

Thus, the public cloud can ensure the integrity of the messages.

At the same time, public cloud’s signature \(Sig_{C}\) can be verified by its public key by using the following Eqs. 30 and 32 as follows:

$$Sig_{C} = S_{{PRK_{C} }} (ID_{DE} ||S_{SD} ||ID_{HPC} ||T_{C} ),$$
(30)
$$(ID_{DE} ||S_{SD} ||ID_{HPC} ||T_{C} )\mathop = \limits^{?} V_{{PUK_{C} }} (Sig_{C} ).$$
(32)

Therefore, the doctor can ensure the integrity of the messages, while the doctor’s signature \(Sig_{D3}\) can be verified by its public key by using the following Eqs. 35 and 37 as follows:

$$Sig_{D3} = S_{{PRK_{D} }} (PK||T_{D3} ||ID_{P} ||R_{D3} ||R_{D1} ),$$
(35)
$$(PK||T_{D3} ||ID_{P} ||R_{D3} ||R_{D1} )\mathop = \limits^{?} V_{{PUK_{D} }} (Sig_{D3} ).$$
(37)

Thus, the hospital’s private cloud can ensure the integrity of the messages.

The private cloud’s signature \(Sig_{HPC1}\) can be verified by its public key by using the following Eqs. 41 and 43 as follows:

$$Sig_{HPC1} = S_{{PRK_{HPC} }} (PK||T_{HPC1} ||ID_{HPC} ),$$
(41)
$$(PK||T_{HPC1} ||ID_{HPC} )\mathop = \limits^{?} S_{{PRK_{HPC} }} (Sig_{HPC1} ).$$
(43)

Thus, the doctor can ensure the integrity of the messages. In the proposed scheme, all parties create a signature, and their authenticity is ensured by these signatures. Therefore, the proposed scheme meets the integrity requirement.

Non-repudiation

While all parties send messages, it is also important that no party can deny sending a message that they have sent. The proof of the non-repudiation offered by the proposed scheme is given in Table 2.

Table 2 Proof of the non-repudiation offered by the proposed scheme

Forward and backward security

New random numbers are selected for session keys in every session, thus changing the session key by using the following Eqs. 17 and 39 for every session on the proposed scheme, as follows:

$$SEK_{1} = h((S_{D} R_{P2} + r_{6} (R_{P1} + H(ID_{P} ||B_{P} ||R_{P1} )PK))||r_{6} R_{P2} ),$$
(17)
$$SEK_{2} = h((S_{HPC} R_{D3} + r_{8} (R_{D1} + h(ID_{D} ||Cert_{D} ||R_{D1} )PK))||r_{8} R_{D3} ).$$
(39)

The encryptions in the proposed scheme are changed every session because it contains time stamps which change every session. The encrypted messages, which are caculated by using the following Eqs. 12, 1823, 29, 34, 40, 45 and 47 are as follows:

$$C_{P1} = E_{{PUK_{D} }} (ID_{P} ||B_{P} ||R_{P1} ||R_{P2} ||T_{P1} ),$$
(12)
$$C_{D1} = E_{{PUK_{P} }} (ID_{D} ||Cert_{D} ||R_{D1} ||R_{D2} ||SEK_{1} ||T_{D1} ),$$
(18)
$$C_{P2} = E_{{SEK_{1} }} (M_{SD} ,ID_{P} ,T_{P2} ),$$
(23)
$$C_{D2} = E_{{PUK_{PC} }} (ID_{P} ||T_{D2} ||ID_{D} ||Cert_{D} ||ID_{DE} ),$$
(25)
$$C_{C} = E_{{PUK_{D} }} (ID_{HPC} ||ID_{DE} ||T_{C} ),$$
(29)
$$C_{D3} = E_{{PUK_{HPC} }} (Cert_{D} ||T_{D3} ||ID_{D} ||R_{D3} ||R_{D1} ),$$
(34)
$$C_{HPC1} = E_{{PUK_{D} }} (ID_{HPC} ||SEK_{2} ||T_{HPC1} ||R_{HPC2} ),$$
(40)
$$C_{D4} = E_{{SEK_{2} }} (ID_{P} ||ID_{D} ||T_{D4} ||Cert_{D} ),$$
(45)
$$C_{HPC2} = E_{{SEK_{2} }} (M_{EMR} ||T_{HPC2} ).$$
(47)

The timestamps in the encrypted messages and the random numbers in the session keys ensure that attackers cannot decrypt messages sent in the current session, and they cannot use messages from previous sessions as duplicate or replacement messages. For the same reason, if attackers obtain current messages, they cannot decrypt old messages. Therefore, the proposed scheme offers both forward and backward security.

Known attacks

Replay attack

The proposed scheme uses two forms of encryption, namely the public key operation, and the session key operation. Both are secure against replay attacks. In the public-key operation, all messages include a timestamp. The timestamps prevent replay attacks because the timestamp is different at any time, which means that encrypted messages are different for every session. The details of the public key operations which are computed by using the following Eqs. 12, 1825, 29, 34 and 40 are as follows:

$$C_{P1} = E_{{PUK_{D} }} (ID_{P} ||B_{P} ||R_{P1} ||R_{P2} ||T_{P1} ),$$
(12)
$$C_{D1} = E_{{PUK_{P} }} (ID_{D} ||Cert_{D} ||R_{D1} ||R_{D2} ||SEK_{1} ||T_{D1} ),$$
(18)
$$C_{D2} = E_{{PUK_{PC} }} (ID_{P} ||T_{D2} ||ID_{D} ||Cert_{D} ||ID_{DE} ),$$
(25)
$$C_{C} = E_{{PUK_{D} }} (ID_{HPC} ||ID_{DE} ||T_{C} ),$$
(29)
$$C_{D3} = E_{{PUK_{HPC} }} (Cert_{D} ||T_{D3} ||ID_{D} ||R_{D3} ||R_{D1} ),$$
(34)
$$C_{HPC1} = E_{{PUK_{D} }} (ID_{HPC} ||SEK_{2} ||T_{HPC1} ||R_{HPC2} ).$$
(40)

The session keys are also changed every session by the random number chosen. The session keys which are calculated by using the following Eqs. 17 and 39 are as follows:

$$SEK_{1} = h((S_{D} R_{P2} + r_{6} (R_{P1} + H(ID_{P} ||B_{P} ||R_{P1} )PK))||r_{6} R_{P2} ),$$
(17)
$$SEK_{2} = h((S_{HPC} R_{D3} + r_{8} (R_{D1} + h(ID_{D} ||Cert_{D} ||R_{D1} )PK))||r_{8} R_{D3} ).$$
(39)

The transmitted messages also contain timestamps. So, even if an attacker intercepts previous messages and sends them back to the current session, they will fail the verification, and communication will be terminated.

Man-in-the-middle attack

For an attacker to conduct a man-in-the-middle attack, they need to intercept transmitted messages. Then they will modify the intercepted message, and send the modified message to the destination party. However, all signatures in the proposed scheme involve a timestamp, the scheme uses public-key cryptography, and public and private keys. Therefore, the public key is used to encrypt the message, and the private key is used to sign the message. An attacker cannot modify a signature while it involves a private key, and cannot modify the timestamp. Therefore, they cannot conduct a man-in-the-middle attack, as it is not possible to successfully modify a message. The signatures which are computed by using the following Eqs. 13, 19, 26, 30, 35 and 41 are listed as follows:

$$Sig_{P1} = S_{{PRK_{P} }} (R_{P1} ||ID_{P} ||R_{P2} ||B_{P} ||PK||T_{P1} ),$$
(13)
$$Sig_{D1} = S_{{PRK_{D} }} (R_{D2} ||ID_{D} ||T_{D1} ||Cert_{D} ||SEK_{1} ||PK),$$
(19)
$$Sig_{D2} = S_{{PRK_{D} }} (S_{D} ||T_{D2} ||ID_{P} ||ID_{DE} ||ID_{D} ),$$
(26)
$$Sig_{C} = S_{{PRK_{C} }} (ID_{DE} ||S_{SD} ||ID_{HPC} ||T_{C} ),$$
(30)
$$Sig_{D3} = S_{{PRK_{D} }} (PK||T_{D3} ||ID_{P} ||R_{D3} ||R_{D1} ),$$
(35)
$$Sig_{HPC1} = S_{{PRK_{HPC} }} (PK||T_{HPC1} ||ID_{HPC} ).$$
(41)

Impersonation attack

An impersonation attack occurs when an attacker poses as a legitimate party in order to access sensitive information.

  1. (1)

    Impersonation of the patient

    If an attacker can impersonate a legitimate user, then they can forge a \(Sig_{P1}\) message to appear as if it was sent by the patient. \(Sig_{P1}\) is computed by using the following Eq. 13 as follows:

    $$Sig_{P1} = S_{{PRK_{P} }} (R_{P1} ||ID_{P} ||R_{P2} ||B_{P} ||PK||T_{P1} ).$$
    (13)

    Even if the attacker knows the patient’s public key, they still cannot forge \(Sig_{P1}\) since it is signed with the patient’s private key.

  2. (2)

    Impersonation of the hospital’s private cloud

    If an attacker can impersonate the hospital’s private cloud, they can forge a \(Sig_{HPC1}\) message by receiving the \(C_{D3}\) and \(Sig_{D3}\) messages. \(Sig_{HPC1}\) is computed by using the following Eq. 41 as follows:

    $$Sig_{HPC1} = S_{{PRK_{HPC} }} (PK||T_{HPC1} ||ID_{HPC} ).$$
    (41)

    However, even if the attacker obtains the private cloud’s public key, they still cannot forge \(Sig_{HPC1}\) because it is signed with the original private cloud private key.

  3. (3)

    Impersonation of the doctor

    If an attacker can impersonate the doctor, then they can forge a \(Sig_{D1}\) message using the \(C_{P1}\) and \(Sig_{P1}\) messages. \(Sig_{D1}\) is computed by using the following Eq. 19 as follows:

    $$Sig_{D1} = S_{{PRK_{D} }} (R_{D2} ||ID_{D} ||T_{D1} ||Cert_{D} ||SEK_{1} ||PK).$$
    (19)

    However, even if the attacker knows the doctor’s public key, they will still not be able to forge \(Sig_{D1}\) since it is signed with the doctor’s private key. For the same reason, during the EMR search phase, the attacker may wish to forge the \(C_{D2}\), \(Sig_{D2}\) and \(Sig_{D3}\) messages. \(Sig_{D2}\) and \(Sig_{D3}\) are computed by using the following Eqs. 26 and 35 as follows:

    $$Sig_{D2} = S_{{PRK_{D} }} (S_{D} ||T_{D2} ||ID_{P} ||ID_{DE} ||ID_{D} ),$$
    (26)
    $$Sig_{D3} = S_{{PRK_{D} }} (PK||T_{D3} ||ID_{P} ||R_{D3} ||R_{D1} ).$$
    (35)

    Thus, even if the attacker knows the doctor’s public key, the attacker still cannot forge \(Sig_{D2}\) and \(Sig_{D3}\) since they are signed with the doctor’s private key.

  4. (4)

    Impersonation of the public cloud

    If an attacker is able to impersonate the public cloud, then they can forge a \(Sig_{C}\) message according to the received \(C_{D2}\) and \(Sig_{D2}\) messages. \(Sig_{C}\) is computed by using the following Eq. 30 as follows:

    $$Sig_{C} = S_{{PRK_{C} }} (ID_{DE} ||S_{SD} ||ID_{HPC} ||T_{C} ).$$
    (30)

    Even if the attacker can obtain the public cloud’s public key, they will still be unable to forge \(Sig_{C}\) because it is signed with the public cloud’s original private key.

    It is therefore impossible for malicious attackers to successfully impersonate any party in the proposed scheme.

Discussion

Security comparison

Table 3 gives a comparison of the security attributes of the proposed scheme with those of other schemes.

Table 3 Comparison of the security attributes of the proposed scheme with those of other schemes

This study found that the schemes proposed by Chiou et al. [13], Mohit et al. [14] and Li et al. [16] do not support patient anonymity and patient unlinkability, are not secure against impersonation attacks and do not support doctor unlinkability, while the proposed scheme can achieve all of these. We applied encryption and signature mechanism to protect transmitted messages, which guarantees confidentiality and integrity. Our proposed architecture is indeed applicable in real environments, which also fully ensures availability.

Computation cost

The computation cost of the proposed scheme is \(12T_{Sign} + 14T_{A} + 6T_{S} + 4T_{H}\), which is higher than those of other schemes because it uses both asymmetric and symmetric encryption for improved security. Although other schemes require less execution time, they do have some related flaws, as there are some security requirements that they do not meet, such as patient anonymity, patient unlinkability, and doctor unlinkability. To sum up, the proposed scheme is more secure than others. Table 4 shows the computation cost comparison.

Table 4 Comparison of computation costs

Communication cost

The communication cost comparison is shown in Table 5. This study adopts the approach described for the Mohit et al. scheme [14] to compute the communication cost. The proposed scheme incurs a communication cost lower than those of the schemes proposed by Chiou et al. and Mohit et al. [13], and higher than those of the schemes proposed by Kumar et al. and Li et al., because the proposed scheme uses signatures in every session, which incur a greater communication cost, but enables non-repudiation. The cost of communication at each stage was analyzed in a 4G environment, with a maximum transmission speed of 100 Mbps, and in a 5G environment, with a maximum transmission speed of 20 Gbps [39].

Table 5 Communication cost comparison

Conclusion

EMR security is a significant issue in current distributed EMR storage and sharing schemes, as it is crucial that any system be secure against malicious attacks. The scheme proposed in this study offers secure and efficient distributed sharing of EMR data between four parties using cloud computing technology and encryption, such as public-key operation, session key operation, and elliptic curve cryptography. The proposed scheme offers patient privacy during the consultation phase, ensures message integrity and non-repudiation, achieves mutual authentication between parties, offers authentication of medical resource sharing via cloud technology, and is secure against known attacks, thus providing a convenient and secure way to store, use and share medical information resources between hospitals, ensuring more efficient use of medical information resources, and offering patients better and more timely diagnosis and treatment.

Availability of data and materials

Not applicable.

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Acknowledgements

This work was supported by Asia University, Taiwan, and China Medical University Hospital, China Medical University, Taiwan, under Grant ASIA-108-CMUH-05 and ASIA-107-CMUH-05. This work was also supported by Asia University, Taiwan, UMY, Indonesian, under Grant 107-ASIA-UMY-02. This study is also supported by the Ministry of Science and Technology (MOST), Taiwan, Republic of China, under the Grants of MOST 108-2221-E-324-013 and MOST 107-2221-E-468-015.

Funding

This work was supported by the National Natural Science Foundation of China under Grants 61801413, by the Natural Science Foundation of Fujian Province of China under Grant 2017J05110, and by Education and Scientific Research Project for Young and Middle-aged Teachers in Fujian Province under Grant JAT160345.

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C-LC and Y-YD have made substantial contributions to conception and design, involved in drafting the manuscript. P-TH and Y-CW have made the acquisition of data and analysis and interpretation of data. The critically important intellectual contents of this manuscript have been revised by H-CC. The corresponding authors are H-C Chen and Y-Y Deng. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Yung-Yuan Deng or Hsing-Chung Chen.

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Chen, C., Huang, P., Deng, Y. et al. A secure electronic medical record authorization system for smart device application in cloud computing environments. Hum. Cent. Comput. Inf. Sci. 10, 21 (2020). https://doi.org/10.1186/s13673-020-00221-1

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Keywords

  • Secure medical record system
  • Authorization
  • IoT
  • Cloud
  • Health care
  • Security