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This document is the original author manuscript of a paper submitted to an IFIP
conference proceedings or other IFIP publication by Springer Nature. As such, there
may be some differences in the official published version of the paper. Such
differences, if any, are usually due to reformatting during preparation for publication or
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## Ajouter
# Novel Hybrid Technique Enhancing Data Privacy and Security

Mr. Sunil Raj Y, Dr. S. Albert Rabara, Dr. A. Arun Gnanaraj, Dr. S. Brito Ramesh Kumar

Research Scholar, Dept. of Comp. Sci, St. Joseph's College (Autonomous), Affiliated to Bharathidasan University, Trichy - 2, India.

Associate Professor, Dept. of Comp. Sci, St. Joseph's College (Autonomous), Affiliated to Bharathidasan University, Trichy-2, India.

Software Project Manager and Solution Architect, Qanawat L. L. C, Dubai Media City - 502299, Soudi Arabia.

Assistant Professor, Dept. of Comp. Sci, St. Joseph's College (Autonomous), Affiliated to Bharathidasan University, Trichy -2, India.

ysrsjccs@gmail.com, a_rabara@yahoo.com, arun.art06@gmail.com, brittork@gmail.com

**ABSTRACT:** Internet of Things is playing a major role by connecting everything via Internet to the Cloud. Data from things are collected at gateways and processed at the application servers. The processed data is sanitized and masked to preserve it on Cloud. The security and privacy issues such as data misuse, loss or theft make IoT Cloud more untrusted. While providing numerous benefits IoT Cloud help the business organizations grow by limiting the time and economy. Fixing the security and privacy issues would enhance the use of these technologies. This work is aimed at proposing a novel DNA based algorithm to enhance the security and privacy of data on cloud. The detailed study is conducted on the existing security schemes. Finally, clear picture on the pits and holes in existing IoT Cloud based security schemes have been presented. The proposed scheme has been tested by implementing it using opensource tools. Results generated depicts the level of security and privacy provided by the proposed scheme. This would also help researchers to analyse the efficiency of existing hybrid security schemes.

**KEYWORDS:** IoT, ECC DNA, Cloud Computing, TPA, Privacy, Security

## 1. INTRODUCTION

Internet of Things (IoT) connects the devices and sensors over the Internet. Objects with intelligent sensors, and a number of connectivity protocols help connecting things together [1-2]. As the devices are of low capability, the connecting protocols include, CoAP, MQTT, AMQP, and XMPP [3-5]. Data thus transferred by this IoT network, will be converted to HTTP by the gateway. This data finally reaches cloud for processing, analysis or storage.

Cloud Computing (CC) provides services in a distributed fashion despite of the geographical locations. Therefore business/ firms are saving a huge space and large amount of time. Major transactions are done using the protocols such as HTTP, POP, SMTP, FTP and so on. Most services have direct link with IoT's, where they send request using protocols such as CoAP/ MQTT. Working on the request Cloud would respond with its own language (HTTP). In this scenario any point of time eavesdroppers or malicious users may initiate an attack [6].

Availing lot of advantages, greatest problem in cloud is security threats [23-27]. The security and privacy issues that arise as CC leads to lack of manual control and implements virtualization. This may lead to integrity, consistency and privacy issues. The attacks such as spoofing, replace, DOS, eavesdropping and man in the middle attack could expose the data privacy. Privacy of data in IoT Cloud can be achieved by handling privacy at device level, storage level, processing level and transit level [29]. Therefore, proper security mechanism is to be devised to enhance the security by strengthening the authentication and encryption techniques [7].

User authentication combined with audit mechanisms and proper encryption could enhance the security and privacy [29 - 32] to a larger extent. The encryption schemes in Hybrid form perform better. DNA coding-based encryption is performing better with ECC [8-12]. It is revealed that DNA is more efficient and would be predominantly used in IoT Cloud [13]. This strengthens the security using subsequent substitution and ECC does the rest. For enhancing the security but reducing the computing power the DNA encoding mechanism stands first. As the research is on the go DNA may be undertaking every area. This work is intended to have a detailed review on the security mechanisms employed in IoT Cloud and to propose a novel DNA based security mechanism.

The paper is organized as follows: Section (ii) presents the review of literature, Section (iii) presents the proposed algorithm, Section (iv) showing the result and analysis, Section (v) concludes the work.

## 2. REVIEW OF LITERATURE

The review exhibits the recent security techniques that exist to protect the IoT network. As DNA cryptography requires substitutions as Caesar ciphers, they reduce computational complexity and assure security. Here data is transformed to genomic sequence which resembles a DNA strand.
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In [25] a lightweight encryption based on DNA sequence for IoT device's is proposed by the authors. Here authors have used DNA sequence to generate secret key, that is used to encrypt images. Hence mixing it with the classical cryptographic scheme such as symmetric or asymmetric would provide strong security [14-15, 22].

Novel methods have been proposed to enhance security of data, using Huffman with DNA cryptography [4, 16]. The proposal exhibits multiple level of encoding. DNA coding scheme include an advantage of better authentication, storage, and digital signatures. In [9] authors have tried securing the data using digital signatures and DNA cryptography. Here public-key algorithm is implemented in the form of DNA sequencing. In [10] a DNA based method is realized on IoT's. After implementation of proposal efficiency in energy consumption was detected.

[11] Presents DNA and ECC based hybrid scheme. After sequence selection, sorting is applied and then resultant is replaced with DNA codes. Now the data is converted into binary after which they are encrypted using ECC. To provide to IoT environment another approach by [12], uses DNA ECC for reducing the processing time in IoT devices and reducing the size of memory in IoT devices.

In [24] author have designed an algorithm based on composite chaos map for securing image. After XOR operation using composite chaotic map, DNA encoding which results in image being less prone to attacks. [28] have proposed a system to secure the data in transit with integrity and availability mechanisms. To enhance the data confidentiality a DNA cryptography is used along with AES.

The Table 1, accounts few recent proposals ECC and DNA based hybrid algorithm. In [17] authors have found that DNA and ECC make difference in IoT. The framework is employed with double layered security, first is DNA followed by ECC. On combining cryptography with steganography [18] have used SHA512, ECC, DNA and CM-CSA. To hide data behind video, initially the data is compressed using IHE. Multilevel encrypted data is put in pixel points behind frames. The steganographic process is done to enhance security of data.

On suggesting a double level of encryption authors in [19] authors have used two keys for encoding. The first key is generated using ECC, and Gaussian kernel (GKF). The other key being generated based on random injective mapping. In [20] authors have proposed ECC based hybrid technique. This provides solution for secure communication between nodes. Authors have implemented the scheme as two parts, where the first is encrypting the data with play fairs. And the second is hiding the encrypted data behind DNA in a random location using ECC.

In [26] authors have proposed an architecture to improve the level of security in IoT Cloud. They have adopted a hybrid DNA based mechanism with ECC. Also, authors have implemented an audit mechanism to monitor data integrity.

<table><caption>Tabel 2.1. DNA based Hybrid Security – Existing Approaches</caption><thead><tr><td></td><td>Proposal</td><td>Technique</td></tr></thead><tbody><tr><td>[11]</td><td>Framework</td><td>DNA &amp; ECC</td></tr><tr><td>[12]</td><td>Framework</td><td>DNA &amp; ECC</td></tr><tr><td>[17]</td><td>Framework</td><td>ECC, RSA, DNA</td></tr><tr><td>[18]</td><td>Algorithm</td><td>DNA, SHA512-ECC</td></tr><tr><td>[19]</td><td>Algorithm</td><td>DNA, ECC, DES, GKF</td></tr><tr><td>[20]</td><td>Algorithm</td><td>DNA, ECC</td></tr><tr><td>[26]</td><td>Architecture</td><td>DNA, ECC, TPA</td></tr></tbody></table>

Hybrid encryption schemes being the security experts, table 2.1, shows the way algorithms are combined for enhancing the security in IoT Cloud. The attacks that are raised by the anonymous or malicious users are dealt with these schemes. Though the proposals are providing better security, there is no prominent approach to resist data privacy and security attacks on IoT Cloud. Hence the proposed security mechanism.

## 3. PROPOSED WORK

The proposed mechanism enhances the security as it is composed of four components including, DNA Processing Center (DPC), Security Management (SM), Trusted TPA on Cloud (TPAC) and Secure DNA Bank (SDB). The devices such as sensors/ actuators communicate with each other while it is under clouds boundary.
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## 3.1 Functionality of the Proposed Architecture

**User Registration and Authentication.** Registration is the initial level where service user is adopted to the **IoT** Cloud platform through the **DNA Gateway (DG)**. Such users are allowed to use the services. The registration will be done with credentials including Name, DoB, MSISDN, MAC, E-mail and so on. The User ID is provided for authenticating the user later. For any user to access the service, have to be authenticated which largely increase the security and privacy of user data. The authentication is done by sending and validating the OTP.

**Device Registration and Authentication.** Any authenticated user allowed to register their **IoT Device**. The required credentials are IMEI, location, service, name and type. Things Manager (TM) receives the credentials and passes it Things Registry (TR). An key is generated and split into two. First few bits are sent via **DNA Gateway** and the remaining sent to users' mobile. If the authentication is successful, the key is stored. As the TR forwards the device id generated to the certificate registry (CR) it generates a Device Certificate (DC) based on ECDSA. Once the device is registered it is ready for use on successful authentication by the user. The process of device authentication is done by the verification of DC.

**Data on Transit.** After the successful authentication of User at DG and device authentication at TM, on verifying the service certificate the Service Registry (SR) provides the user with the service. The data is encrypted using **ECC DNA** and hash of the data is generated using SHA1. The cipher text and signature merged together is sent to the cloud through the application. The application server after extracting the encrypted text calculates the signature and compares the same with the signature received. This process at the receiving end ensures the privacy and integrity of data. After the user and application specific process the data is again encrypted to be stored at SDB.

**DNA Bank/Data at Rest.** The data from the Data Owner (Do) is allowed to be stored as blocks. These blocks contain encrypted data, signature of data and signature of the next block of data. As the data enters the cloud the Third Party Audit Manager (TPAm) makes an entry on the device and the user involved in the process. TPAm also records the signature. While a request is received from the Data Users ($D_U$), TPAm verifies the access rights and transfers the control to Third party Auditor for user (TPAu). TPAu handles the process of requesting the Do through TPAo. Only after recording the credentials such as signature along with device and user credentials the access is provided.

**TPAC.** Third Party Auditors monitor the access to keep the non-repudiation. The $TPA_u$ hold the user's privileges and other related credentials while monitoring the activities of $D_u$. The $TPA_o$ monitor the activities of Do. Also providers are also included in the process of auditing as they are treated as an user. Thus TPAC by verifying TPAs and CSP's could enhance the privacy and integrity of data on **IoT Cloud** environment.

<figure><img src="image_2.png" /><figcaption>Figure 1. IoT Cloud framework with enhanced Data Privacy and Security</figcaption></figure>
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## 3.2 Encryption Technique

The data is encoded using **DNA** which then transfers it through **DG**. The device authentication is the key to enter the process. After authentication application token is generated. As the authentication becomes successful, the device manager generates a unique session token to handle the user access. The process of encryption is depicted here below and Table 3.1, shows the symbols used and their meanings.

<table><caption>Table 3.1. Symbols used to represent data</caption><thead><tr><td>Symbols</td><td>Meaning</td></tr></thead><tbody><tr><td>ϑ</td><td>Set containing ascii</td></tr><tr><td>ω</td><td>Variable holding a set of binaries</td></tr><tr><td>α</td><td>Set containing set of paired binaries</td></tr><tr><td>gc</td><td>Set containing genomes and associated binary values</td></tr><tr><td>β</td><td>Resultant of first cycle of substitution</td></tr><tr><td>γ</td><td>Set holding the grouped pairs of genomes into 4's</td></tr><tr><td>∞</td><td>Resultant of second cycle of substitution</td></tr><tr><td>ε</td><td>Vectors containing odd elements</td></tr><tr><td>ε'</td><td>Vector holding matrix associated ε</td></tr><tr><td>δ</td><td>Holds even set of data</td></tr><tr><td>δ'</td><td>Used to store matrix representing δ</td></tr></tbody></table>

**Step 1:** Initially ASCII equivalent for the input data is retrieved, as depicted in the equation 1. Here d is the data that is received at the **DPC**, $f_{asc}$ is the function that converts it into ASCII, and $ϑ$ represents the array that is generated.

$$ \vartheta = f_{asc}(d) \qquad (1) $$

### Process of Substitution

According to the ANSI standards every character in a given set is assigned with unique numbers as in the following table 3.2.

<table><caption>Table 3.2. ASCII Value Substitution</caption><thead><tr><td>Characters</td><td>Associated Values</td></tr></thead><tbody><tr><td>0 - 9</td><td>48 - 57</td></tr><tr><td>A - B</td><td>65 - 90</td></tr><tr><td>a - b</td><td>97 - 122</td></tr><tr><td>Symbols and Blank</td><td>Rest of the values</td></tr><tr><td>Space characters</td><td>between 0 and 256</td></tr></tbody></table>

### For example

Let 'DNA', be the input value the resultant value after the process of calculation is 687797 as per the standard. For any integer value between 0 to 9 the ASCII will be between 48 and 57 respectively.

This phase of encoding works at an order of O(n), and at the successful conversion of data $ϑ$ is passed for the further encoding process.

**Step 2:** After the retrieval of ASCII values, the binary equivalent is retrieved as equation 2, shows the conversion of $ϑ$ into binary sequence. The $ω$ hold the binary sequence retrieved by $f_{bin}$ from the ASCII elements in $ϑ$.

$$ \omega = f_{bin}(\vartheta) \qquad (2) $$

### Process of Substitution

The binary equivalent of any integer can be calculated easily by subsequent division of the value by 2.

### For instance,

Assume the number 687797 the ASCII value generated. This is changed into binary:

- Modulo divide the 68 and store the binary value (remainder) in an array

- Divide the number 68 and store the quotient value to the same variable
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- Repeating the process will arrive with a final result, the resultant can be of any size and an eight-bit representation of the given character is 01000100 01001101 00011000.

Higher and random sized binary enhance the security, as it is hard to be guessed. Higher the randomization and bit size also increase the processing time.

**Step 3:** Binary equivalent is in $\omega$, as in the equation 3, the process of encoding starts by grouping input in pairs of two elements. Here $\omega$, presents its contents to the pairing function $f_{par}$ that chops the entire contents into pair of twos.

$$ \alpha = f_{par}(\omega) \qquad (3) $$

The process of conversion is expanded as in equation 4. The sequence of elements represented as, $\omega(i)_j$ to $\omega(n)_m$. Here $i$ represent the starting element in $\omega$ and $n$ represent the last element in the set $\omega$. And $j$ count the bits in two's, and $m$ the last bit. The $f_{par}$ could be expanded as, $\alpha_i=\omega_i + \omega_{i+1}$, which forms a pair iterating till $\omega_n$ the upper limit reaches. The final set $\alpha$, could be written as in equation 4.

$$ \sum_{i=0}^{n} \alpha = \sum_{j=0}^{m} \omega_j \omega_{j+1} \qquad (4) $$

where $i$, the initial value of $\alpha$ and increases until $n$ is reached at $\omega_n$. And $j$ is initialized with 0 stepping higher till $m$, while passing only two binary elements such as $\omega_j$ and $\omega_{j+1}$. The routine takes $O(n*2)$ for the successful partitioning of $\omega$.

**For example,**

If the input value is 01100001, the binary sequence is generated as follows,

<table><tr><td>01</td><td>00</td><td>01</td><td>00</td><td>01</td><td>00</td><td>11</td><td>01</td><td>00</td><td>01</td><td>10</td><td>00</td></tr></table>

**Step 4:** Now binary pairs are encoded using the fixed set, of values as in the following table. The encoding is done based on the set generated. After the verification of pairs, the associated nucleotide is substituted replacing the binary pair. This the coding table is generated as in equation 5.

$$ \sum_{i=0}^{4} gc = \sum_{i=0, j=0}^{1} (i + j) \qquad (5) $$

The generated table is depicted in table 3.3. The set actually contain A, T, C, or G, which actually means adenine, thymine, cytosine and guanine respectively.

<table><caption>Table 3.3. Nucleotide Table for Substitution</caption><thead><tr><td>Code</td><td>Genome</td></tr></thead><tbody><tr><td>00</td><td>A</td></tr><tr><td>01</td><td>T</td></tr><tr><td>10</td><td>C</td></tr><tr><td>11</td><td>G</td></tr></tbody></table>

**Step 5:** The process of substitution $fdse$ is represented in equation 6, where each and every pair of elements is replaced with the genome as in equation 7. The encoded message is at $\beta$,

$$ \beta = fdse(\alpha) \qquad (6) $$

$$ \sum_{i=0}^{n} \alpha = \sum_{i=0}^{m} gc \qquad (7) $$

To understand the process, let us consider the example here,

If the input value is 01100001, the substitution of the genomes would result in the following set of values,

<table><tr><td>T</td><td>A</td><td>T</td><td>A</td><td>T</td><td>A</td><td>G</td><td>T</td><td>A</td><td>T</td><td>C</td><td>A</td></tr></table>

**Step 6:** Next process is to group the genome into pairs of four. This is achieved using the algorithm as represented in equation 8, and the process it does is equated in equation 9.

$$ \gamma = fnuc(\beta) \qquad (8) $$

$$ \sum_{i=0}^{n} \gamma = \sum_{j=0}^{m} \beta_j \beta_{j+1} \beta_{j+2} \beta_{j+3} \qquad (9) $$

For example, let us consider the genomic sequence generated recently,
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For the input TATATAGTATCA, the substitution of the genomes would result in the following set of values,

<table><tr><td>TATA</td><td>TAGT</td><td>ATCA</td></tr></table>

**Step 7:** Generate nucleotide table, for the four-digit genomic sequence. The series is tabulated with an initial value a random number as represented in equation 10.

$$f_{ntbl}(\text{rand}(1, \text{len}(a)), \text{len}(\alpha) + 2) \quad (10)$$

Here to construct nucleotide coded set a random number between 1 and length of the actual data is taken. The set generated by $f_{ntbl}$ is as described in Table 3.4. The order of time taken by $f_{ntbl}$ to complete the process is calculated as O(n * 4).

<table><caption>Table 3.4. Nucleotide generated for the message</caption><thead><tr><th>Text</th><th>DNA</th><th>Text</th><th>DNA</th><th>Text</th><th>DNA</th><th>Text</th><th>DNA</th><th>Text</th><th>DNA</th><th>Text</th><th>DNA</th></tr></thead><tbody><tr><td>101</td><td>ATAA</td><td>109</td><td>AGGA</td><td>115</td><td>CTAA</td><td>123</td><td>ACAA</td><td>131</td><td>GATA</td><td>139</td><td>TAGT</td></tr><tr><td>102</td><td>TCTA</td><td>110</td><td>CAAA</td><td>116</td><td>GCTA</td><td>124</td><td>CTCA</td><td>132</td><td>GTAA</td><td>140</td><td>TACT</td></tr><tr><td>103</td><td>GCGA</td><td>Start</td><td>TTGA</td><td>117</td><td>GTCA</td><td>125</td><td>TGTA</td><td>133</td><td>ATGA</td><td></td><td></td></tr><tr><td>104</td><td>GTGA</td><td>Stop</td><td>TAAA</td><td>118</td><td>CGTA</td><td>126</td><td>GAGA</td><td>134</td><td>AGTA</td><td></td><td></td></tr><tr><td>105</td><td>AGAA</td><td>111</td><td>ACTA</td><td>119</td><td>CTGA</td><td>127</td><td>TATA</td><td>135</td><td>GACA</td><td></td><td></td></tr><tr><td>106</td><td>CGCA</td><td>112</td><td>CATA</td><td>120</td><td>TGCA</td><td>128</td><td>CACA</td><td>136</td><td>GCAA</td><td></td><td></td></tr><tr><td>107</td><td>ATTA</td><td>113</td><td>TCAA</td><td>121</td><td>TCGA</td><td>129</td><td>TGAA</td><td>137</td><td>AGCA</td><td></td><td></td></tr><tr><td>108</td><td>ACCA</td><td>114</td><td>TACA</td><td>122</td><td>ATCA</td><td>130</td><td>TAGA</td><td>138</td><td>ACGA</td><td></td><td></td></tr></tbody></table>

The message encoded using table is more secured, as random number is random. This is because random number depends on the size of the message that changes based on the application.

**Step 8:** The set $\beta$, is grouped in pairs of four by $f_{nuc}$ as in equation 8. This is done by merging the set of elements, as $\gamma_i=\beta_i + \beta_{i+1} + \beta_{i+2} + \beta_{i+3}$, here $\gamma$ is a set containing grouped message. Thus, the data are grouped and are stored in $\gamma$. The message $\gamma$ thus encoded is ready for further encoding with the generated $f_{nuc}$ by the module $f_{enc}$ as in equation 11.

$$\infty = f_{enc}(\gamma, f_{ntbl}(\infty)) \quad (11)$$

For each and every entry of $\gamma$ is replaced with associated index of $f_{nuc}$. This actually generates the set of digits by fully hiding the message. The time taken for this process is in the order of O(n), this actually sustaining the speed of the process. The process is formulated as:

$$\sum_{i=0}^{n} \infty = \sum_{j=0}^{m} f_{ntbl}(j), \quad \text{if } \gamma_j \leftarrow \{\theta\} \quad (12)$$

Where, i representing the index of the resultant message set $\infty$, and j representing index of input set. Here both i and j, starts with 0 and the iteration steps with one till the value reaches m and n. The message is stored in $\infty$ as in equation 12.

Here let us consider the grouped sequence of genomes,

For the input TATA / TAGT / ATCA, the substitution of the cyphertext would result in a set of values as follows,

<table><tr><td>127</td><td>139</td><td>122</td></tr></table>

**Step 9:** As in the equation 13 & 14, $f_{split}$, takes $\infty$ as input and finds the odd numbers which are then stored into $\varepsilon$. The calculation is done with the simple mathematical calculation of modulo division. After modulo division with the digits, data that do not generate a 0 as result is stored at $\varepsilon$. And for each entry of $\varepsilon$, a separate vector $\varepsilon'$ is generated by replace every non zero values with 1's as represented in equation 13.

$$\varepsilon = f_{split}(\infty) \quad (13)$$

$$\delta = f_{split}(\infty) \quad (14)$$

Thus, $f_{split}$ could separate every odd value in the message. In equation 12 input calculated for separating the even numbers. The $f_{split}$, takes $\infty$ as input and finds the even numbers which are then
stored into $\delta$ by applying modulo division. The numbers that generate 0 is stored in $\delta$. Parallely each entry in $\epsilon$, a separate vector $\delta'$ is generated by replace every non zero values with 1's as in equation 14. Thus, $f_{split}$ separate every odd value in message.

$$ \epsilon' = f_{split}(\epsilon) \qquad (15) $$

$$ \delta' = f_{split}(\delta) \qquad (16) $$

After splitting the converted message in to two set of integers and matrix representation is generated, as in equation 15 and 16, $f_{mdd}$ takes odd set $\epsilon$, even set $\delta$. The resultant denoted by $\mu$, hold the message ready for undergoing the final phase of encoding process by ECC. Data Retrieval Matrix looks as in the following example:

<table><caption>Example - Data Retrieval Matrix</caption><tr><td>127</td><td>139</td><td></td><td></td><td>1</td><td>1</td><td></td><td>0</td><td>0</td></tr><tr><td></td><td></td><td>122</td><td></td><td>0</td><td>0</td><td></td><td>1</td><td>0</td></tr><tr><td>V</td><td>2</td><td></td><td>V</td><td>1</td><td></td><td></td><td></td><td></td></tr></table>

**Step 10:** Now the hash for the both the odd ($\epsilon$) and even ($\delta$) set is calculated using SHA512 as represented in equation 17 and 18. The DRM is stored with the generated hash as the reference. This DRM set is stored in gateway for the use during decryption.

$$ dh_1 = f_{sha}(\epsilon) \qquad (17) $$

$$ dh_2 = f_{sha}(\delta) \qquad (18) $$

**Step 11:** Before encryption, the process of key generation is done by $f_h$. The curve generated based on the curve equation 19, contains y, x, ax and b, of which (x, y) represent a point on the curve.

$$ y_2 = x_3 + ax + b \qquad (19) $$

The domain parameters of curve are a, b, h, p, N, G, and r. Here 'p' representing prime number, 'a' and 'b' representing coefficients. The 'G' represents point, 'N' represents prime factor, 'h' represent the cofactor and 'r' representing random integer that is less than 'N'. Since NIST specifies the 'p' to be greater than $2^{160}$, the equation 19 is rewritten as in equation 20, by assuming.

$$ y_2 = x_3 + ax + b \mod p \quad (p>2 \ 160) \qquad (20) $$

To encrypt any given input, sender choses a random number 'r'. Using this 'r', point is calculated towards encrypting the text with the receiver's Public Key (Pu).

$$ C = [(r.G), (M+r. Pu)] $$

Example for the key generation is depicted, by assuming the plain text as "W" which is represented by a value 4,433.

$$ y_2 = x_3 - ax + b \pmod{997}, a = (-3), b=3 $$

$$ y_2 = (-3)^3 + 1 \pmod{997} $$

$$ G = 17,427 $$

$$ Pr = 11 $$

$$ Pu = 37, 620 $$

$$ r = \text{Random Number} = 7 $$

**Step 12:** The final phase of encryption is done by passing the data $\mu_1$ and $\mu_1$ to the $f_{ecc}$ along with the $pu$ is depicted in equation 21 and 22 subsequently. After data is DNA encoded and encryption process is over signature (dnaSig) is recorded. After the completion of process of encryption of $f_{ecc}$, the data is sent to the cloud for storage.

$$ d_1' = f_{ecc}(\mu, pu) \qquad (21) $$

$$ d_2' = f_{ecc}(\mu, pu) \qquad (22) $$

After the successful encoding, the data is again passed through another set of encoding process where a random salt (Es) is used to generate the code as the user request to store the data. This salt is named here as encryption salt (Es), which will be used to construct a sequential array of numbers
associated to the DNA codes generated in the previous cycle. The partitioned data will be separated as odd and even set, where the odd set of data will have its associated matrix generated and even set of data will have its own set of matrices generated. After the signature is calculated using SHA 512, the cipher text will be grouped in to two portions and two set of matrices are generated to handle both the portions of data separately.

DNA data is converted into the digital form which is partitioned into two groups $data_{si}$ and $data_{sj}$. The encrypted data along with the necessary credentials such as unique signature reach the cloud storage after the validation of TPAo. The cloud storage gateway after verifying the data with the received signature (dnaSig), allocates the buckets for the data after processing. Thus, communication between IoT and cloud application are encrypted in a much-secured manner.

### 3.3 Secure Data Decryption

The request from the device at the IoT Environment is taken to cloud along with device certificate. The CR validates the certificate by extracting the device information, based on the credentials stored in the certificate registry. The firewall after making the entry on its device log, directs the request to the TPAu, while TPAo after making the entry on the log including the device credentials of the client and user credentials, sends the request to the Do. Do may provide the Access Token (Acct). Now the Acct is transferred to Du through TPAu, for authorizing the requestor. After making the entry on the TPAr, TPAu verify the signature in the register with the signature of the data on the storage. After verifying the signature, the data will be transferred from the storage.

To decrypt of the data is done by the receiver, as it multiplies the first point of the ciphertext pair (r.G) with the private key (Pr). Now this result is added to the second point of the ciphertext pair.

$$M = (M + r.Pu) - (Pr (r.G)) = (M + r. Pr G) - (Pr (r.G))$$

After authentication of application token, session token and user credentials the encrypted data is decrypted and send to the client through the firewall reaching the DNA Gateway. As the gateway receives the data after verifying the dnaSig, it first merges the DNA matrix $data_{si}$ and $data_{sj}$, together $data_m$ with the help of matrix created. Once identifying the code pattern generated for the data with the help of application id and the session id stored, it multiplies the even numbered DNA matrix with the n that is randomly chosen, where n > 1 < 10. Then it merges the DNA matrix together so that the actual DNA message.

The DNA data that is received would never require further processing but decoding based on the standard table that was generated for an application.

$$ \begin{aligned} \text{code}_{si} & \Rightarrow \text{data}_{si} \& \text{code}_{sj} \Rightarrow \text{data}_{sj} & 18 \\ \text{data}_{m} & = \text{data}_{si} + \text{data}_{sj} & 19 \end{aligned} $$

The next level of decryption involves merging the data together that can be decoded using that generated table. The DNA data thus calculated is combined to form a string altogether, from where the further process of decryption could proceed decoding the DNA's. As the DNA's are calculated using the generated application specific nucleotide code, final phase of decryption is done. After actual data is decoded out, the dSig is compared with calculated signature of data that is retrieved.

If verification successful the data is sent to client, or an error token eT is generated. The eT intimates the replace attack to TPAo, who further will keep DOw informed.

## 4. RESULT AND ANALYSIS

The implementation is done using opensource tools such as PHP and MYSQL. The interface is designed using HTML5 and CSS3. The cloud sim is used to evaluate the performance of the proposed framework.

### 4.1 Analysis on ECC DNA

The implementation of the work algorithm is done and results are generated. The input and the output, of the system is recorded to analyse the performance. The sample of the results generated by the proposed algorithm is present here in Figure 7.
<figure><img src="image_3.png" /><figcaption>Figure 7. Sample Input and Output – Proposed ECC DNA</figcaption></figure>

The figure 7a, shows the inputs text of size 16 characters, figure 7b, displays the binary sequence of every character. On subsequent conversion the binary is converted into nucleotides as in figure 7c. Finally, the figure 7d, shows the final cypher text ready for transmission. The analysis on the proposed DNA algorithm is presented here by sampling the data. The efficiency of the algorithm on the basis of time taken is analysed as in Table 4.1.

<table><caption>Table 4.1. Analysis on Encryption of Data- Sample 1</caption><thead><tr><td>Test</td><td>Plain Text</td><td>Cipher Text</td><td>Key Size</td><td>Time (MS)</td></tr></thead><tbody><tr><td>Test 1</td><td>10</td><td>80</td><td>1024</td><td>0.07</td></tr><tr><td>Test 2</td><td>20</td><td>160</td><td>1024</td><td>0.12</td></tr><tr><td>Test 3</td><td>50</td><td>400</td><td>1024</td><td>0.17</td></tr><tr><td>Test 4</td><td>120</td><td>960</td><td>1024</td><td>0.23</td></tr><tr><td>Test 5</td><td>240</td><td>1920</td><td>1024</td><td>0.32</td></tr></tbody></table>

The key size chosen is 1024 bits and at various input sizes the time taken is analysed. At a maximum of 240 characters of data is encrypted in 0.32 ms. The resultant cyphertext is of size 1920 bits.

<table><caption>Table 4.2. Analysis on Encryption of Data - Sample 2</caption><thead><tr><td>Test</td><td>Plain Text</td><td>Cipher Text</td><td>Key Size</td><td>Time (MS)</td></tr></thead><tbody><tr><td>Test 6</td><td>10</td><td>80</td><td>2048</td><td>0.08</td></tr><tr><td>Test 7</td><td>20</td><td>160</td><td>2048</td><td>0.12</td></tr><tr><td>Test 8</td><td>50</td><td>400</td><td>2048</td><td>0.20</td></tr><tr><td>Test 9</td><td>120</td><td>960</td><td>2048</td><td>0.24</td></tr><tr><td>Test 10</td><td>240</td><td>1920</td><td>2048</td><td>0.33</td></tr></tbody></table>

The process of decryption is done after the implementation of the algorithm. The sample data set for analysis of the results generated is presented here in table 4.2. The time taken for encryption is analyzed and is summarized as follows:
<figure><img src="image_4.png" /><figcaption>Figure 8. Time taken by the ECC DNA for Encryption</figcaption></figure>

The figure 8, describes the time taken by the encryption algorithm for encrypting the plain text. Test conducted is based on two key patterns, first is with 1024 bit key and next is using 2048 bit key. As per the results generated by the system the average time taken for encrypting 10 byte of data is 7.5 ms. The maximum size reported for this work is 240 byte, for which an average time of 32.5 ms is recorded. Therefore, the ECCDNA proves better for encryption.

<table><caption>Table 4.3. Analysis on Decryption of Data - Sample 1</caption><thead><tr><td>Test</td><td>Cipher Text</td><td>Plain Text</td><td>Time (MS)</td></tr></thead><tbody><tr><td>Test 1</td><td>80</td><td>10</td><td>0.08</td></tr><tr><td>Test 2</td><td>160</td><td>20</td><td>0.14</td></tr><tr><td>Test 3</td><td>400</td><td>50</td><td>0.16</td></tr><tr><td>Test 4</td><td>960</td><td>120</td><td>0.26</td></tr><tr><td>Test 5</td><td>1920</td><td>240</td><td>0.31</td></tr></tbody></table>

The implementation is tested to verify its efficiency during data decryption and results generated are sampled as in Table 4.3. Algorithm performed the decryption process in an efficient manner. The variable length data is used as input to check the efficiency. The minimum size of data is performed at an average of 9ms and the data with about 1920 bytes is performed at an average of 35ms.

<table><caption>Table 4.4. Analysis on Decryption of Data - Sample 2</caption><thead><tr><td>Test</td><td>Cipher Text</td><td>Plain Text</td><td>Time (MS)</td></tr></thead><tbody><tr><td>Test 6</td><td>80</td><td>10</td><td>0.09</td></tr><tr><td>Test 7</td><td>160</td><td>20</td><td>0.13</td></tr><tr><td>Test 8</td><td>400</td><td>50</td><td>0.18</td></tr><tr><td>Test 9</td><td>960</td><td>120</td><td>0.23</td></tr><tr><td>Test 10</td><td>1920</td><td>240</td><td>0.35</td></tr></tbody></table>

The efficiency of data decryption process is described in Table 4.4, which shows a consistency in the time taken for decryption while compared with the previous set of data. As per the results, it is sure that the encryption algorithm is efficient and faster enough to work with any set of data with a higher size of key.
<figure><img src="image_5.png" /><figcaption>Figure 9. Time taken by the ECC DNA for Decryption</figcaption></figure>

The figure 9, describes the time taken by the encryption algorithm for encrypting the plain text. As per the results generated by the system the average time taken for decryption for 80 byte encrypted input data is 8.5 ms. The time taken is to decrypt the data of size 1920 bytes, for which an average time taken is recorded as 33 ms.

The proposed work while compared with the existing approaches found to have better performance. The approach included RC4 along with DNA. The comparison is presented here below in table 4.5.

<table><caption>Table 4.5. Comparison with Existing Proposals</caption><thead><tr><th></th><th>RC4</th><th>RC4 - DNA</th><th>Proposed ECC - DNA</th></tr></thead><tbody><tr><td>Plain Text (bytes)</td><td>128</td><td>128</td><td>120</td></tr><tr><td>Key Size (bytes)</td><td>256</td><td>256</td><td>1024</td></tr><tr><td>Encryption Time (ms)</td><td>0.414</td><td>0.584</td><td>0.23</td></tr><tr><td>Plain Text (bytes)</td><td>256</td><td>256</td><td>240</td></tr><tr><td>Key Size (bytes)</td><td>256</td><td>256</td><td>2048</td></tr><tr><td>Encryption Time (ms)</td><td>0.576</td><td>0.69</td><td>0.33</td></tr></tbody></table>

The results depict the efficiency of the proposed algorithm as the key size increases the time taken for encryption also increases. Among the present scenario, such situation the proposed **ECC DNA** after testing with higher key sizes 1024 and 2048 could perform better up to 0.023 ms and 0.033 ms respectively. Therefore, the proposed **ECC DNA** proves performing better at encryption.

## 4.2 Analysis of Proposed Framework

Test is conducted using an opensource tool Cloud Analyst. The load test, response time and throughput were recorded. Series of requests were generated to test performance of the system as in Figure 9. It shows that the system could accept multiple request if the system is implemented.

<figure><img src="image_6.png" /><figcaption>Figure 9. Analysis of the Parrel Requests</figcaption></figure>

As any request to have a task done response time of the system is recorded and found to be reasonable as in Figure 10. After the series of requests are received, the calculation is done with the input and the response is sent back. The minimum time taken to respond is 6.8 ms and a maximum of 16.5 ms.
<figure><img src="image_7.png" /><figcaption>Figure 10. Analysis on the Response Time of the System</figcaption></figure>

During the communication, network show up throughput as the request and response are higher. On the analysis of throughput is depicted as in Figure 11. It also depends on the type of network used, here the throughput recorded is between 2.2 ms to 4.4 ms on an average.

<figure><img src="image_8.png" /><figcaption>Figure 11. Analysis of Throughput of the System</figcaption></figure>

As per the study it is found that performance is also affected depending on medium that is used and the other aspects of devices being employed. The proposed mechanism performs better on analysing the aspects such as request, response and throughput.

## 5. CONCLUSION

The analysis reflects the efficiency of the security techniques as the privacy attacks such as data leakage is mitigated. As described in [4, 8-12] that **DNA** based security algorithms with **ECC** provide better security at **IoT** level. Hybrid algorithms proposed could encrypt the data as fast as 0.033 ms as the size of key is 2048. The decryption time stands equally faster up to 0.035 ms. Data privacy and integrity stands high as security is strong. **DNA** is efficient in such a way that it could enhance the security and privacy as it is prominent at data hiding and the proposed architecture enhance the privacy and security by enforcing authentication and repudiation using TPAC. As per the results generated, it is clear that using Hybrid encryption could enhance the security in **IoT** Cloud.

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