RETRACTED ARTICLE: Crypto-Stegno based model for securing medical information on IOMT platform

Abstract

The integration of the Internet of Things in medical systems referred to as the Internet of Medical Things (IoMT), which supports medical events for instance real-time diagnosis, remote monitoring of patients, real-time drug prescriptions, among others. This aids the quality of services provided by the health workers thereby improve patients’ satisfaction. However, the integrity and confidentiality of medical information on the IoMT platform remain one of the contentions that causes problems in medical services. Another serious concern with achieving protection for medical records is information confidentiality for patient’s records over the IoMT environment. Therefore, this paper proposed a Crypto-Stegno model to secure medical information on the IoMT environment. The paper validates the system on healthcare information datasets and revealed extraordinary results in respect to the quality of perceptibility, extreme opposition to data loss, extreme embedding capability and security, which made the proposed system an authentic strategy for resourceful and efficient medical information on IoTM platform.

1 Introduction

The Internet of Things (IoT) extends people’s freedom for communicating, participating and collaborating on issues [13, 27, 33]. Gradually, IoT established diverse technologies with advanced protocols and procedures [55, 62]. It performs a significant function in international communiqué between several gadgets with Internet connection wired/wireless sensors, medical devices, and devices such as ultrasonic sensors, refrigerators, etc. [33, 36]. The advancement of the IoT is projected towards transforming the medical sector as well as compel the growth of the IoMT (Islam, Kwak, Kabir, [20, 31, 33]. The IoT revolution is surpassing the human resources of today with exciting technological, political, and social perspectives. The IoMT is acquiring massive allurement from the examination association in healthcare [38, 61]. Medical devices gather critical health-related information with the aid of the Internet in the IoMT environment [9, 38, 67]. Patients are given profound supporting data to muddle through their recoveries.

Nevertheless, due to inventions of several medical gadgets, intruders can change the discourses of the gadgets, which is a life threat to serious inmates [38]. The utmost demanding security risk in which medicinal industry experience is medical information. Through the administration of gadgets in IoT [10, 19, 32, 38], more specifically (IoMT) [18], patients’ information can be hijacked by hackers using botnet [76]. Hence, the security of IoMT gadgets and medical information is crucial [6, 37] (Fig. 1).

Fig. 1

Structure of IoMT

The right information is a necessity of contemporary communication schemes at the exact time and only for the exact beneficiary. Classified information must be secured from snooping, modification, and manufacturing as an essential commodity. This is much more important for personally identifiable medical information, due to the confidential and secured structure of patient records. Protected depository and sharing of medical records are frequently threatened by a changing threat environment that is constantly developed by advanced intrusion aims, an ever-increasing number of security susceptibilities as well as un-educated and un-aware operators who handle these sensitive records. Conventional cryptographic and steganographic methods are generally used to safeguard/conceal healthcare archives; though, they frequently encounter execution faults. Steganography could protect the records by concealing them in a concealment object but, as soon as the presence of the information and the encrypting system is revealed, it’s not protected anymore. Therefore, steganography only can’t assure communication protection and is best utilized in combination with suitable encoding or scrambling techniques.

The patient data are mostly stored in the hospital as a cloud server on IoMT, which as a result makes the security vital. An additional framework is therefore needed for the safe communication and active depository of medical information intertwined with patient information, thereby enhancing the level of security of the encoding and decoding processes. This paper used Crypto-Stegno Based Model to secure Medical Information on the IoMT environment and seriously examines the security methods implemented for confidentiality fortification of healthcare information, specifically, utilizing the amalgamation of cryptography and steganography methods. The paper also examines the performance, efficiency, analysis and execution practicability of a few of the medical information methods.

The contribution of the proposed work are as follows:

• 1) The cryptography for encryption is very slow in processing hiding medical data, and the prospect of information security cannot be guaranteed using only cryptography, and there is problem of communication recover if the image in encrypted using steganography. Hence, to solved the problems of the two algorithms, the paper proposed Crypto-Stegno IoMT-based model to secure medical information on the cloud. Therefore, the contribute to both cryptography and steganography literature by developing a safety and forceful encryption, decryption, and embedding system.

• 2) This proposed method combined International Data Encryption Algorithm (IDEA) and Matrix-XOR to establish enhanced IoMT protection for medical records. The IDEA technique is incorporated for encryption before embedding the secret information in the carrier image using XOR, the cipher message was inserted into the cover image, creating a stego image which doesn’t show the scrambled message whereas the message carrier is noticeable. This created high level of security and privacy, where a causer user unable to extract the information even after receiving the message.

• 3) The used of cryptography algorithm (IDEA) helps in the communication recover if the image steganography was unable to communicate effectively, and Matrix-XOR was used to boost the speed of the algorithm. Therefore, eliminate the information extraction process for malicious users without go through the overall blocks of the algorithms. The two algorithms complement each other by an extra measurement.

2 Internet of medical things

The IoMT, likewise identified as medical IoT. IoMT is referred to as a set of aesculapian gadgets and applications connected using different networks. IoMT may also apply to all software and medical devices that are connected via computer networks to healthcare IT structures. Most healthcare facilities use IoMT software to optimize treatment, manage illnesses, minimize delays, enhance the experience of patients, manage medications, and reduce costs. The medical IoT retail sector is anticipated to strike $117 billion by 2020, as reported by market research [8, 28].

The IoMT uses information technology software as its basis for medical device assistance in communicating with the devices, instances of such applications include medical tracking gadgets, mHealth gadgets, among others. Such gadgets assist patients to relay medical information in real-time utilizing their mobile phones with Internet access. Patients with diabetes, cardiovascular conditions are deemed appropriate for remote mobile apps to monitor their health and send their health reports to medical practitioners. Such machines are used in infirmaries to deliver patient care and to avoid physician visits to the patient’s home.

To guarantee dependability and protection in homeopathic or healthcare societies a protected database is needed. Healthcare networks are vulnerable to security and privacy problems, allowing patients to suffer harmful effects such as a denial of service. Some vulnerabilities may impact one particular component more significantly than others. For example, a secure message would be further prominent in investigating and rapid intervention, while matters associated with the safety of application are probable to be further protuberant in self-care (Fig. 2).

Fig. 2

IoMT Model

As the number of gadgets related to IoT is becoming more intense, it is becoming increasingly challenging to attain vigorous protection and confidentiality. Security and privacy in the healthcare province pose an arduous problem that persistently advances with the substantial utilization of medical things (MT). The protection and privacy of the IoMT compel matters to be further complicated owing to the importance and approachability of the records in the medical province. The lack of proper security and privacy in IoMT won’t alone jeopardize the confidentiality of patients but might as well jeopardize the existence of patients. Therefore, the protection of medical information is of importance in IoMT.

IoMT interconnectivity leaves medical equipment vulnerable in similar means as further schmoosed computer systems are vulnerable to cybersecurity breaches. Unlike these other networked computing systems, however, there’s a growing apprehension that the connectivity of these healthcare gadgets will impact straightforwardly on clinical care as well as patient safety [9, 25, 72]. For instance, the Identity Theft Resource Center estimated that in 2017, the U.S. medical and healthcare industry suffered around 28% of entire data breaches, and 94% of healthcare organizations were victims of cyber-attacks even with regulations [12, 23, 58]. Patients, doctors, sanitoria and further healthcare services, therefore, need to consider possible IoMT risks to rising upcoming attacks.

3 Crypto-Stegno based model

Revolution on the internet provides an easy way of communication between two or more parties; meanwhile, it’s a big challenge to secure the information and way of communication over the internet, which is an open network. In order to address the security challenges, lots of methodologies have been suggested under cryptography (information encryption) and Steganography (information hiding) [30, 43, 47, 53, 54, 56]. Cryptography transforms secret information in such a way that it converts to an unintelligent communication to observers [4, 17, 24]. Cryptography refers to the system of covering up communications to add confidentiality in the safekeeping of the information. It offers many protection encoding schemes when interacting in an open channel or system of connection.

The essential prospect of information security can’t be guaranteed by means of utilizing cryptography alone, so alternative approach such as steganography is required to prevent risks which include a repudiation of service or comprehensive disruption of the communication system, but the problem is, it draws attention. Therefore, it is essential to have an imperceptible communication deprived of observing to anyone in the communication channel, thus steganography is required. Steganography is connected to cryptography hence complements cryptography by adding an extra measurement.

The steganography algorithms are classified based on data embedding and extraction techniques [5, 45]. These algorithms are also classified on the basis of the key used for the data embedding algorithm, this includes the pure, private, and public-key steganography. Recently, several algorithms have been established in this field and are categorized as Least Significant Bit based steganography methods, improved Least Significant Bit based methods, adaptive schemes for Least Significant Bit in the human visual system among others [7, 30, 45, 53, 54, 56, 63]. In steganography, researchers don’t just want to preserve the confidentiality of communication alone by secreting it, they want to make sure that no unauthorized individual will suspect the existence of information. The utilization of highly authenticated, genuine as well as electronically marked information in cryptography can be hard to gain entrance even for approved users at a critical period of choice-making, so a better algorithm needs to be incorporated during critical decision making [2, 15].

A choosy admittance control can’t be carried out by using solitary cryptography, which is an essential requirement for information safety, hence steganography was amalgamated as it is important to practice administrative controls and procedures. Cryptography doesn’t protect in contrast to the susceptibilities and treatments arising from the combined deficiently plan schemes, procedures, and measures [2]. This must, therefore, be resolved using a specific approach by properly planning and building a defense structure.

In steganography, once the image is focused on invasion, for instance, conversion and alternation, it becomes difficult to recuperate the picture. Communication is problematic to recuperate if the image appears in steganography is rather easy to notice occurrence with significant damage. Medical information may be susceptible to intruders or attackers utilizing either steganography or cryptography methods, thereby improving the security and robustness of medical information protection will be made possible by combining cryptography and [2, 66]. Hence, the methods were hybridized to improve and enhance one another. There are several occurrences of medical information breaches even with the encryption of data equipped with steganography and cryptography techniques on the IoMT environment. Hence, there is a need for a hybridized technique to develop a practically unbreakable and non-suspicious system. The medical information will be encrypted using a cryptography technique, thereafter a Matrix XOR encrypting procedure was utilized to entrench the scrambled record into a low intricacy cover object. The design employed prohibits the necessity for pre and/or post encoding of the medical information. This paper focuses only on IoMT’s security issue which leads to the probable invasion of the medical information. An amalgamated scheme utilizing Triple Data Encryption Standard (3DES) cryptography algorithms and the steganography encoding technique Matrix XOR was used to protect medical information stored on the IoMT platform.

4 Related work

In the modern era, IoMT is widely utilized for tele-healthcare [3, 41]. In, IoMT, the medical cloud can distribute data to several nodes via wireless medium [62, 79, 80]. Although IoMTs are the best healthcare system, medical IoT devices hold extremely sensitive patient data, so it is mandatory to provide safe IoMT communication [49, 68]. Tan, et al., (2006) [73], The lightweight identity-based cryptography (IBE-Lite) approach has been developed and claims to provide accessibility for security and confidentiality.

Nevertheless, their strategy considers various security and privacy issues as well as productivity issues. Alarm-net was developed for smart home automation based on the query protocol Wood et al., (2009) [35]. Not only was this strategy vulnerable to adversarial privacy attacks, which could expose the inhabitant’s location. On the other side, it often consumes a lot of energy, so defense requires more execution time. Modern healthcare strategies for health monitoring are provided by the BSN-care system [71]. It takes more cycles to produce random keys due to the use of external keys. External keys for protecting medical data are used in the methods discussed above for IoMT. The fundamental principles of digital watermarking are described in the most precise terms possible, Wang, et al., (2020) [52] presented the definition of watermarking, the roles provided by watermarking, and the metrics and evaluation metrics for watermarking schemes are then implemented in the corresponding section.

Data steganography is a technique used to hide data, secret message, within another data, cover carrier. It is considered as a part of information security. Audio steganography is a type of data steganography, where the secret message is hidden in audio carrier. Nassrullah, et al., (1988) [16] proposed an efficient audio steganography method that uses LSB technique. The proposed method enhances steganography performance by exploiting all carrier samples and balancing between hiding capacity and distortion ratio.

It suggests an adaptive number of hiding bits for each audio sample depending on the secret message size, the cover carrier size, and the signal to noise ratio (SNR). Comparison results show that the proposed method outperforms state of the art methods in terms of average segmental SNR, number of failing samples, and Czekanowski Distance (CZD). In addition, the proposed method shows the ability to operate with large message sizes (up to half of carrier size) with graceful degradation as opposed to the other methods which fail at large message size. So, the proposed method provides more flexibility in message and carrier sizes while preserving high efficiency.

In this modern era there is rapid increase in use of internet to exchange sensitive information. However, communication via the internet is unsecure and unreliable. Due to these factors, data hiding techniques has been proposed to increase the confidentiality and security of sensitive information. Moreover, Crandall, (2017) [48] introduced Code Based Steganography, which merges steganography with coding theory. It implemented matrix encoding using linear codes to upsurge the graphical worth of stego image by preserving high embedding capacity. Molaei et a l., (2017) [75] proposed a steganography scheme which implemented Reed Muller codes and modulus function in attempt to increase embedding capacity.

These fault tolerant schemes have ability to recover secret messages from attacks using error detection and correction. However, existing schemes have low embedding capacity (150%) and low PSNR value (48 dB). To overcome this problem, this study offered a multiple embedding method that aims to re-embed secrets bits on the same LSBs of the selected pixels based on a secret key. The experiments results show that the proposed method achieved higher embedding capacity (450%) three times more than Molaei’s method. The proposed method obtained a higher PSNR value of 51 dB and higher error correction capability.

Yaqoob et al., (2018) [21] investigated the ransomware attacks and privacy issues in IoT. In view of essential criteria, the study suggested a scientific categorization by describing and filtering the content (e.g., dangers, necessities, IEEE norms, sending level, and advancements). In addition, to warn people about how genuinely IoT devices are powerless against hazards, a few clear contextual analyses were carried out. In this report, several underlying active research difficulties (e.g. data integrity, flexible safety systems, the omission of upgradability of safety programming, fixation of capability highlights, and practical assurance of trillions of computers, trustworthiness) were identified and addressed.

Elhoseny et al., (2018) [20] presented a dynamic cryptography method in 2018 that was created as a mixture of calculations from AES and RSA. The model begins by encrypting the secret data; it hides the result in a main picture using 2D-DWT-1 L or 2D-DWT-2 L at that point. To disguise various content lengths, both shadow and gloomy surface images were used as cover images. In the case of blending pictures, the PSNR values typically ranged from 50.59 to 57.44 and in the case of darkened pixel images, from 50.52 to 56.09. For shadow images, MSE estimates ranged from 0.12 to 0.57, and for blurred scaling images, from 0.14 to 0.57. The implemented pattern showed its ability to shroud the identified medical data into a transmissible cover image to improve subtlety, limits and irrelevant decreasing in stegoimage compared to other existing and best-inclass methodologies.

Lakshmanaprabu et al., (2018) [44] introduced a multi-level design to include the excavation of enormous data in SIoT with the support of a map-reduced system alongside a targeted classifiers monitor. In relation, to minimize the disturbance and unpleasant data from the directory, a Gabor layer was used, whereas Hadoop MapReduce was also used to trace and decrease large volumes and to improve the efficiency of the proposed work. In addition, employing elephant herds modeling, the portion evaluation was conducted on a changed sample group. In order to organize the patterns and evaluate the efficiency of the proposed study, the proposed system architecture was implemented using a linear kernel support vector machine-based classifiers.

Shankar et al., (2017) [59] applied the symmetric encryption cryptographic algorithms to enhance the security and wellbeing of the images. This novel strategy was used to create different offers which were attached to encoding and decoding by techniques of elliptic curve cryptographic algorithm. The experimental findings demonstrate that the average transceiver ratio is 58.0025, the mean - squared blunder estimate is 0.1164 and the relationship coefficient is 1 for the unencrypted picture without any stretching of the first picture.

Mahmoud et al., (2018) [46] suggested the CoT methods and phases of the inquiries and also the use of CoT in magnificent field of healthcare. The study thereby affirms certain relevant CoT concerns, such as the lack of institutionalisation. In relation, with an inside and out inquiry among the most relevant proposal available in the writing, it emphasizes the importance of vitality. An evaluation of all the vitality productivity provisions discussed in this study also seems that vitality efficacy needs to be improved, especially with regard to QoS and performance.

Khan, et al., (2020) [39] present steganography-assisted secure localization of smart devices for Visual Sensor Network (VSN). The proposed system is based on The YCbCr color area achromatic-component (Y-Plane) and the spatial domain maximum probability estimation algorithm (MLEA). In this technology age, documents protection via digital media carriers is the prime issue, if a Visual Sensor Network (VSN) captures sensitive documents, then the capture documents in the situation of sending from one location to some other requires basic protection in order to maintain the strictly private. The webcam devices are smart to handle the image data in the suggested steganography-assisted Visual Sensor Network (VSN) and to retrieve sensitive details and provide the user of the system with a qualitative data for further activity.

First the image data is shifted to 90 degrees in the suggested methodology and converted into YCbCr color space. In addition, related to key providing sub-blocks in Y-Plane, the hidden image is divided into different columns of the same length, then hidden message is stored using an MLE technique (MLEA) and the subsequent sensitive information blocks are incorporated in the Y-Plane sub-image. The research results indicate that the proposed method not only improves the visual consistency of stegno-images, but also offers excellent imperceptibility, robustness and protection compared to the existing techniques.

A framework for IDEA and Matrix XOR based model have been proposed to secure the IoMT-based cloud information medical records. An experimental and performance analysis of the proposed algorithm with other ciphers has been carried out in terms of Peak Signal to Noise Ratio (PSNR), Structural Similarity Index Metric (SSIM), Root Mean Squared Error (RMSE), Mean Square Error (MSE), and computational speed.

5 Security and privacy of IoMT medical applications

Healthiness is one of the fundamental peoples’ requirements for an improved existence. Enhancing health care facilities can improve people’s value of life in any community [51, 65]. Recently, several medical service workers have accepted IoT automation to advance medical care procedures, improved information transmission amid people, decrease process faults, administer drugs as well as control sicknesses, reduce expenses and eventually advance healthcare processes’ competency and efficiency [, 8, 22, 51, 65]. However, in terms of information safety and confidentiality, the sum of related gadgets and the huge sum of impressionable datasets gathered by those gadgets have brought novel challenges. Cyber-attacks have also changed along with the rapid development of IoT and had created a recent avenue of invasion and risk to the whole medical industry. Many studies explored IoT’s numerous privacy and protection issues and device weaknesses in cloud and fog computing settings relevant to IoT-based medical management gadgets [8, 50] and [8] analyzed the IoMT protection and confidentiality taxonomy in detail.

The safety and confidentiality of records relating to patients are twofold essential notions. When we refer to record safety, this signifies that records are securely stowed and transmitted to ensure its absoluteness, genuineness, and legitimacy. Record confidentiality signifies that records can solitary be obtained by individuals who are authorized to sight and utilized it [65, 69]. More rational security measures may be established with different objectives and specifications in mind. The extensive utilization of IoMT gadgets offers an improved assurance of an individual’s health [64], but it also places a great deal of demand on record safety and concealment.

Consequently, efficacious IoMT advancement needs to accept safety and confidentiality as an essential concentration. Though most health-care establishments don’t devote sufficient funds to shield safety and confidentiality [29, 65], there isn’t any hesitation that safety and confidentiality perform a significant function in IoMT. IoMT gadgets create a growing amount of ever more complex real-time records, which is extremely delicate. On one side, the failure of health organization or system security may have catastrophic consequences. On the other hand, privacy information for the patient is accessible at all levels of record processing, record transfer, cloud storage, and record republication.

Since IoMT gadgets don’t possess enough reminiscence, computation, and information transmission abilities, they need an efficient, accessible, extreme-performance computing and huge stowage infrastructure for real-time processing and record stowage. Several IoMT organizations currently deposit the health records collected and extend their application servers into the cloud. The apps will get their medical activities uploaded into the cloud appropriately. Cloud facilities enable a hopeful clarification for the effectual administration of ubiquitous medical records through their resistance and capacity to obtain public resources and mutual infrastructure in a pervasive and universal manner. This section addresses IoMT’s protection and privacy briefly, including access control, data encryption, trusted third-party auditing, data search, and data anonymization.

Access control

Access control is the way an information scheme determines an individual’s uniqueness and predefined rules that prohibit unauthorized individuals from retrieving resources [34, 65]. Access control involves various encryption methods, such as symmetric key encryption (SKE), asymmetric key encryption (AKE), and attribute-based encryption (ABE) [65].

Data encryption

Universal data encryption could be executed at three communication phases: connection encoding, node encoding, and end-to-end encoding. The communication acquired from the earlier connection will be decoded into a readable form for any transitional node in associated encryption, and the readable text will thereafter be encoded into scrambled-text by utilizing the undisclosed key of the following connection [65]. Unlike liaison encryption, node encryption doesn’t require plaintext communications in the system node. So, node encryption can deliver huge network data protection. The message is not decrypted once utilizing end-to-end encryption until it is forwarded to the destination. Since communications are continually existing as scrambled-text all through to protect e-health public services, vital organization procedures execute a significant function in the protection method. Nevertheless, the communication frequency could be greatly altered by intricated encryption systems or transmission protocols, and as well fail to perform data transmission. In fact, they must use important medical services that are not accessible. Scientific and cautious steps are needed to solve the hard equilibrium between safety, protection, and system application consumption [65]. Protection matters have been key impediments to e-health systems that deliver unremarkable assistance to the aging and weak individuals owing to the inadequate funds obtainable and confidentiality apprehensions.

Trusted third-party auditing

Cloud servers aren’t completely reliable. Where data manipulation, as well as erasure, occurs lacking consumer authorization, the quality and accuracy of healthcare records deposited in the cloud may be in jeopardy. The data standards are usually particularized by the consumer for security reasons so that the server supplier isn’t in an undeviating connection with the record basis. Furthermore, the reputable Trusted Third Party (TTP), which delivers the impartial audit outcomes, could be properly presented to allow cloud service providers to be accountable and to shield the authentic advantages of cloud operators [26, 65]. Trusted third-party inspecting to enhance security in cloud storage. Wireless Transmission. TTP’s work issues consist of complex audit, batch auditing, and performance measurement auditing.

Data search

Sensitive data must be scrambled before contracting out to preserve data confidentiality, which obsolescence the current use of data built on readable keyword searches. Allowing an encoded record pursuit service in the cloud is thus of utmost significance [14]. The main approaches for searchable encryption consist of searchable symmetric encryption (SSE) and keyword search public-key encryption (PEKS). It should as well be remembered that the further sophisticated the encryption methods, the easier it is to scan the data, and the easier it is to verify the accuracy of the search results. If the results of the search cannot be enforced appropriately then all protection and privacy safeguards have less value [65].

Data anonymization

Patient-delicate records can be detached into three classifications: explicit identifiers, quasi-identifiers, and attributes to privacy. An explicit identifier, for instance, an ID number, name, and cell phone number can uniquely indicate a patient. An amalgamation of quasi-identifiers may as well provide a specific indication of a patient, such as age, birth information, and address. Information on privacy ascribes to a patient’s delicate characteristics, which includes sickness and profits. While considering the allocation features of the earliest data in the procedure of data publication, it’s crucial to guarantee that the personal characteristics of the novel dataset are accurately treated to assure the confidentiality of the patient. Currently, haphazard perturbation expertise and anonymous data technology are typically utilized to resolve such issues as k-anonymity, l-diversity, and confidence bounding. The conventional k-anonymity is particularly extensively utilized. The disadvantage, however, is that it doesn’t restrict delicate records, and invaders may utilize steadiness invasion and contextual information invasion to recognize delicate information and individual communication, resulting in privacy loss [65].

Security and privacy for IoT devices remain huge issues that bring a whole new degree of user privacy concerns online [74]. This is because such apps can only collect personal information, such as the names of users and telephone numbers, but can also track user behaviors (e.g., when users are in their homes and what they had at lunchtime). It is therefore very important to build an IoMT based on security and privacy to ensure trust and privacy for users during the use of IoMT.

6 The proposed techniques

First, cryptography describes IDEA’s execution of encrypting the confidential message in a text or file mode to achieve advanced confidentiality. Secondly, the Matrix-XOR procedure and the grey code method were utilized to insert the scrambled message into image pixels to shield the undisclosed message inside the carrier medium which constitutes one more solitary layer of fortification. The IDEA and Matrix-XOR algorithm principle offers two-tier security for safe message communication through an optimized message network and is separated into 2 steps. The first step accomplished the encoding procedure thereafter entrenches the scrambled message into the carrier medium, while the next one describes the retrieval of the hidden message followed by the decoding process.

6.1 The international data encryption algorithm

Using a 128 bit input key K, the Concept encrypts 64-bit plaintext blocks into 64-bit ciphertext blocks. The algorithm consists of an output transformation followed by eight identical rounds. The six 16-bit subkeys used in each round anyway ${K}_i^{(r)},1\le i\le 6$, To convert a 64-bit X input into four 16-bit block outputs, which are then added to the next round. The 128-bit input key K derives all the subkeys. In decryption mode, the subkey derivation process varies from the encryption mode, but otherwise encryption and decryption are carried out with the same hardware.

IDEA uses only three operations on 16-bit sub-blocks a and b: bitwise XOR denoted by ⊕, unsigned addition mod (2¹⁶) denoted by ⊞ and modulo (2¹⁶ + 1) multiplication, denoted by ʘ. All these three operations are derived from different algebraic groups of (2¹⁶) Elements that are vital to IDEA’s algorithmic power. Of the three arithmetic operations, bitwise XOR and unsigned addition mod (2¹⁶) are trivial to implement, while multiplication requires careful design and bit-level optimization for both area-efficient and quick implementations of modulo (2¹⁶ + 1).

Except for key scheduling, the IDEA algorithm is defined as follows: [70].

INPUT: 64-bit plaintext M = m₁…m₆₄; 128-bit key K = k₁…k₁₂₈.

OUTPUT: 64-bit ciphertext block Y = (Y₁, Y₂, Y₃, Y₄).

• 1. (Key schedule) Compute 16-bit subkeys ${K}_1^{(r)},\dots, {K}_6^{(r)}\ \mathrm{for}\ \mathrm{rounds}\ 1\le r\le 8,\mathrm{and}\ {K}_1^{(9)},\dots, {K}_4^{(9)}$ for the output transformation.

• 2. a

$$ \left({X}_1,\kern0.5em {X}_2,{X}_3,{X}_4\right)\leftarrow \left({m}_1\dots {m}_{16},{m}_{17}\dots {m}_{32},{m}_{33}\dots {m}_{48},{m}_{49}\dots {m}_{64}\right), where\ {X}_i\ is\ a\ 16- bit\ data\ store $$

(1)

• 3. For round r from 1 to 128 do:

(a)

(2)

(b)

(3)

(c)

(4)

• 4.
  

  (5)

In IDEA, a ʘ b corresponds to modulo (2¹⁶ + 1) multiplication of two unsigned 16-bit integers a and b, w here $0\in {\mathbb{Z}}_{2^{16}}$ is associated with $\left({2}^{16}\right)\in {\mathbb{Z}}_{2^{16}+1}$ as follows: if a = 0 or b = 0, replace it by (2¹⁶) (which is ≡ − 1 mod (2¹⁶ + 1)) prior to modular multiplication; and if the result is (2¹⁶), replace this by 0. Decryption is achieved with the ciphertext Y provided as input M. Key scheduling is described in standard textbooks on cryptography [57, 70], and its hardware requirements are negligible when compared to modulo (2¹⁶) multipliers.

6.2 Crypto-Stegno framework for secure transmission of medical information on IoMT-based platforms

The Internet of Things (IoT) provides computing tools as extremely flexible as web services. With the rapid growth of IoT and cloud computing technology, a growing number of individuals, organizations, and businesses prefer IoT and cloud platforms for storing and manipulating their data. Cloud computing has major benefits including cloud storage, connectivity, data sharing, hardware and software cost savings, etc. Many security challenges attributed to the IoMT environment, however, have not yet been addressed, especially in traditional computer environments [8, 50]. Moreover, protection and privacy concerns have been observed to seriously limit practical implementations of IoMT technologies [8]. To tackle these major problems, it is important to propose and develop new algorithms and methods to secure the IoMT platform and infrastructure.

In this section, the paper suggested an enhanced novel method built on an amalgamation of steganography and cryptography procedures to hide the undisclosed message into a cover object to deliver satisfactory fortification for the concealed message transmission utilizing a standard IoMT transmission channel. This combination of approach has positively achieved the targeted standard of certain critical characteristics such as information confidentiality, efficiency and sturdiness, proof of the outstanding performance, and efficient application of this steganography method. Cryptography describes IDEA’s implementation of encrypting the conceal data in text or file form to achieve advanced security.

The primary goal of protection is reached in the field of data transmission through the combined techniques. Figure 3 displays a general block illustration of the postulated system. This describes the precise combination notion of the IDEA and XOR steganography algorithms that deliver two-tier security for secure message conveyance through an IoMT-based network. In the local network, the device is configured to investigate the security and reliability of image data.

Fig. 3

Proposed crypto-stegno based model for securing images on IoMT

This research combined IDEA and Matrix-XOR to establish enhanced IoMT protection for medical records. Using XOR, the cipher message was inserted into the cover image, creating a stego image which doesn’t show the scrambled message whereas the message carrier is noticeable. The procedure to retrieve the medical information will be reversed. The whole system phase is outlined as followed:

• Step 1: Load Medical image

• Step 2: Generate a medical Code/ medical Template

• Step 3: Create an undisclosed key utilizing IDEA.

• Step 4: Implement the IDEA Encryption to an image utilizing the undisclosed key created.

• Step 5: Choose a cover object and convert the carrier medium to binary form

• Step 6: Maneuver the XOR of every pixel of the carrier medium and alter the carrier medium of the XOR with every bit of concealed message one after the other.

• Step 7: Display stego image

• Step 8: Conserve the stego image.

The framework for the IoMT-based structure in the postulated approach is outlined as follows.

• Cover information producer: active creation of the steganographic image.

• Stowage server: stock the steganographic messages that are transferred from the customer.

• Customer: Entered the communication, conceal it into the steganographic object, and transfer it to the storage server.

6.3 Stage I

The hidden message entrenching process of projected technique is elucidated as outlined:

• Step 1: Choose the entered-incomprehensible textual file that is prepared to be concealed in the carrier image.

• Step 2: Finalize the carrier medium from the sender documents.

• Step 3: Firstly, encode the hidden message utilizing the IDEA approach.

• Step 4: The scrambled secret message from step 3 is concealed into the carrier object utilizing the Matrix-XOR procedure.

• Step 5: Transfer the subsequent stego image acquired from step 4 on the IoMT cloud.

6.4 Stage II

The hidden message extraction process from the stego image is described as outlined:

• Step 1: Pick the stego image that is to be moved.

• Step 2: Copy the stego image from the IoMT-based cloud.

• Step 3: Decode the hidden textual communication from the stego image utilizing the Matrix-XOR procedure.

• Step 4: Apply the IDEA decryption process.

The anticipated process of IDEA and Matrix-XOR system comprises of the two sections.

Method for encryption procedure

The fortification procedure of hidden message is completed by applying asymmetric encryption procedure called IDEA, and the equivalent verification code is utilized for hidden message inserted and retrieved. The method of decryption is performed utilizing the notion of the same encryption procedure for the extraction of hidden textual from carrier image except that sub-keys are derived utilizing another process that would be enhanced by altering the extent of an undisclosed key employed in the encoding and decoding processes on the communication. The block encryption IDEA functions with 16-bit readable text and scrambled text blocks and is measured by a 32-bit key.

The Plain IDEA method defines that there’re four matching cycles and a “semi cycle” end alteration and fuses three algebraic processes on nibbles (4-bit blocks): bitwise XOR, addition modulo 24 (=16) and multiplication modulo 24? 1(=17). There’re 16 probable nibbles, amongst which 14 phases of a whole cycle are specified at this juncture.

The subsequent phases demonstrate the system procedure.

Input: hidden message, undisclosed key.

Output: Scrambled message.

Let the readable message bits be stowed in A1–A4 and the 28 subkeys be termed as X1–X28.

• Step 1: Compel multiplication of A1 and sub-key X1.

• Step 2: Compel the addition of A2 and sub-key X2.

• Step 3: Compel the addition of A3 and sub-key X3.

• Step 4: Compel multiplication of A4 and sub-key X4.

• Step 5: XOR the outcomes of actions step 1and step 2.

• Step 6: XOR the outcomes of actions step 2 and step 4.

• Step 7: Compel multiplication of the outcome of action e and sub-key X5.

• Step 8: Compel addition of the actions step 6 and step 7.

• Step 9: Compel multiplication of the outcome of action h and sub-key X6.

• Step 10: Create the addition of actions step 7 and step 9.

• Step 11: Compel XOR the outcome of actions steps 1 and step 9.

• Step 12: Compel XOR the outcomes of actions step 3 and step 9.

• Step 13: Compel XOR the outcomes of actions step 2 and 10.

• Step 14: Compel XOR the outcomes of actions step 4 and step 10.

The procedure is recurred from step 1 to step 14 for the lingering three cycles, but with separate sub-keys. The last alteration transpires, next to the accomplishment of series 4, thereafter the concluding alteration transpires, which comprises of the subsequent phases.

• Step 15: Compel multiplication of A1 and the sub-key Y25.

• Step 16: Compel the addition of A2 and the sub-key Y26.

• Step 17: Compel addition of A3 and the sub-key Y27.

• Step 18: Compel multiplication of A4 and the fourth sub-key Y28.

Immediately these phases are completed, the aftermath bits are clustered into 7 bits and their equivalent characters are constituted, which signify the scrambled information. The scrambled messages are stowed in a file.

Method for information entrenching

The following make clear the process of communication embedding procedure.

Input: cover image, scrambled text.

Output: stego image.

• Step 1: Select the apportioned cover image from the sender.

• Step 2: The cover image is divided into 4 8-bit planes and they signify the grey code order (set1 depict the value 00, set2 depict the value 01, set3 depict the value 11 and set4 depict the value 10).

• Step 3: Interpret the scrambled message as a product of the encryption process and the equivalent is transformed into the ASCII code system all through to the last text.

• Step 4: The outcome of the previously quoted step is transformed into a binary bit, and if its overall addition is an odd digit, at that moment an extra bit ‘0’ is to be introduced in the end.

Else, there isn’t any modification in the procedure.

• Step 4a: Lastly, the overall binary bit is divided into 2-bit blocks for a key contribution of the anticipated system.

• Step 4b: The 2-bit blocks are confirmed with a grey code set itemized in step 2 to couple it with bit value. Once the outcome of this confirmation is true, the equivalent pixel is picked and the first LSB bit is transformed as ‘1’ and the lingering pixel’s first LSB positions are noticeable as ‘0’up to its last pixel. The phase 4b process is recurrent for second and third LSB bits, and in the end, the stego image is attained.

6.5 Method for information extraction utilizing matrix-XOR procedure

The similar sequences of entrenching procedures are outlined in the converse path to retrieve the hidden messages in the stego image by applying the deciphering technique on the stego image acquired from the correspondent. The comprehensive message recovering procedure is highlighted here.

Input: stego image.

Output: scrambled information.

• Step 1: Analyze the obtained stego image.

• Step 2: The obtained image format is divided into 4 8-bit pixels, and the pixels depict the grey code direction.

• Step 3: Recover the pixels that have the value ‘1’ in their Matrix-XOR location. The step 3 process is recurrent for second and third Matrix-XOR bits.

• Step 4: Create out the set estimation in accordance with the utilized position.

• Step 5: The greater result is divided into a 7-bit block up to its last pixel, and this block is transformed into a decimal system that depicts the precise ASCII value of the scrambled message.

• Step 6: The ASCII values are changed into their equivalent identity to attain the cipher message material.

For step 1 and step 2 the following were taking:

• Step 1 (Permutative Straddling): As long as there’s no requirement to utilize the full size to hide the scrambled information, the image fragment stays unutilized. This complication is abolished with permutative straddling. This practice diffuses the conceal communication over the whole cover image; i.e., over the whole image. A Permutation is determined by a password established on a key. Once an individual has the correct key, a similar permutation can recur.

• Step 2 (Encoding): There are several procedures for entrenching an undisclosed message into an object block. By presenting the Matrix XOR encrypting procedure, the anticipated study improves entrenching proficiency. The alteration of triple(f, k, g(i)) to quad(e, k, g(i)) and the density of the scrambled communication improves the proficiency of this procedure. The Matrix XOR procedure entrenches the g(i) chaotic sequence (undisclosed message) in the enhanced object block (carrier block). In this procedure, the one-bit block from the carrier medium block is substituted with the scrambled message block. The one-bit entrenching procedure is implemented utilizing the following equation:

$$ {M}_e=D\oplus C $$

(6)

wherever the binary message bit is, D and C is the binary image bit block. Two requirements must be fulfilled to perform this entrenching procedure.

Requirement 1: For the two blocks, if the XOR process fallouts in a zero, therefore there isn’t any necessity to alter the ending bit location.

Requirement 2: For the two blocks, if the XOR process doesn’t fallout in zero, then there is an alteration of the carrier medium block (i.e., zero to one or one to zero). Subsequent to determining the bit location for the carrier medium block, the entrenching procedure is implemented built on the following equation:

$$ {M}_e=\left\{\left(\left(d(i)\oplus c(i){c}^{"}(i)\right)+{\left(d(i)\oplus c(i)\right)}^{"}\ {c}^{"}\ (i)\ \right)\right\} $$

(7)

7 Result and discussions

This work used the combination of IDEA cryptography and the Matrix-XOR steganography algorithms to implement a safe medical image. MATLAB 2013A was utilized to develop the framework, the software was approved to have strong essential math, signal, and image processing functionality. The iris templates from CASIA Iris Image Database V3.0 were selected. The iris template was created after the segmentation, normalization, and extraction of the features, after which a unit-eye image was chosen from the CASIA database for the experiment. Iris template was therefore protected utilizing IDEA and the scrambled templates were thereafter concealed in a carrier medium utilizing Matrix-XOR to generate an image called stego images .

Inspired by the appropriateness and tamper-proof security offered by cryptography and steganography algorithms, the paper presented a robust Crypto-Stegno medical image technique based on IDEA and Matrix-XOR to ensure image transmission on IoMT-based healthcare platforms.

Unlike traditional methods, the proposed methodology was based on the Crypto-Stegno method’s classical renditions, which made it tenable to secure images against the misuse feared when physically significant hardware is performed, subject to necessary refinements. In particular, the scheme used the Crypto-Stegno classical transcription power for both the embedding and extraction processes while the application was tailored to the medical images. The Crypto-Stegno was used to determine areas of the carrier image by overlaying the secret bits. The design proposed prevented the necessity for pre- or post-encryption and extraction procedures which implied that only the stego image was necessary to extract the hidden image. The proposed method was extensively tested on the CASIA Iris Image Database V3.0 dataset consisting of iris images of color. Illustration 5 presents the findings and images obtained by embedding the image of the hidden medical iris (presented earlier in Fig. 4) in the image of the cover color. (Fig. 5)

Fig. 4

Sample Iris Images.

Fig. 5

Sample cover Images

Fig. 6

Time Complexity of the Proposed System

To further show the efficiency of the proposed IDEA and Matrix-XOR model, the time complexity of the system was evaluated and compared with some existing models like LSB steganography, FMO steganography, and optimized modified matrix encoding (OMME) steganography. From Fig. 6, the result show that the proposed system performed better in term of time complexity with 0.36, and the closest system is OMME with 0.40-time complexity.

Table 1 offered a comparative overview of the output relative to other simulation-based image hiding approaches in terms of embedding ability as well as mean values for Peak Signal to Noise Ratio (PSNR), Structural Similarity Index Metric (SSIM), Root Mean Squared Error (RMSE) and Mean Square Error (MSE) to establish the competence and effectiveness of the projected process.

Table 1 Summarized outcomes of the performance comparison

The outcome of the projected scheme was correlated with few current medical image securities that employed separate approaches. PSNR, SSIM, RMSE, and MSE were utilized as the criterion for performance evaluation. [20] Amalgam optimization with cryptography method for medical image safety in IoT, afterward analyzed the error distribution of image using PSNR and MSE and recorded a PSNR of 58.22 and 0.9234 MSE. [40] Safeguarding information in the Internet of Things (IoT) utilizing Cryptography and Steganography Procedures reported a PSNR of 62.44and 1.4314 of MSE. [60] in their recent work of Dual-layer security of image steganography built on IDEA and LSBG procedure in the cloud location, and recorded PSNR of 54.85, SSIM of 0.9967, RMSE of 0.92556 and MSE of 0.8565. [1] in their work recorded PSNR of 44.59 and SSIM of 0.9774. Compiled outcomes of the performance comparison for medical image protection approaches are presented in Table 1.

To authenticate the performance of our system, we relate our projected amalgam method utilizing cryptography (IDEA) and steganography (Matrix-XOR) with other current methodologies in literature. As represented in performance evaluation, it can be noticed that the projected system achieved excellently than the other methods with consideration to PSNR, RMSE, and MSE in Table 1. The excellent performance was owed to the amalgamation of two procedures; therefore, the projected method guaranteed that delicate messages or communications were shielded from illegitimate individuals by disclosing solitary the scrambled file information to IoMT authorized users.

Table 2 present comparative analysis of encryption and decryption time for different size of algorithm. We analyzed computational time for IDEA with Matrix XOR algorithm with the existing method by (Khalifa, et al., [42] using ECC-based-Hash and OTK, RSA with SHA-1.

Table 2 Summarized outcomes of the performance comparison

8 Conclusion and future research direction

IoT-based systems have been developed and implemented in recent years in medical fields and this is called IoMT, but in some cases, data stored in the IoMT-based environment via cloud storage are open to various cyber-attack methods to recite/inscribe information via third parties. This is considered to be a major privacy and security risk or problem to the implementation of IoMT-based system. This has inspired the recent study using steganography to advance the safety of image communication in the IoMT platform. This paper has suggested a technique using the IDEA principle in conjunction with the steganography technique Matrix-XOR. The Matrix-XOR procedure in image method for implanting the undisclosed message into the carrier medium, this delivers the steganographic image with a better-quality entrenching efficiency, satisfactory protection, and minimal alteration aftermath. The author proposed an approach to secretly transfer data in the IoMT-based environment built on steganography and cryptography procedures. This hybrid methodology achieves information privacy, completeness assurance, efficiency, and sturdiness that proves successful for the achievement of the processes. The performance of the proposed system indicated that the model performed well in comparison to other state-of-the-art techniques, indicating possible uses as a veritable tool for effective privacy and security of medical images on future IoMT-based information. In future, the proposed hybrid model can be use on audio and video IoMT-based healthcare capture data and information on the cloud. The information and data security and privacy of IoMT-based system are quite important especially for medical images like X-ray, Radiology, ultrasound, magnetic resonance imaging (MRI), and positron-emission tomography (PET) among others. Hence, future implementation needs more efficient security algorithms to be implemented like DNA encryption, fully homomorphic encryption, and Bcrypt on the cloud, thus enhance the privacy and security of IoMT-based system. Also, a lot of research that focused on IoMT-based system privacy and security has used RSA and AES on both private and public data. In future work, machine learning techniques need to be further integrated to address issues relating to heterogeneous and constantly evolving medical information inputs. The proposed work takes less time for both encryption and decryption process, thereby help in speedy up the information retrieval form the IoMT-based devices, thus resulting in a safety and dynamic encryption, decryption, and embedding system.