Securing communication by attribute-based authentication in HetNet used for medical applications

The introduction of electronic health recorders to collect patient information in the healthcare system has various steps. It electronically stores patient medical records and uploads them to a database server [16]. From the perspective of the medical care system, patients see several doctors during their lives, from attending a primary health clinic to hospitals. Therefore, health records are created with every clinical meeting or emergency visits [17, 18]. Keeping data integrity in view, safe routing is a very important issue within a given network (HetNet). For securing communication in HetNets, most of the research work is done at the physical layer [8, 9]. In medical applications like hospitals where we have a wide variety of users, our authentication scheme needs to be robust with a wide dynamic range for authentication. If security issues are addressed at the physical layer, we need to increase its dynamic range, which requires a lot of hardware, hence further increase in cost and power consumption. Therefore for such applications, physical layer security is not a feasible option. Although few techniques were employed at the network layer, they had limitations like IBE has less dynamic range [19]; in symmetric key encryption, exchanging the key secretly between the users is a big problem [20]. Therefore, the key objective of this article is to address security issues at the network level by employing ABE authentication as it contains characteristics like efficient key management, error tolerance, privacy preservation, emergency data storage, and retrieval.

The contribution of this paper is that the health data of patients have been successfully secured while routing it to the data requesters. This is possible by employing ABE authentication on the stored data.

The remaining article is oriented as current related work performed in the relevant field is discussed in Section 2. Section 3 addresses ABE’s background. In addition, the recommended method is presented in division 4, Section 5 gives a brief introduction about AVISPA tool, Section 6 shows the formal validation of proposed scheme in AVISPA tool, Section 7 is regarding the results and discussion of the proposed approach, and finally, Section 8 comes up with the conclusion and future scope.

Several accomplishments have been dedicated to security problems in HetNets for the past few years, such as Hu et al. [2] recently examined the PLS in HetNets backed by SWIPT to boost the safety issue. Further, they inserted artificial sound in the communicated beam together with the macrocell and femtocell base stations. Subsequently, authors in [5] realized that multi-tier structural design together with rigorous 5G latency requisites poses new security challenges due to possible repeated deliveries and validations in 5G mini cells and HetNets. Thus, introducing SDN in 5G will allow efficient authentication handovers and protection of privacy through its centralized control capability. In another research, authors of article [10] suggested a joint source allocation scheme that under fairness requirements simultaneously considers PLS, cross-level intervention, and joint power optimization and sub-carriers. Duan et al. [11] in another paper proposed SDN-supported fast validation approach utilizing weighted SCI handover to enhance authentication performance during handover and satisfy the 5G latency needs. In paper [21], authors have introduced FFFTM (Flooding Factor-based Framework for Trust Management) in MANETs for the secure transmission of data. The true flooding method is used to recognize intruder nodes depending on the evaluation of trust value. Makarfi et al. [22] presented the ordinary logarithmic expression for the system capability in a different form, to allow the study of the random variables describing the channel fading and interference in terms of the joint moment generating functions (MGF). In [23], an interference management method for PLS in a two-tier HetNet system to increase the user’s secrecy rate under eavesdropping attack is proposed. Wang et al. [24] investigated the PHY layer security of a two-tier HetNet thru sub 6 GHz substantial MIMO macrocells and millimeter wave (mmWave) small cells. They evaluated the scope and secrecy efficiency using stochastic geometry by taking into account the pilot attacks from the spies.

Some of the work related to our proposed scheme is discussed in Table 1; it is quite evident that the ABE scheme has been used for securing data in networks like vehicular ad hoc network, Internet of things, and body sensor network. For securing communication in HetNet, various studies have been dedicated to the PHY layer, nevertheless, no effort is carried-out at network layer utilizing such approaches. Hence, this research article proposes an ABE authentication scheme to secure data in medical-dedicated HetNet.

Issues regarding protecting the privacy of patients and the security of medical details are two basic problems with the proper use of electronic medical services [33]. Different techniques are used to protect this healthcare data. The most commonly used techniques are validation, encryption, data masking, access control, monitoring, auditing, and so on [34]. In paper [35], the authentication at the physical layer is introduced by utilizing the time-varies CFO (carrier frequency offset) related through each couple of wireless communications systems. Encryption methods like IBE, SKE, and conventional PKE techniques may be utilized for securing the health data recorded by body sensors [14]. Sudarsono et al. [13] presented a secure sharing of data in the e-healthcare system utilizing IBE with signature. So that data can only be shared by authentic users based on specific public identity, and data exchanged is encrypted and authenticated such that only authorized users can exchange the data. Although IBE does not require a public key distribution infrastructure, it has a less dynamic range as it considers only one attribute that needs to be fulfilled necessarily [19]. Similarly, SKE is faster as it utilizes only one key for encryption and decryption, but exchanging this key secretly between the users is a big problem [20]. All these techniques are used for securing the essential health data of users at the network layer. The attacks on network layer capture information, modify it, and direct for re-communication [17]. Taking the above limitations into consideration, ABE authentication is taken into account to keep safe the health information from these kinds of attacks. Further, the comprehensive evaluation of the existing security protocols in the state-of-the-art is carried-out in Table 1.

Assuming there are two multiplicative cyclic groups G₀ and G₁ of prime order p, let g be generator of G₀, and e be a bilinear map, e: G₀× G₀→ G₁. The characteristics of bilinear map e are as given below:

G₀ is a bilinear group if the group operation in G₀ and the bilinear map e: G₀× G₀→ G₁ are both competently computable. Notice that the depict e is symmetric since e (g^x, g^y) = e (g, g)^xy= e(g^y, g^x).

There are many types of PKE, and ABE is one of them. ABE is also related to IBE, and the distinction between the two is that ABE scheme is one-to-many while IBE scheme is one-to-one [15, 19]. In ABE, a group of features is taken into consideration, and according to that set, the message is encrypted, such that decryption of message can be performed by only those users meeting the attributes in the attribute set.

The advantage of using attribute-based authentication over identity-based authentication is that it is error-tolerant. That means if we have 10 attributes (say) in the attribute list we can set a threshold of 7 attributes. Anyone satisfying the said condition can get access the data while as in identity-based authentication of all the said identities needs to be fulfilled then only one can get access to the data. Therefore, it will make things difficult in our healthcare system.

The significance of routing data in the healthcare organization employing attribute-based authentication scheme is presented in Fig. 4, where the flowchart for the whole technique has been depicted. The data requester sends its credentials to the base station for authentication. If the credentials of the data requester get matched with the attribute list of the base station, then the authentication is successful and the base station sends a signal to the owner of the data that the user is verified. Now, the data requester gets access to the data; otherwise, it denies the request by detecting the intruder.

Unsecure routing cannot be afforded in medical applications because the patient’s health data is secret, and if it is not routed to desired users, it could cost somebody’s life. Hence, our information essentials to be protected and routed to desired users. The following steps are taken to implement attribute-based authentication in HetNet and have been defined from Eqs. 1 to 6 in an algorithm manner. The prototype of HLPSL code is shown in the following steps:

Base station (BS) sends a nonce number “N_y” for authentication to data requester (R) and the whole message is encrypted using R’s public key “K_r”.

Data requester (R) receives nonce number “N_y” from BS.

Data requester (R) sends request to base station (BS) for verification on attribute values (S) along with a nonce number “N_y” and the whole message is encrypted using base station’s (BS) public key K_s.

Base station (BS) checks the nonce number sent by data requester’s (R) along with attributes (S) in its attribute-trust list (Z).

After authentication, base station (BS) will send confirmation message (ok) to data owner (O) that data requester (R) is authenticated and you can proceed with the next packet.

Now, in the above entire prototype, the key generation is done in two major steps:

During this phase, the private key generator (here MBS) generates a master secret key (M_sk) based on attributes defined in Z.

The private key generator will distribute public keys (K_i) and secret keys (S_i) to the users connected to it using the master secret key.

Further, symbolizations using the above equations are specified in Table 2.

Figure 9 shows the protocol simulation, and Fig. 10 shows the intruder simulation when no authentication scheme is used. Here, Bob wants to communicate with Alice over the public channel without encrypting the data. This data is at the highest risk of being attacked by an intruder as the message is sent in plain-text. The intruder can easily receive all the data sent from Bob to Alice, and hence, intruders can modify the data. When this malicious data is received by Alice, it assumes that it is being sent by Bob, which is not true, and in a crucial application like healthcare, it can prove hazardous. From both Figs. 9 and 10, it is apparent that when two users communicate without using any authentication scheme intruder can easily attack the data, thereby putting the information at great risk.

The simulation output under CL-AtSe back-end of this security protocol gives the “SUMMARY” if the protocol is “SAFE” or “UNSAFE” or whether the study is indeterminate. Here, this one is unsafe for this case.

Figures 11 and 12 show the protocol and intruder simulation by using a single key, respectively. Here, the sender (data requester) first encrypts data using key “K_s” and then sends it to the receiver (base station). The same key is used by the target user to decrypt data. If somehow intruder gets the knowledge of the secret key, an intruder could easily get access to data and modify it. Exchanging the key secretly between users is the problem in this case. So this is a weak authentication technique. The simulation output under CL-AtSe back-end of this security protocol shows that this protocol is safe.

Figure 13 demonstrates the protocol simulation of proposed security protocol in the AVISPA using CL-AtSe. Here, the proposed security protocol is simulated in the presence of intruders who can pose a threat to our information.

Figure 14 shows intruder simulation of proposed work in the AVISPA using CL-AtSe in the presence of the intruder. The communication process is initiated by the base station. It acts as a private key generator (PKG) and provides public and private keys to all users connected to it, with the help of master secret key (M_sk). During the authentication process, the base station sends a nonce number to the user (data requester) encrypted with the public key (K_R) of that particular user. These nonce numbers are random numbers and are not the same for any two users. Data requester sends back this nonce number along with credentials (S) to the BS, encrypted via the public key of BS’s (K_S). If the base station acknowledges that he received the same nonce number and the credentials of the user are present in the attribute trust list, then the base station authenticates the data requester. So here nonce number also becomes one of the attributes. The intruder may attempt to attack the crucial health data, yet the attacker is unable to violate the privacy of the entire network because of the implemented authentication scheme because it becomes difficult for an intruder to guess all the attributes on which authentication takes place. In addition to this, the nonce number that acts as one of the attributes is generated at the time of communication and is extremely difficult for an intruder to guess it. Therefore, due to this, communication inside the network is safe from attacks by adversaries. Under CL-AtSe back-end, simulation performance of this security protocol gives the “SUMMARY” if the protocol is “SAFE” or “UNSAFE” or whether the study is indeterminate. Here it is safe for this case.

It is clear from case 1 that we need to secure the data from intruders before transmission. Our authentication scheme needs to be robust so that intruder cannot attack the data easily. As in case 2, a weak authentication scheme is used which does not provide a robust authentication against intruders. Case 3 provides an error-tolerant and robust authentication scheme with a wide dynamic range.