485
Protecting IoT based transmitted data security using tokenized multiple layered encryption techniques
MOHANAD FAEQ ALI
Faculty of Information and Communications Technology,UTeM, Durian Tunggal,Melaka, Malaysia.
[email protected] NORHARYATI HARUM
Faculty of Information and Communications Technology, UTeM, Durian Tunggal,Melaka, Malaysia.
[email protected] NUR AZMAN ABU
Faculty of Information and Communications Technology, UTeM, Durian Tunggal,Melaka, Malaysia.
MOHAMMED NASSER AL-MHIQANI
Faculty of Information and Communications Technology, UTeM, Durian Tunggal,Melaka, Malaysia.
[email protected] MOHAMMED SAAD TALIB
Faculty of Information and Communications Technology, UTeM, Durian Tunggal,Melaka, Malaysia.
[email protected] ALI A. MOHAMMED
Faculty of Information and Communications Technology, UTeM, Durian Tunggal,Melaka, Malaysia.
Abstract
Now-a-days the development of Internet of Things (IoT) is increased rapidly in different applications. The created IoT consists of several connected devices which are used to transmit the information from one device to another device. During the data transmission process, security and privacy is one of the serious issues. The security issue creating more vulnerabilities and difficulties while accessing the data. There are several traditional techniques are used to manage the data security but they are failing to maintain the information. Most of the information is maintained by creating the password which used for long time that also creating the security problem. So, in this system uses the tokenized multiple layered encryption technique to creating the security to transmitted information. The created system uses the three layer of encryption technique along with tokenized process, which successfully ensures the protection to data in every layer. In addition to this, each layer uses the specific encryption technique, which creates the difficulties while guessing key value. This created IoT based secure data transmission process efficiency is evaluated using experimental results.
Keywords:
Internet of Things, security, tokenized multiple layered encryption techniques, three-layer, experimental results.
1.Introduction
Internet of thing (IoT) [1] is one of the emerging technologies, which consists of several inter- connected device that used to transmit the information from one place to another place via internet connection. The internet connections are provided to devices, digital machines, mechanical machines and objects while transmitting data. Allowing the devices to accessing the internet connect creates the several vulnerabilities. Even though, the IoT itself having the security [2] concept to acts as the safeguard to connected devices, sometimes, the security related vulnerabilities [3] are increased drastically if the data is not protected correctly. The IoT device information is accessed by common users, so, the attacks are generally happened in the network which creates the difficulties in safety measures. There are several challenges are involved while providing the security to IoT device [4] related information in IoT environment. The development of IoT environment, network appliances and other developments created difficulties while trying to providing the security. In addition to this, the markets are more interest to delivery their IoT smart device product to customers instead of maintaining the quality and safety product to customers. One of the critical issues involved in IoT security is maintaining hardcode that is default password [5] for every type of information accessing process. Suppose, the default passwords are changed, the security of the information is still one of the critical factors because, hackers are easily guessing the user password. Other issues of IoT security is, most of the IoT devices are fixed with the life time on machine, that never receives the updates regarding the security [6] that time intermediate user easily access the information.
According to the survey of 1990’s most of the security expert identifies that unsecured devices are accessed by intermediate user and access the smart devices [7]such as refrigerator, TV, baby monitoring device to access the children activities and that uses the entry point in the application.
Further, the study is extent in 2010, Stuxnet virus is used to by several user to create the physical damage in Iranian Centrifuge [34][36]. This attack starts in 2006 and developed in 2009, in which the virus targets the supervisory control acquisition systems. The systems infected by malware virus which is passed to the programmable logic controllers. In 2013, the security is affected in IoT botnet [8] because 25% of smart IOT devices such as household appliance, baby monitoring system, smart TV and etc. are created using computer. Due to the system- based device development process affects by injecting the virus. The research is continuous by Charlie miler and chris valasek in 2015, the virus is affect the jeep and trying to change the ratio station.
Due to the changes of its function, air conditioner and accelerators are stop working because of engine is affected. This IoT based security [9] issues are further analyzed in 2017, food drug administration, which warns the system against the system security. There several intrusion attacks, virus and malware are affect the several IoT device related information. So, the several security methods are created depending on the IoT applications and IoT ecosystems. During the development process several solutions are created for handling the system [10] issues in critical situation. There are different security measures such as digital certificates, incorporating security, identity management process, API security, hardware security, network security, network access control, security gateway, patch management, continuous software updates, consumer education and integrating teams are used to protect the IoT device [11][35] and related information.
487 Even though, the IoT device is chosen the effective security measures, the data is transmitted to the other device via the internet which is hacked by intermediate user. So, the security of the data must be managed because, the transmitted data is more crucial information, then the quality of the data should be maintained correctly. The traditional encryption system [12][33] provides the security, authentication and authorization to the shared data, but they are having several difficulties such as key generation is complex in some situation, quite slow, requiring a greater number of factorizations, complexity while developing, minimum life span and man in the middle attack. Due to these issues and difficulties, in this work effective multiple layer of encryption is introduced before transmitting data from one device to another device. The introduced techniques ensure the security in every layer, that improves the overall safety and quality of the data. More ever, the system uses the different algorithm in every layer, so, the generated key is difficult to access by third party. Although, the system uses the various encryption techniques, that provide security very fast compared to different encryption algorithm and eliminates the man in the middle attack successfully. The introduced system is developed using the Burp Suite development tool [13] which helps to analyze the security related vulnerabilities, application attack issues and other testing process effectively. The efficiency of the system is evaluated using various parameters such as encryption time, decryption time, throughput, CPU processing time, memory utilization and accuracy of security. Then the rest of the manuscript is organized as follows, section 2 analyze the various researcher opinions regarding data transmission security, section 3 discusses about the tokenized multiple layered encryption techniques based IoT data transmission security, section 4 evaluate the efficiency of tokenized multiple layered encryption techniques based IoT data transmission security and concludes in section 5.
2. Related Works
In this section discusses about the different researcher work on the IoT-data transmission security in various applications. (Chikouche, N et al., 2019)[14] developing the effective privacy preserving authentication protocol-based security IoT data transmission in IoT environment. The developed system effectively utilizes the post quantum cryptography-based schemes which successfully eliminates the different attacks such as replay attack, desynchronization attacks and quantum attacks. The successful detection of these attacks improves the data transmission process in IoT environment effectively. (Kuzminykh I et al., 2019) [15] discussing the various encryption algorithms to examine the lifetime of the IoT device. The IoT device is affected due to the low energy consumption, intermediate attacks and other manufacture reasons. Among the above issue, security is one of the main reasons to minimize the IoT device life span. For overcoming the above issues, various data encryption algorithms are introduced because, the device lifetime span is determined according to the algorithm key length and algorithm principles. Thus, the introduced system successfully maximizes the network lifetime compared to other security approaches. (Mohamed Elhoseny et al., 2018) [16] developing the system for making the effective and security medical data transmission model in IoT environment. The created system transmits both images and data, so, the privacy and security of the image is managed with the help of steganography techniques with encryption algorithms. During this process, various cryptographic algorithms such as Rivest Shamir, advanced encryption
algorithm, Adelman algorithms are used with the discrete wavelet transform technique. The method effectively creates the security to the transmitted medical data successfully. Then the efficiency of the system is evaluated using experimental analysis, in which systems ensures minimum error rate on gray scale and color image and attains high accuracy of security.
(Xiruo Liu, et al., 2017) [17] analyzing the security framework in internet of things for ensuring the security in future data transmission process. Initially, mobility first frame work is created to maintain the security in IoT which integrated with the local system with global IoT systems. This effective IoT integration process maintains the interoperability, usability without having internet loss also protect the data security. During the secure framework creation process, heterogeneous hardware is proposed in terms of resolution services. The resolution services key components are created in the middle layer in which the light weight key protocol is used to establish the security related services in IoT environment successfully. (Sriram Sankaran et al., 2016)[18]introducing the lightweight security framework in internet of things (IoT) system using the identity based cryptographic techniques. During this process, the developed identity-based techniques examines each user activities and identities for detecting the changes in the user activities successfully.
This secure IoT-related data transmission system is developed using RELIC and Contiki simulation tool, in which system provides high security for data and minimum overheads in IoT.
According to the above researchers’ opinions, security related ideas clearly shows that the IoT requires the security mechanisms for improving the overall data transmission process. Even though, the discussed techniques ensure enough security, it takes time and man in the middle attack is still have complexity. For overcoming the above difficulties, in this work effective security technique called tokenized multiple layered encryption techniques is used to ensure the IoT data transmission security. The detailed working process of tokenized multiple layered encryption techniques related secure IoT data transmission process is discussed in section 3.
3. Tokenized Multiple Layered Encryption Techniques Based IoT Data Transmission Security
In this section discusses about thetokenized multiple layered encryption techniques based IoT data transmission security process. In this work different IoT dataset information is used to transmit the data from one location to another location because to determine the efficiency of the system. The detailed description of dataset used in this work is discussed as follows.
3.1 Detail Description of IoT Dataset AMPDs IoT Dataset
The almanac of minutely power dataset is named as AMPds[19], which helps to researcher to examine the load disaggregation. The dataset consists of several information such as natural gas, electricity, water level which is measured in one-minute interval. Totally, the dataset has 1,051,200 readings which is gathered in 2 year of monitoring process. In addition to this details, dataset has weather data that is collected from the environment Canada YVR weather station.
The weather data is captured which is transmitted to one location to another location for examining the climate details in future research purpose.
489 Mhealth dataset
The next utilized dataset is Mhealth [20]which collects according to the mobile application. The small sensor is fixed in three places of human body. The placed sensors are examining the patient activities by conducting 12 different physical activities. The placed smart sensor is capturing the patient heart electrical activities by continuous capturing of ECG measurements.
Totally 10 subjects are used in this work to capture the heart related activities and information is captured successfully.
CCAFS Dataset
Climate Changed and Food Security dataset (CCAFS) [21] which consists of several agriculture related information in terms of global and regional information. The data is continuously capturing the agricultural information, climate details, production, livestock, ecosystem services, hydrology details effectively by using the smart device.
As discussed above datasets are used in this research work, each dataset is different domains, in this work, the effective encryption algorithm is used to encrypt the details which ensures the security to the data. The collected IoT data is transmitted from one location to another location, during this time, intermediate users are access the broadcasting data, that create the severe problem in future and data analytics process. As discussed earlier, the IoT device have self- security mechanisms but they are providing security while capturing the data. During the transmission process, data may be accesses by several intermediate users as well as malware attack that reduce the efficiency and quality of transmitted data. So, the quality of transmitted IoT data should be managed with the help of effective encryption algorithm. The detailed working process is discussed as follows.
3.2 Encryption Method to Ensuring Security in IoT Data Transmission process
In this section describes the detailed security establishment process in IoT data transmission process. Initially, the IoT device collects the data from one application ex: human body activities, agricultural activities, weather condition, power station and so on. The collected information must be transmitted to another location. The collected data consists of several sensitive information, patient disease details, medicine information, rainfall level, chemical level in food and etc. The transmitted data is accessed by third party server which completely reduce the quality of that data. During the transmission process, original data is processed by the tokenization [22] process which ensures the data security, with minimum computation time and resources. Tokenization is one of the effective data security process which replace the sensitive data with non-sensitive data. Generally, tokenization process generates the random number of every transmitting data that completely depends on the token generator server. The generated token system is difficult to predict by third party because, the server changes the sensitive value into non-sensitive information. The created system protects the transmit data from third party access, malware attack and ensure the authentication as well as authorization. The main reason for choosing this tokenization in this work is, the tokens are generated according to the plain text which does not require any mathematical computation, maintains of the data token [23] also easy by database, difficulty while accessing original data because, they require token value that is
complex to guess. IoT transmitted data is never leave from the transmission zone because, it requires several compliance requirements and strength of the security is high. Due to these reasons, in this work tokenization is chosen for basic security establishment process. Considered, the IoT device transmit the patient health information like, temperature, heart rate, patient name, personal information, disease information and etc. The transmitted information must be tokenized which is done by random generated alphanumeric token ID [24]. Let patient temperature is 101.1° 𝐶, it is tokenized like, 𝑎7ℎ%6𝑡𝑓 in token server. This token ID is saved in the server, but the receiver side it can understand that is particular patient temperature value.
This transmitted patient details are de-tokenized and authorized access the correct IoT data information. This generated token value is only valid at one time, next time the value is re- generated which ensures the data security successfully. The tokenization process effectively works any type of data such as credit card, financial transaction, patient records, customer records, user accounts, bank transmission, agriculture information and etc. Here not only, the tokenization process [25] provides the security to IoT data, the multiple layered encryption techniques also combined with tokenization process to ensure the data security[37]. The detailed working of IoT data security process is depicted in figure 1.
Figure 1:Secure IoT data Transmission Process
The above figure 1 depicted that the secure IoT data processing structure using the tokenized multilayered encryption technology. As discussed earlier, the data is collected fro m IoT device, which is transmitted to the end user using mobile application. The data is shared via mobile application to end user or cloud storage. The data stored in the cloud can be accessed during the
491 research purpose. Before data shared in the cloud, it has been stored in the encrypted format, to maintain the data security. As discussed earlier, initially, tokenization process is applied to perform basic security process. After performing tokenization process, multilayered encryption process is performed in which the data is encrypted from already encrypted message. The process of continuous encryption process is named as cascade encryption, super encipherment encryption. During the encryption process, two cipher text is used for encryption process, in which similar key is used for both cipher text else different key is used for different layer of encryption process[26]. The different type of key utilization creates difficulties to intermediate users. More ever, each layer uses various statistically independent key that also create the more security to transmitted information. Already, the tokenized information is treated as cipher text which is processed by layer of encryption process. During the encryption process in first layer, the specific string S is added in the end of the cipher text which is commonly named as the magic number. According to the string, the system ensures that the incoming data related cipher text need to be decrypted before accessing the data in the second layer. In the first layer, ElGamal algorithm [27] is used for making the encryption process, which is one of the asymmetric encryption algorithms. The algorithm works on the Diffie Hellman key exchange process that successfully provide the security and privacy to transmitted data. The algorithm consists of three phase key generation, encryption and decryption part. The detailed encryption process of tokenized data is done as follows.
Layer 1- Key Generation
The elGamal encryption process [28] works on the cyclic group G, which is multiplicative group of integers and modulo n. In the defined group, the security is provided according to the G problem that is more related to the discrete logarithms. Generate the key in group G of order z with generator g. Then the group G’s unit element is denoted as e. After, defining the group G value, the specific integer a is chosen from the group that is represented as follows,
𝑎 = 1, … . . 𝑧 − 1 (1)
Then the compute the h value as,
ℎ = 𝑔𝑥 (2)
From the computed value, the public key is formed as follows,
𝑝𝑢𝑏𝑙𝑖𝑐 𝑘𝑒𝑦 = 𝐺, 𝑧, 𝑔, ℎ (3)
The generate public key is distributed to others and x is maintains as private or secret key.
After generating the key generation process, the encryption process is performed to improve the security of shared IoT data in distributed environment.
Layer 1- Encryption process
Then the tokenized message (M) need to be encrypted using the shared public key [29]. The message M must be map in the group G using reversible mapping function. From the group random integer y value is chosen that is defined as follows,
𝑦 = 1, … . . 𝑧 − 1 (4) Then the shared secrete value s is computed as follows.
𝑠 = ℎ𝑦 (5)
After that cipher text C1 and C2 is computed for given tokenized message m. The computation is done as follows,
𝐶1 = 𝑔𝑦 (6)
𝐶2 = 𝑚. 𝑠 (7)
Based on the encryption process, the generated cipher text is transmitted to the distributed environment which increase the data security. The person should access the tokenized message M only the person having the shared secret key s because 𝑐2. 𝑚−1 = 𝑠.
According to the process, new y and s value is generated continuously which effectively ensures the security to the transmitted IoT data.
Layer 2: Encryption
Further the security is improved by using second layer of encryption process. The computed cipher text is the plain text to the second layer which is processed by Rjindael encryption process [30]. This encryption process works according to the substitution permutation principle. During the encryption process it uses the fixed block size but different key sizes are used to encrypt the incoming plain text. The key size of the encryption process is changed in every round while generating the cipher text. For example, 10 rounds are used 128 bits key, 12 rounds for 192 bits key and 14 rounds uses 256 bit key. For every round in the encryption algorithm having different processing steps. First step of the work is key expansion, the key value is obtained according to the scheduled key value which is derived from cipher text. After performing the key expansion process, add round key, sub bytes, shift row and mix column process [31] should be performed for getting the cipher text in the second layer. Sub byte step must be performed in two block of information, consider the two block a and b, in which the a value information is transmitted to the b block information which is done by using the 8 bit substitution box. The S-box Chosen process is avoid the fixed guessing of key and easier access of transmitted IoT data. Then the shift row process is performed by shifting the left to right format, then the new shifting value is obtained from the information. Then mix column step is performed in which the a block specific column information is replaced by the b block specific column that is done according to the linear transformation process. Finally, the XOR operation is performed in the Add round key step. In this step, a block information is XOR with the key value and the new value is stored in the block b. This process repeated and get the cipher text from the first layer cipher text perfectly. At last the information is transmitted to the cloud server or end user, which is accessed according to the user needs. During the access process, following decryption process is performed to get the original IoT message.
493 Layer 2: Decryption
When the user want to access the IoT data from the third party environment, they must be authenticate first before accessing the information. The authentication is done by doing the decryption process in which the user only accesses the IoT data when they having the right shared secret key. First the second layer process decryption must be performed in which the shared secrete key block is generated which is performed to get the output of the addroundkey step message. Then the reshifting process is doing and finally, inverse subbyte substitution process is performed to get the second layer input (first layer cipher text). After that, layer 1 decryption process is doing to get the tokenized information.
Layer 1-Decryption
The previous layer 2, generates the C1 and C2 cipher text, which is decrypted with the help of private key x. For getting the plain text, computation is done as follows,
𝑆 = 𝐶1𝑥 (8)
𝐶1 = 𝑔𝑦 (9)
𝐶1 = 𝑔𝑥𝑦 = ℎ (10)
According to the derivation, the generated shared secret key value is same as the encryption process shared value. After that, the inverse of group (𝑠−1)value should be computed. The inverse process is performed using the modular multiplicative inverse process. So, the derivation is done as follows.
𝑠. 𝐶1𝑧−𝑥 = 𝑔𝑥𝑦. 𝑔(𝑧−𝑥)𝑦 = 𝑔𝑧 𝑦 = 𝑒𝑦 = 𝑒 (11) Then the original message is computed as follows.
𝑀 = 𝑐2. 𝑠−1 = 𝑀. 𝑠 . 𝑠−1 = 𝑀. 𝑒 − 𝑀 (12)
This process is repeated until to get the plain text of layer 1. Then the obtained information is further processed by tokenized server, here, the plain text M related tokens are already saved. If the obtained cipher text is right, then the related tokens are provided to the user by performing the de-tokenization process. Thus the introduced tokenized multiple layered encryption process successfully provides the security to IoT data and the excellence of the system is determined using experimental results. Then the detailed efficiency is discussed in section 4.
4. Results and Discussions
In this section discusses about the tokenized multiple layered encryption techniques based IoT data transmission security process. During this process, different IoT based dataset information is used to examine the excellency of the security system. The create system provided enough security against the third-party access, intermediate users, unauthorized access, man in the middle attack problem. The discussed system is developed using the Burp Suite development tool[33] which is one of the security web application testing process. The tool coding is written in Java and developed for web security. Due to the freely available of the development tool, in
this work the created IoT based data transmission process is tested in this environment. Based on the development tool, the system is created using layer of encryption process. Each layer successfully generates the specific private and public key which helps to manage the quality of data effectively. More ever, the layer of encryption process create complexity to intermediate accessor. Suppose, the intermediator accesses the key in one layer, it is difficult to guess in another layer that means tokenized multiple layered encryption technique (TMLE) based IoT data transmission process improves the data quality and enhance the security. Then the developed system efficiency is evaluated using different performance metrics such as encryption time, decryption time, throughput, and accuracy of security.
Encryption Time
This metric is one of the common metrics to evaluate the efficiency of security-based data transmission process. Encryption time is nothing but the entire time to perform to converting the plain text into cipher text. The computed encryption time helps to estimate the throughput of the introduced encryption algorithm. According to the discussion, in this work, the encryption time is computed from the tokenization process to the final layer encryption process. In this work, efficiency of the system is evaluated on three different IoT data. So, the obtained encryption time of different dataset value is depicted in table 1.
Table 1: Encryption Time (Ms)
S.
N O
File size (KB)
AMPDs Mhealth CCAFS
AES PPAP LSF TMLE AES PPAP LSF TMLE AES PPAP LSF TMLE
1 50 22.13 21.45 22.67 20.21 22.34 22.21 21.23 20.18 21.24 21.31 20.1 20.03
2 62 27.45 26.24 27.42 26.14 26.98 27.13 26.28 26.03 27.45 26.98 26.34 26.11
3 98 32.34 29.45 31.48 29.34 29..87 31.54 29.67 29.31 31.56 29.56 29.48 29.14
4 145 36.50 33.65 32.14 30.22 38.56 36.24 32.17 31.23 35.23 32.36 31.67 31.04
5 200 42.45 43.5 42.78 39.87 41.67 43.52 41.78 40.21 42.98 42.45 41.77 39.32
6 326 47.29 46.7 45.2 43.12 47.87 46.23 43.12 42.18 46.38 42.78 42.61 41.24
7 524 53.46 49.97 47.21 41.34 52.23 48.23 46.23 39.17 51.67 49.67 46.145 45.12
8 1245 63.24 61.56 62.19 61.23 62.78 61.67 63.27 59.78 63.23 62.78 61.38 61.21
9 2356 73.28 71.48 70.78 69.86 74.13 73.89 72.19 70.3 69.89 70.67 68.38 68.12
10 5345 78.67 75.56 72.78 70.38 76.27 77.2 71.76 70.1 73.99 76.34 72.44 71.34
From the above table 1 depicted that the encryption time of various encryption algorithm while making the IoT data transmission process on different IoT dataset. During the data transmission process, introduced tokenized multiple layered encryption technique (TMLE) achieves security with minimum encryption time compared to other encryption algorithms such as privacy preserving authentication protocol (PPAP), advanced Standard encryption algorithm (AES) and lightweight security framework (LSF). Among the three methods, introduced TMLE approach
495 have different layer of security attaining process which creates the difficulties while third party user trying to access the information during the IoT data transmission process. The efficiency of the introduced system is worked on three datasets. The obtained results are shown in figure 2.
(a) (b)
(c)
Figure 2: (a) AMPD’S IOT data set Encryption Time, (b) Mhealth -IoT dataset Encryption time and (c) CCAFS IoT dataset Encryption Time
The above figure 2 graphical analysis, clearly depicted that the introduced TMLE encryption algorithm successfully provide the security with minimum encryption time (AMPD’s IoT dataset-43.17ms, Mhealth IoT dataset-42.84ms and CCAFS IoT dataset-43.26ms) compared to other techniques {(AMPD’s IoT dataset-AES47.68ms, PPAP-45.95ms, LSF-45.46ms), (Mhealth
IoT dataset- AES-49.20ms, PPAP-46.78ms, LSF-44.77ms) and (CCAFS IoT dataset-AES- 46.36ms,PPAP-45.49ms, LSF-44.03ms)},on various size of various IoT dataset. The TMLE has low encryption time due to the easiest tokenization process, generation of effective keys in different layer leads to increase the process even though it has multiple layer of security process.
Further, the entire system security is determined by including the decryption time. The introduced TMLE system should consumes minimum decryption time.
Decryption Time
The decryption time also the common security metric which estimate the time taken to converting the generated cipher text into the normal IoT plain text message.The decryption time helps to predict the throughput of the introduced TMLE algorithm. According to the analysis, the decryption process is computed from reverse process of encryption algorithm and the obtained results on various IoT dataset is shown in table 2.
Table 3: Decryption Time (Ms)
S.
N O
File size (KB)
AMPDs Mhealth CCAFS
AES PPAP LSF TML E
AES PPA P
LSF TML E
AES PPA P
LSF TML E 1 50
21.88 21.2 22.42 19.96 22.09 21.96 20.98 19.93 20.99 21.06 19.8
5 19.78 2 62
27.2 25.99 27.17 25.89 26.73 26.88 26.03 25.78 27.2 26.73 26.0
9 25.86 3 98
32.09 29.2 31.23 29.09 29.61 31.29 29.42 29.06 31.31 29.31 29.2
3 28.89 4 145
36.25 33.4 31.89 29.97 38.31 35.99 31.92 30.98 34.98 32.11 31.4
2 30.79 5 200
42.2 43.25 42.53 39.62 41.42 43.27 41.53 39.96 42.73 42.2
41.5
2 39.07 6 326
47.04 46.45 44.95 42.87 47.62 45.98 42.87 41.93 46.13 42.53 42.3
6 40.99 7 524
53.21 49.72 46.96 41.09 51.98 47.98 45.98 38.92 51.42 49.42 45.8
9 44.87 8 1245
62.99 61.31 61.94 60.98 62.53 61.42 63.02 59.53 62.98 62.53 61.1
3 60.96 9 2356
73.03 71.23 70.53 69.61 73.88 73.64 71.94 70.05 69.64 70.42 68.1
3 67.87 10 5345
78.42 75.31 72.53 70.13 76.02 76.95 71.51 69.85 73.74 76.09 72.1
9 71.09
497 From the above table 2 depicted that the decryption time of various encryption algorithm while making the IoT data transmission process on different IoT dataset. During the data transmission process, introduced tokenized multiple layered encryption technique (TMLE) achieves security with minimum decryption time compared to other encryption algorithms such as privacy preserving authentication protocol (PPAP), advanced Standard encryption algorithm (AES) and lightweight security framework (LSF). Among the three methods, introduced TMLE approach have different layer of security attaining process which creates the difficulties while third party user trying to access the information during the IoT data transmission process. The efficiency of the introduced system is worked on three datasets. The obtained results are shown in figure 3.
(a) (b)
(c)
Figure 3: (a) AMPD’S IOT data set Decryption Time, (b) Mhealth -IoT dataset Decryption time and (c) CCAFS IoT dataset Decryption Time
The above figure 3 graphical analysis, clearly depicted that the introduced TMLE encryption algorithm successfully provide the security with minimum decryption time (AMPD’s IoT dataset-42.92ms, Mhealth IoT dataset-42.59ms and CCAFS IoT dataset-43.01ms) compared to other techniques {(AMPD’s IoT dataset-AES47.43ms, PPAP-45.70ms, LSF-45.21ms), (Mhealth IoT dataset- AES-47.01ms, PPAP-46.53ms, LSF-44.52ms) and (CCAFS IoT dataset-AES- 46.11ms,PPAP-45.24ms, LSF-43.78ms)}on various size of various IoT dataset. The effective utilization of shared secret key on layered decryption process and de-tokenization process in token server helps to decrypt with maximum speed and provide the effective results. Further, the excellence of the introduced system security is evaluated using the throughput of the encryption and decryption process.
Throughput
Throughput is nothing but the efficiency of the security system which is computed by the division of average total of plaintext size and encryption time. Then the computed encryption throughput value is shown in table 3. According to the above table 2, the total transmitted plain text value is 10,351. Then the average of encryption time is computed by dividing the total plain text amount by 10 and the get the average value is 1035.1. Then the total encryption time is computed from above table 2, the value is With the help of this, the encryption throughput value is estimate as follows,
𝑇ℎ𝑟𝑜𝑢𝑔ℎ𝑝𝑢𝑡 𝑒𝑛𝑐𝑟𝑦𝑝𝑡𝑖𝑜𝑛 =𝐴𝑣𝑒𝑟𝑎𝑔𝑒 𝑡𝑜𝑡𝑎𝑙 𝑜𝑓 𝑝𝑙𝑎𝑖𝑛 𝑡𝑒𝑥𝑡
𝑡𝑜𝑡𝑎𝑙 𝑜𝑓 𝑒𝑛𝑐𝑟𝑦𝑝𝑡𝑖𝑜𝑛 𝑡𝑖𝑚𝑒 (13)
Likewise, the decryption process throughput value is computed as follows 𝑇ℎ𝑟𝑜𝑢𝑔ℎ𝑝𝑢𝑡 𝑑𝑒𝑐𝑟𝑦𝑝𝑡𝑖𝑜𝑛 =𝐴𝑣𝑒𝑟𝑎𝑔𝑒 𝑡𝑜𝑡𝑎𝑙 𝑜𝑓 𝑝𝑙𝑎𝑖𝑛 𝑡𝑒𝑥𝑡
𝑡𝑜𝑡𝑎𝑙 𝑜𝑓 𝑑𝑒𝑐𝑟𝑦𝑝𝑡𝑖𝑜𝑛 𝑡𝑖𝑚𝑒 (14)
Table 3: Throughput
AMPDs Mhealth CCAFS
AES PPAP LSF TML E
AES PPA P
LSF TML E
AES PPA P
LSF TMLE
Total encrypti
on Time 476.81 459.56 454.65 431.71 442.83 467.86 447.7 428.49 463.62 454.9 440.31 432.67 Throug
hput (Encryp
tion) 2.17 2.25 2.28 2.4 2.34 2.21 2.31 2.42 2.23 2.28 2.35 2.39 Throug
hput of 2.18 2.26 2.29 2.41 2.2 2.22 2.33 2.43 2.24 2.29 2.36 2.41
499 decrypti
on
From the table 3. It clearly depicted that the introduced TMLE approach attains the high throughput value compared to the other encryption algorithm. The method ensures the maximum value due to successful generation of key values and tokenization process. The generated key maintains the sensitive information from the unauthorized person. Then the obtained encryption throughput value on different dataset is shown in figure 4.
Figure 4: Throughput
From the above figure 4, it clearly shows that introduced system ensures high throughput value on both encryption and decryption process in three IoT dataset. The obtained tokenized multiple layered encryption technique (TMLE) is higher than compared to the traditional security algorithms such as privacy preserving authentication protocol (PPAP), advanced Standard encryption algorithm (AES) and lightweight security framework (LSF). In the diagram 4, the shaded and pattern column is represented on the introduced TMLE algorithm throughput value which is maximum compared to other method. The effective throughput value indicates that the system ensures the high security value compared to the other methods.
Accuracy of Security
The most important metric is accuracy, in which the system must ensures the maximum accuracy which means, the introduced system ability to withstand their quality of data, sensitive
information against different attacks. During the analysis process, man in the middle, malware detection and unauthorized access are happened, but the introduced TMLE system ensures the maximum accuracy compared to other method. The different key generation, encryption process improves the overall system accuracy and the obtained result is shown in table 4.
Table 4: Accuracy
S.
N O
File size (KB)
AMPDs Mhealth CCAFS
AES PPAP LSF TML E
AES PPA P
LSF TML E
AES PPA P
LSF TML E 1 50 97.68 97.79 98.34 98.89 97.9 98 98.6 99.1 98.3 98.5 99.1 99.6 2 62 97.89 97.98 98.55 98.91 98.1 98.2 98.8 99.1 98.5 98.7 99.3 99.6 3 98 98.28 98.12 98.43 99.02 98.5 98.4 98.7 99.3 98.9 98.9 99.2 99.8 4 145 98.56 98.43 98.78 98.92 98.8 98.7 99 99.2 99.2 99.2 99.5 99.7 5 200 97.78 97.98 98.3 98.56 98 98.2 98.5 98.8 98.4 98.7 99 99.3 6 326 98.20 98.19 98.34 98.92 98.4 98.4 98.6 99.2 98.8 98.9 99.1 99.7 7 524 98.45 98.62 98.722 99.02 98.7 98.9 99 99.3 99.1 99.4 99.5 99.8 8 1245 99.02 98.98 98.97 99.23 99.3 99.2 99.2 99.5 99.7 99.7 99.7 99.4 9 2356 98.87 98.234 98.63 98.9 99.1 98.5 98.9 99.1 99.5 99 99.4 99.6 10 5345 99.03 98.83 98.91 98.99 99.3 99.1 99.1 99.2 99.7 99.6 99.6 99.7
From the above table 4 depicted that the security accuracy of various encryption algorithm while making the IoT data transmission process on different IoT dataset. During the data transmission process, introduced tokenized multiple layered encryption technique (TMLE) achieves maximum security to transmitted IoT data compared to other encryption algorithms such as privacy preserving authentication protocol (PPAP), advanced Standard encryption algorithm (AES) and lightweight security framework (LSF). The utilized algorithm maintains the security from initial level and layer of encryption and decryption process eliminates the intermediate access successfully. When the new people trying to access the IoT shared data, the security system creates the difficulties of guessing key values and token. So, this process improves the overall system security accuracy. Then the obtained result is shown in figure 5.
501 (a) (b)
(c)
Figure 5: (a) AMPD’S IOT data set Security Accuracy, (b) Mhealth -IoT dataset Security Accuracy and (c) CCAFS IoT dataset Security Accuracy
According to the analysis, the system ensure the maximum security accuracy on different dataset AMPD’s IoT dataset-98.93%, Mhealth IoT dataset-99.18% and CCAFS IoT dataset-99.62%) compared to the other methods such as {(AMPD’s IoT dataset-AES-98.37%, PPAP-98.31%,
LSF-98.59%), (Mhealth IoT dataset- AES-98.61%, PPAP-98.56%, LSF-98.84%) and (CCAFS IoT dataset-AES-99.01%,PPAP-99.06%ms, LSF-99.34%)}. Thus, the introduced system successfully reduces the complexity of IoT data transmission security problem and improve the overall authentication system in distributed environment.
5. Conclusion
Thus, the system introduces the tokenized multiple layered encryption technique (TMLE) for secure IoT data transmission process. During this process different IoT datasets are used to transmit the data from one location to other location. First the transmitted data token value should be identified which is generated with the help of random alphanumeric value. After that, the private key, shared secret key is identified and cipher text is generated for incoming tokenized input. Then the key expansion, subbyte substitution, mix column, addrounded key steps are applied to get the next cipher text which is stored in the cloud environment. When the user wants to access the data, the above process is performed in the reverse manner and the plain text is obtained. The obtained value is then detokenized process is applied to get the original plain text effectively. The efficiency of the system is evaluated using the Burp suite development tool in which the system ensures the 99. 62% of accuracy while sharing IoT data with minimum encryption and decryption time.
6. ACKNOWLEDGMENT
The authors would appreciate UTeM Zamalah Scheme. This research study is supported by Universiti Teknikal Malaysia Melaka (UTeM), to continue second author's study under UTeM Zamalah Scheme.
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