Intelligent Automation & Soft Computing DOI:10.32604/iasc.2023.029397 | [picture]
Article |

Cryptographic Algorithm for Enhancing Data Security in Wireless IoT Sensor Networks

A. Bhavani and V. Nithya*

Department of ECE, SRM Institute of Science and Technology, Kattankulathur, 603203, Chennai, Tamilnadu, India
Corresponding Author: V. Nithya. Email: nithyav@srmist.edu.in
Received: 02 March 2022; Accepted: 06 April 2022

Abstract: Wireless IoT Sensor Network can handle audio, video, text, etc., through the interconnection of ubiquitous devices. The entertainment and application-centric network relies on its autonomous nodes for handling large streams of multimedia data. Security breaches and threats due to insider attacks reduce the data handling and distribution capacity of the nodes. For addressing the insider attacks problem, Session-Critical Distributed Authentication Method (SCDAM) is proposed. The proposed method relies on short-lived concealed authentication based on an improved elliptic curve cryptography (ECC) algorithm. In this authentication, the session time and the interrupts are accounted for, providing end-to-end authentication. The session keys are distributed before and after each interrupt from which the shared data is authenticated. This authentication process uses a linear hash process, ensuring non-repetition of keys in the consecutive sessions. This proposed authentication method is capable of providing improved sessions, less data distribution loss, and complexity.

Keywords: Insider attacks; elliptic curve cryptography; hash function; session authentication; IoT

1  Introduction

Nowadays, the Internet of Things (IoT) played a crucial role and going to change in this world [1]. Approximately, the usage of IoT devices will be reached around 22 billion by 2025. Due to the tremendous cost-saving reason, most industries utilize various IoT devices for their application purposes [2]. IoT devices are incorporated by several organizations and individuals with wireless sensors to create multiple smart applications. Each IoT device depends on wireless sensor technology, which causes supply chain management, smart cities, smart buildings, smart homes, and intelligent agriculture [3,4]. Along with this, the Y-O-Y growth and structure analysis of various industries, the wireless IoT sensor market has been reached globally in 2020–2026 [5]. IoT devices collect the data from local conditions or environments with wireless technology, and the gathered information is transmitted via the powerful platform or components. The IoT sensors are distributed in various geographic locations that are communicated via the gateways, central hubs, and servers. The main reason for incorporating the wireless sensor with IoT is that it consumes minimum maintenance and low power function [6,7]. Although the IoT devices are distributed in various locations, it also collects enormous data volumes by making the proper interactions. The heterogenous environment-based data collection causes security-related issues.

The IoT devices are gathering sensitive information like healthcare details, bank and business transactions, etc. This information needs to be secured from unauthorized access [8]. Due to the heterogeneous device location, the communication path or information may be accessed by unauthorized users. Distribution denial of service (DDoS) attacks [9] is pervasive while sharing the data from one location to another [10]. The wireless IoT sensor networks are created with minimum security features that are more difficult to handle. Therefore, the security of wireless IoT sensor devices-based communication should be managed by applying the different security mechanisms [11,12]. The created system must be recognizing the unauthorized users, unauthorized activities, malicious attack detection, and prediction of DDoS and insider attacks [13,14]. Several supervised learning techniques are utilized to predict unwanted activities in the IoT based data sharing process [15]. These algorithms consume high overhead, high false positives, never considering the device service attributes, difficulty predicting the type of attacks [16] and low response levels [17].

The security algorithm should be crated for handling the wireless IoT sensor data security and node distribution by considering this problem definition. Hence this paper uses the Session-Critical Distributed Authentication Method (SCDAM) for addressing the insider attacker problem. The SCDAM algorithm authentication process is improved by applying the Elliptic Curve Cryptography (ECC) approach [18]. During the authentication process, session time and interrupts are utilized to establishing the end-to-end authentication process. The session keys are distributed before and after each interrupt from which the shared data is authenticated. This authentication process uses a linear hash process, ensuring non-repetition of keys in the consecutive sessions. The discussed SCDAM with the ECC algorithm establishes the security and addresses the insider attack with less data distribution loss, complexity, and improved sessions. This wireless IoT sensor device-based data handling process is implemented using the NS2 simulations. The entire paper is prepared as follows, Section 2 dealing with the different researcher opinions regarding wireless IoT sensor data handling. Section 3 analyses the working process of SCDAM with ECC based IoT data sharing and handling; excellence of the system is evaluated in Section 4. The end of the work is summarized in Section 5.

2  Related Works

Maram et al., 2019 applied SIMON block cipher lightweight cryptographic (SIMON-LC) algorithm for managing data security in IoT applications [19]. This paper uses SIMON cipher characteristics to enhancing the speed of the process. Integrating the advanced encryption standard algorithm with the SIMON block cipher algorithm maximizes data security with minimum encryption time, execution time, and memory consumption.

Zhang et al., 2019 managed the UNICODE data security and privacy in the Internet of things using intelligent security algorithm [20]. Here, substitution S-box is utilized to handling the various UNICODE data such as image, video, audio, and text. This process works in a dynamic and key-dependent manner that improves the overall data security in IoT applications. The effective utilization of substitution-based S-box enhances overall system performance.

Adhikari et al., 2017 developed the RFID authentication process in IoT using the Elliptic Curve Cryptographic approach (RFID-ECC) This work analyzed the various security weaknesses for improving the overall IoT data security [21]. A radio frequency identification scheme is developed by utilizing the Elliptic curve cryptography (ECC) approach by considering the security weakness. This process enhances the overall security requirements with minimum cost. Elhoseny et al., 2019 created the secure IoT communication framework in the content-centric network by applying the elliptic curve cryptography [22]. The security was ensured by designing the certificateless public key infrastructure for resource-constrained IoT communication. The lightweight cryptosystem is incorporated with the elliptic curve cryptography to effectively manage data security and effectively eliminate the intermediate cryptographic attacks.

Wang et al., 2018 developed a secure IoT healthcare-based data transmission model by applying various cryptographic algorithms [23]. This process creates the hybrid encryption scheme by integrating the 1-D or 2-D discrete wavelet transform with Adleman, Shamir, Rivest, and the advanced encryption standard algorithm. The hybrid encryption algorithm was encrypting the transmitting IoT data, which includes both text and images. The combination of encryption algorithms is difficult to identify by the intermediate attackers. Then the introduced hybrid encryption scheme manages the patient confidentiality, capacity, and imperceptibility effectively.

Manikandan et al., 2018 introducing the one round cipher algorithm [ORCA] for managing the multimedia data security in IoT applications [24]. The algorithm generates the key dynamically, and the dynamic permutation table, round substitution table, and two pseudo-random metrics are utilized. These table pieces of information are being used to create the ciphertext used to maintain multimedia data security. The cipher scheme’s effective utilization improves the overall IoT data security with maximum speed, flexibility, simplicity, and low error propagation.

Deebak et al., 2019 developed the random coefficient selection and mean modification approach for managing the security in the IoT framework [25]. This approach uses multiple discrete coefficients to analyze the data randomly to ensure data security. This process ensures high robustness and minimizes the region-related attacks successfully. The utilization of normalized cross-correlation relative values helps to eliminate the intermediate attacks with a 0.95 correlation value.

Sudhakaran et al., 2020 managed data security in IoT-related wireless sensor networks by applying the hybrid secure routing mechanism [26]. Flexible security is ensured using the two-fish symmetric key method in the global sensor networks. This process is achieved by authenticating the user based on the authentication and encryption model [27]. In addition to this, the eligibility weight function is applied to validate the sensor nodes. After that, Ad-hoc On-demand multipath distance vector and multipath optimized link-state routing protocol are utilized to transmitting the data via the authenticated node. This process manages security and multipath diversity.

2.1 Problem Definition

In the wireless IoT sensor networks, security, and data privacy is one of the significant challenges. The incorporation of sensor technologies in IoT devices can collect a huge volume of data that consists of text, audio, video, etc. This information is transmitted from the organized location to the processing place for ensuring a specific application. The data transmission should be authenticated before initiating the process because it eliminates intermediate attacks and access. According to the various researcher’s opinions, several cryptographic and encryption techniques are utilized to authenticate the data before making the transaction.

Further, the secure key generation process is also defined for maintaining data security and privacy. Although the discussed methods fail to resolve the security breaches and threats due to the insider attacks, they reduce the nodes’ data handling and distribution capacity. In this work, Session-Critical Distributed Authentication Method (SCDAM) with Elliptic Curve Cryptography (ECC) approach is applied to ensure the discussed problem definition for addressing the insider attacker problem.

2.2 Insider Attack Problem

The insider attack problem is nothing but the malicious attacks in the network by the authorized person. Compared with the external attacks, the insider attack has a specific advantage because the authorized person has a network architecture structure and policies. Most organizations plan to create security measurements for external attacks and fewer mechanisms for managing the internal attacks. Due to the fewer security precautions of internal attacks, sensitive data has been stealing by injecting the Trojan viruses. Then the insider attack hacks the system’s full processing capacity, storage, and system overloading. According to the NOKIA report in 2019, almost 33% of IoT devices are infected. This information is gathering, according to the 150 million devices-based network traffic details.

Although the IoT devices are integrated with the wireless technology, it has weak security measures that cause to access the sensitive files. The unwanted threatening files are injected into IoT devices and creating damage to the process. Once the insider attack accesses the IoT devices, that will make a severe risk in healthcare and smart home applications. The insider attack blocks the user from accessing the information; it also affects the entire system, platform, and stealing the user’s sensitive details.

The wireless sensor IoT devices collect the multimedia data; therefore, the IoT devices handle the massive volume of data with nodes’ distribution capacity. Hence, the effective cryptographic technique called session-critical distributed authentication method with Elliptic curve cryptography approach is applied to handling the insider attack problem. Then the detailed working process of SCDAM with ECC algorithm is elaborated in the following section.

3  Session-Critical Distributed Authentication Method (SCDAM)

In this work, session-critical distributed authentication method (SCDAM) with elliptic curve cryptography (ECC) approach is applied to manage the data security in wireless sensor IoT devices. This method generates the key value for both sender and receiver according to the ECC method that addresses the user authentication. During the authentication process, session time and interrupts are accounted for via the end-to-end authentication process. Here, the one-time password-based authentication scheme is applied to provide data security to each session. This process manages the IoT data security for every session also eliminate the insider attack problem. The session key is engendered based on the time stamp. The previous session keys do not work on the current session; this causes the introduced method to robust against the insider and reply attacks. In addition to this, the ECC-based end-to-end authentication process and linear hash function establish further dictionary attacks in the wireless sensor IoT device.

3.1 One-time Password Scheme for Session Authentication

Wireless sensor IoT devices are used to collect the various information used to create a smart application. The gathered details are transmitted from one location to another; data security and privacy should be managed. The information is stored and sent in a distributed environment that requires the authentication process to ensure safety. Authentication is nothing but verifying user identities while accessing the IoT data, applications, and resources. The authentication process manages the trusty relationship and enables accountability. The wireless sensor IoT device information is transmitted by creating the one-time password scheme because it can only reduce the insider attack problem. The system generates a list of passwords that secretly communicated with the sender and receiver. The sender only selects the password from the list, which is saved in the server. The selection password is changed according to the user choice, which means the password is disclosed that causes the elimination of the insider attacks. The one-time authentication process has two steps: registration (the IoT device users register their details to the server and get the list of passwords for further transactions) and login & authentication (server authenticates the user to access the data).

3.2 Registration

The first step of the session-critical distributed authentication process is registration. Here, every wireless sensor IoT device users share their secrete key to the server. The secret key is denoted as SEED. For every timestamp T , the server generates the session (SK) by using random number D . Therefore, the session key is denoted as

SK=D||T (1)

With the help of the session key and secrete key, the server computes the key value as K=SEED⊕SK that is sent to the user. The computed K value is transmitted to the user, and then the user estimate the session key SK value as,

SK=SEED⊕K (2)

Afterward, the user generates the initial key ℑK value from the randomly generated secret key E value. The ℑK value is formed using Eq. (3).

ℑK=E⊕SEED (3)

After determining the secrete key E and session key SK , the number of times N should be determined, and details are transmitted to the server. The transmission should be done by performing the

ℑK⊕SK and N⊕SK .

The server was retrieving the N and ℑK values from the user transmitted details such as ℑK⊕SK and N⊕SK . Then the server computing the password by using the initial key ℑK and linear hash function as follows,

P0=HN(ℑK) (4)

In Eq. (4), H is denoted as the linear hash function, which means the data’s dynamic structure implements the hash table while generating passwords. The password is generated P0=P0⊕SK . The generated password P0 and N value is saved in the server database. The server saves the entire IoT device session details in their memory, giving each user a session I.D. to access the details. This process enables authentication while accessing the IoT details in the distributed environment. Along with P0 , P1 and P2 is computed using Eq. (5).

P1=HN−1(ℑK);P2=HN−2(ℑK) (5)

The generated passwords P0 , P1 and P2 are XOR with the respective session key SK and transmitted to the user for getting the password list. The XOR process is represented in Eq. (6)

P0⊕SKP1⊕SKP2⊕SK} (6)

The received values represented in the Eq. (6) are again XOR with the session key SK to get the original password values P0 , P1 and P2 . Here, the registration process itself enhances authentication by ensuring end-to-end authentication. For every key transmission enables the secrete while making the communication between the user and the server. This secrete communication process robust to the insider attack in the wireless sensor IoT device-based data transmission or communication.

Here, the client hashes the ℑK values for N times, and the estimated value is compared with the password. If both values are equal, then the authentication ensures that IoT communication is terminated by considering the intruder. Once the wireless Sensor IoT device user registration is completed, it will be ready to transfer the information from one location to another. The IoT device data has been accessed by login and authentication manner. The secure data access process is discussed as follows.

3.3 Login and Authentication

User authentication is the most critical step in validating user identity and providing access to the user. If the user logging to access the data tth time, the server creates the new session key SK . The SK generation is depending on the timestamp T and random number D . Here, the server estimates the password by using the hash function (H) and initial key ℑK that is defined in Eq. (7)

Pt−1=HC+1(ℑK); (7)

Here, C is computed from N-t, H is hash function. By using the Pt−1 value, server performs the XOR operation with the session key for authentication purpose such as Pt−1⊕SK and SK⊕SEED . The computed values are sent to the user; by using these values, the user calculates the session key value according to Eq. (8)

SK=Pt−1⊕(Pt−1⊕SK) (8)

The computed SK value is checked with the user timestamp value. If the value is valid, then the user estimates the SEED value using Eq. (9)

SEED=SK⊕(K) (9)

In Eq. (9), K=SEED⊕SK . The estimated SEED value is checked with the sever memory to verify the user identity. If the computed SEED value is matched with the database value, then the server’s authenticity is verified effectively.

Once the user verifies the server identity, then the session key is XORed (SK⊕Pt) With a password that is sent to the server. The server computes the password from the session key Pt=SK⊕(SK⊕Pt) . From the estimated Pt value, Pt−1 is computed by taking the hash value of Pt . If both Pt and Pt−1 is matched, then the user is verified. Then the server updates the user information, N with C; here, C = N − t. The server’s next password has been generated and transmitted to the user for accessing the next login and data access process. The following password is generated using Eq. (10).

Pt+1=SK⊕(SK⊕Pt+1). (10)

The computed Pt+1 value is stored in the database to make the next login and wireless sensor IoT data access secure. The session key distribution is maintained at every timestamp and eliminates the insider attack problem due to updating passwords in every access. In this work, the secrete key and session key played a vital role in enabling secure data access. After verifying the user details with the server database, the security is further enhanced by authorizing the user information using the Elliptic Curve Cryptography (ECC) approach.

3.4 Elliptic Curve Cryptography Based Authentication

It is one of the public-key cryptography approaches in which the encryption key is known to the public, and the decryption secretes key is kept private. The ECC approach provides security and data privacy while accessing the IoT data. The above discussed one-time critical session-based process ensures the user and server authenticity. During the user verification process, end-to-end authentication is performed to access the data from the third-party server.

The introduced method relies on short-lived concealed authentication based on an improved elliptic curve cryptography (ECC) algorithm. Here, the public and private keys are generated according to the elliptic curve equation that reduces traditional prime number involvement. The elliptic curve based generated keys are robust and complex to guess by third parties. The algorithm consumes minimum computing power and resource usage but ensures a high level of data security. The elliptic curve equation G(p) is formed according to Eq. (11).

Y2=X3+ax+b (11)

In Eq. (11), Y2 is denoted as an elliptic curve, a and b are the real numbers. With the help of these parameters, the public key and private key are generated. As discussed earlier, the user randomly chooses the secret key from [2, n − 2], and the public key is defined based on the elliptic curve. The ECC-based selected key values are transmitted between user and server for making the authentication purpose. These ECC-related key values enhance overall system security in the fastest manner. The registration, login, and authentication process are then performed to enhance wireless sensor IoT security. The detailed algorithm steps are illustrated in Table 1.

The wireless sensor IoT device information is accessed by authenticating the user and server successfully based on the algorithm steps. Here, the initial key generation depends on the Elliptic Curve Cryptography (ECC) approach, which is more secure and difficult to guess by intermediator. The full registration, login, and authentication depend on the secrete key and session key, which maintains the overall data security. In addition to this, the generated session key values with password values are varied, difficult to guess by the authenticated person for every session. The passwords are selected only by the user, which is various from every time session access. Therefore, the created system resolves the insider attack problem effectively.

4  Results and Analysis

This section evaluates the session-critical distributed authentication method (SCDAM) with elliptic curve cryptography (ECC) approach-based data security and privacy in wireless sensor IoT data transmission. This approach utilizes the session key for every transaction, and the key helps to authenticate the user and server while accessing the details. In this work, insider attack problems are considered because the IoT devices are weak to security metrics.

The SCDAM approach has distinct passwords P0 , P1 … Pn during the registration phase. Among the passwords, the user only selects the respective password, which is accessed by the insider. In this work, the shared password information is also encrypted by applying the XOR operation with the session key. Therefore, the introduced SCDAM with the ECC method robustness to the insider attack. This discussed system is implemented using NS2 simulation, Network Simulator (Version 2), widely known as NS2, is simply an event-driven simulation tool that has proved useful in studying the dynamic nature of communication networks. Simulation of wired as well as wireless network functions and protocols (e.g., routing algorithms, TCP, UDP) can be done using NS2. In general, NS2 provides users with a way of specifying such network protocols and simulating their corresponding behaviours and the attack frequency has varied from 50, 75, 100, 125 and 150 KB/s. Here attack frequency is nothing but the amount of data spent/second towards launching the attacks.

Different wireless sensor IoT devices are utilized during this process because the multimedia data such as text, audio, and video-related information are used. These data are collected by applying different IoT devices such as motion sensors, environment sensors, sockets, cameras, and smartphones. These IoT devices are utilizing the wearable technologies that are being used in various smart applications. Therefore, security should be examined while making the data transmission process. Then the introduced system utilizes the effective security mechanism from starting of the registration to data access. Therefore, the system’s excellence is validated with the percentage of affected packets while attacks on the received packet. The obtained results are compared with existing works such as SIMON block cipher lightweight cryptographic (SIMON-LC) [19], RFID with Elliptic Curve Cryptographic approach (RFID-ECC) [21], and one round cipher algorithm (ORCA) [24]. Then the respective resultant percentage of affected packets analysis is shown in Fig. 1.

Figure 1: Attack frequency vs. percentage of affected packet

Fig. 1 demonstrated that the percentage of affected packets value of session-critical distributed authentication method (SCDAM) with elliptic curve cryptography (ECC) approach that is compared with the SIMON block cipher lightweight cryptographic (SIMON-LC) [19], RFID with Elliptic Curve Cryptographic approach (RFID-ECC) [21], and one round cipher algorithm (ORCA) [24]. From the results, SCDAM has a 44.88% value on average, in case of the SIMON-LC increases from 64.57%, RFID-ECC having 58.83%, and ORCA having 52.25%. Among the methods, SCDAM with the ECC approach attains the minimum affected packet values that mean it has only 1.23% increases when the packets’ size increases gradually. The effective utilization of the session key and user selection passwords reduces the impact of the insider attacker. In addition to this, the resilience of the introduced security scheme should be examined during the frequency of attacks are varied. The resilience factor determines how effectively the wireless sensor IoT device withstands while collecting the various data even though it has different facing attacks. The system’s efficiency is compared with the number of attack frequency with the node’s resilience captured. Then the obtained result is shown in Fig. 2.

Figure 2: Attack frequency vs. resilience to node capture

Fig. 2 demonstrated that the resilience of node captured value of session-critical distributed authentication method (SCDAM) with elliptic curve cryptography (ECC) approach that is compared with the SIMON block cipher lightweight cryptographic (SIMON-LC) [19], RFID with Elliptic Curve Cryptographic approach (RFID-ECC) [21], and one round cipher algorithm (ORCA) [24]. From the results, SCDAM has a 44.88% value on average, in case of the SIMON-LC increases from 64.57%, RFID-ECC having 58.83%, and ORCA having 52.25%.

Among the methods, SCDAM with ECC approach decreases the values from 0.98 to 0.925, whereas SIMON-LC’s resilience decreases from 0.94 to 0.90, RFID-ECC decreases from 0.93 to 0.89, and ORCA decreases from 0.91 to 0.88. Hence the SCDAM with ECC attains a 5.9% higher resilience than compared to other existing methods. The introduced method uses the Y2=X3+ax+b elliptic curve to generate the fundamental values that are difficult to guess by the intermediate user. In addition to the password, users are selected to create complexity when the insider tries to get the session and secret key.

Therefore, the introduced system able to withstand its data transfer performance when different numbers of attacks present. Although the system must receive the amount of data, even the IoT device is influenced by attacks. Therefore, the aggregated throughput is measured at the receiver end. Then the obtained throughput value is shown in Fig. 3.

Figure 3: Attack frequency vs. throughput

In this process, the SCDAM with ECC algorithm uses the encryption process for every transmission performed during the registration, login, and authentication process. The transmission uses the session key that violates the insider attack also several attacks. The secure transaction process not only maintains data security also increases the throughput value. Then the Fig. 3 illustrated that the throughput value of session-critical distributed authentication method (SCDAM) with elliptic curve cryptography (ECC) approach that is compared with the SIMON block cipher lightweight cryptographic (SIMON-LC) [19], RFID with Elliptic Curve Cryptographic approach (RFID-ECC) [21], and one round cipher algorithm (ORCA) [24]. The obtained throughput is examined with different attack frequency. Compared to other methods, SCDAM with the ECC method has a higher throughput value of 11.24%.

Further, the average residual energy value of the wireless sensor IoT device should be examined. Even though the IoT devices are withstanding and can process the different attacks, it should have high residual energy. The energy of the IoT device does not lose during this authentication process. The efficiency of the residual energy of the different number of attack frequencies is computed, and the resultant value is demonstrated in Fig. 4.

Figure 4: Attack frequency vs. residual energy

Then the Fig. 4 illustrated that the residual energy value of session-critical distributed authentication method (SCDAM) with elliptic curve cryptography (ECC) approach that is compared with the SIMON block cipher lightweight cryptographic (SIMON-LC) [19], RFID with Elliptic Curve Cryptographic approach (RFID-ECC) [21], and one round cipher algorithm (ORCA) [24]. The SCDAM with the ECC method has a high residual energy value compared to other methods.

5  Conclusion

Thus the paper analyzing the session-critical distributed authentication method (SCDAM) with elliptic curve cryptography (ECC) approach based on data security in wireless sensor IoT device. Initially, the user keys such as public and private key values are generated according to the elliptic curve equation, which is more secure. The generated keys are then shared between the users and the server by registering, login, and authentication. For every session, the server and user utilize the secrete and session key to encrypt the user shared information. After authenticating the user and server, the password has been created by the server. The generated password is transmitted to the user in terms of the encrypted format. Among the passwords, the user selects the password and access the IoT details. During this process, the linear hash is utilized to generate the inside intruder’s complicated password to guess. Thus the system manages the end-to-end authentication with minimum complexity and high throughput. In the future, optimized encryption techniques are utilized to improve data security in the IoT environment.

Funding Statement:The authors received no specific funding for this study.

Conflicts of Interest:The authors declare that they have no conflicts of interest to report regarding the present study.

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