An Investigation into the Usage of Bounding Boxes in Discriminating

Image Encryption Algorithms

Geetanjli Khambra, Vijay Panse and Shilpa Jackson

Department of Computer Applications, The Bhopal School of Social Sciences, Bhopal, India

Keywords: Bounded Box, Image Encryption, Decryption, Correlation.

Abstract: When it comes to protecting people's privacy and maintaining secrecy, encrypting photographs is the safest

and most effective method. However, the computational expense and treating time required to conduct

complete image encryption prove to be preventive constraints that preclude it from presence employed more

intensively in real time. This is because of the large size and complicated nature of digital images. In order to

solve this issue, many recent studies have turned to selective encryption, a way of encrypting only the most

salient features of an image in an effort to lessen the encryption burden. As a possible contribution, we offer

a selective picture encryption method that uses bounded boxes. The computational repercussions of selective

image encryption have been the subject of experimental studies. It has been determined through testing that

the selective encryption technique is significantly faster than other methods of encryption. Selective

encryption has these features; hence it can be looked at as a viable option. Therefore, this contribution

improves security to an acceptable level during implementation. Experiments with the same have shown

promising results in protecting real-time photos.

1 INTRODUCTION

The best way to ensure privacy and maintain

confidentiality with photographs is to encrypt them.

However, the calculation expense and treating time

required to conduct complete image encryption prove

to be preventive constraints that preclude it from

presence employed more intensively in real time

(Dworak et al., 2016). This is because of the large size

and complicated nature of digital images. In order to

solve this issue, many recent studies have turned to

selective encryption, a way of encrypting only the

most salient features of an image in an effort to lessen

the encryption burden. However, a fair comparison of

its performance to full encryption is needed

(Enayatifara et al., 2017; Yavuz and Yazici, 2016;

Faragallah, 2013).

The most widely used framework for encrypting

images in a chaotic environment is based on a special

set of rules for selective picture encryption (Fister and

Tepeh (2016). The effect of a single pixel can be

correctly diffused to the whole cipher-photo with

numerous conventional rounds of encryption using

the substitution method, in which the pixel values are

modified sequentially, with the alteration completed

to a precise pixel usually depending on the collected

impact of all the preceding pixel values (Wang et al.,

2016; Gu and Ling, 2014; Chen et al., 2017; Chen et

al. 2015). To generate a pseudorandom key stream for

replacement, one can use a logistic map, tent map, or

Lorenz machine, to name just a few of the many

discrete and continuous chaotic structures available

(Shi et al. 2016). The secret password is featured in

the hired chaotic systems' starting parameters and

conditions.

The phases of permutation and substitution are

typically considered neutral. Because the permutation

method best reshuffles the pixel placements while

without pixel price, it is vulnerable in the course of

some of the commonplace attacks, specifically

statistical assaults and seemed/chosen simple text

attacks (Jolfaei and Mirghdri, 2011; Lang, 2015;

Wang et al. 2015; Li, 2016). Pixel charge permutation

and substitution (PS/2) plain-photo Cipher-photo

iterations rounds Using the Permutation Key Chaos-

based image cipher substitution key common form.

The replacement method is secure, but it is

computationally intensive. The permutation method

is much simpler (Su and Gao, 2013).

This is owing to the fact that computations are

carried out over the field of actual numbers, and a

fantastic widespread variety of iterations of a chaotic

Khambra, G., Panse, V. and Jackson, S.

An Investigation into the Usage of Bounding Boxes in Discriminating Image Encryption Algorithms.

DOI: 10.5220/0012491600003739

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 1st International Conference on Artiﬁcial Intelligence for Internet of Things: Accelerating Innovation in Industry and Consumer Electronics (AI4IoT 2023), pages 397-402

ISBN: 978-989-758-661-3

Proceedings Copyright © 2024 by SCITEPRESS – Science and Technology Publications, Lda.

397

map is required for the vital thing movement creation

technique (Sui and Lu, 2014). The computational

precision cannot be a factor in a key sensitivity

analysis of a crypto-instrument. This work introduces

a hybrid model based replacement technique to

enhance the performance of the chaos-based selective

picture cryptosystem (Sui et al., 2015).

The advantages of the digital revolution haven't

been realized without costs, such as restrictions on

copying and sharing digital multimedia system

papers. In order to rise to this challenge, academics

have been working tirelessly to develop novel and

cost-effective document protection strategies for use

in multimedia system documentation. In this setting,

new methods such as coded writing and digital

watermarking are introduced (Wang et al., 2015) .

Another method of protecting the ownership and

authenticity of digital multimedia system material

consists of adding digital watermarks to relevant

documents. As the Internet expands and transmission

technology becomes more commonplace, people will

find it easier than ever to share digital transmission

data like digital images with one another online

(Wangm and Zhang, 2016).

The purpose of this study is to develop a more

secure image encryption technique based on dispersal

and misperception. Image encryption utilizing the

diffusion and confusion techniques, image encryption

using genetic operators, and selective image

encryption using chaos on a Windows machine are all

within the scope of this article.

2 EXISTING WORK DONE

By combining a logistic map with a cellular

automaton, the authors have provided a method for

computing picture encryption. The plan combines

two different types of randomizations, permutation

and diffusion (Liu and Sun, 2016). The pixels are

shuffled using a permutation technique, and then the

dispersion system amplifies the effects of even a

single pixel's alteration throughout the entire image.

The calculation is based on a muddled system, so

even a minor shift in the significant will harvest

drastically different results. The suggested

framework's key feature is its ability to limit attacks

using animal power and to function in noiseless

transmission. The article also suggests that the

framework has strong security based on the results of

key sensitivity analysis, histogram analysis,

differential attack, and other testing (Wu et al., 2015).

This academic study details a quick method of

image encryption. Here, a 2D Sine IMIC Modulation

map is used, and its unstructured capabilities are

analysed using a stage chart, a Lyapunov type range,

and a many-sided quality. At the foundational stage

of encryption, the confusion and dissemination

method are consolidated. The pixels in the image can

be jumbled up very efficiently using a technique

called Chaotic Shift Transform (CST). In addition, a

method of line and segment replacement is used to

reorder the pixels in the image. The scrambling effect

and low-time many-sided quality of CST are

superior. In this instance, we employ the utilization

of several different keys. A 256-bit secret key is

sufficient to withstand a brute-force attack (Zhang et

al. 2013).

Researchers presented an encryption scheme

based on connecting various chaotic maps to provide

secure transmission of therapeutic images. Logistic,

tent, and sine maps are all incorporated into the

suggested procedure. In this method, DICOM picture

pixels are muddled and spread out (Zhang et al.

2012). The manufactured chaos-cryptic arrangement

is submitted to a number of security investigations,

including measurable, differential, key space, key

affectability, deliberate scrambling assault, and select

plaintext attack tests, to validate the severity of the

proposed approach. Measurement analysis,

connection analysis, differential analysis, key space

analysis, key affectability analysis, deliberate

trimming attack analysis, and picked plaintext attack

analysis are just some of the systems used in this

paper to analyse and approve the security and

unpredictability of the proposed plan (Zhang et al.

2014).

In order to optimize for the monarch butterfly, the

authors advocated a greedy approach combined with

a self-adaptive crossover operator (GCMBO).

Movement Administrator and Butterfly Changing

Administrator are combined into one eager system in

GCMBO. Better performance is possible in the future

if more benchmark issues are used, especially real-

world applications (Liu and Li, 2013). Using LTSVR

(Lagrangian twin support vector relapse) and HC

(hereditary calculation) in DCT (discrete Cosine

transform) space, researchers offer a safe and robust

grey scale picture watermarking scheme (Hua and

Zhou, 2016). The key components into which the

watermark will be embedded are determined using

fuzzy entropy. The inability to withstand rotational

and translational attacks is a major shortcoming.

Under the available computational asset, authors

offer an autonomous multi-objective advancement

model that can account for security and quality of

service (Wang et al., 2019).

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3 THE PROPOSED WORK

This work introduces a hybrid model based

replacement technique to enhance the performance of

the chaos-based selective picture cryptosystem. The

following details the suggested architecture for a

replacement method for selective picture encryption

with a key generated via chaos-based key generation.

1.1. The face detector is used to identify the

one-of-a-kind photo. The resulting binary image

will be the same size as the original photograph

but will only include the numbers 1 and 0. A value

of one indicates that the area is in the same

location as the corresponding pixel in the original

image, whereas a value of zero indicates that there

is no area there.

1.2. The original imagery is converted to a

series of zeros and ones, known as binary. The

special photographic archive will be discarded.

Subtracting anything from the past (foreground

detection) is another name for this technique.

1.3. The goal of selective encryption is to

reduce the number of photos that need to be

encrypted without compromising security.

Selective encryption methods require the original

image to be chosen.

1.4. To substitute means to change the location

of a pixel in a picture from one location to another.

In this process, the partial encrypted image is

encrypted using a substitution method based on

Hybrid T models.

Algorithm for the proposed method is as follows:

1. Twitch with your original coloured

medicinal image.

2. Grayscale and binary formats can be

created from the provided image.

3. The multi-chaotic key is used for selective

encryption, which results in the scrambled

images.

4. Images with selective encryption using the

S-Box produce encrypted versions of themselves.

The Inverse hybrid substitution method, which

makes use of both key stream and Inverse image

conversion techniques, is the foundation of secure

and selective Chaos-based image encryption (SSIE).

Figure 2 displays a square chart of the suggested

unscrambling algorithm.

Combining key stream and Inverse image

conversion methods, a decrypted picture can be

derived from the encrypted image using the Inverse

hybrid substitution process.

Figure 1: The Proposed Block Diagram.

New

Image

Image

Alteration

Elimination of

background

area

Choice the

image

encryption area

Encryption

system

Fusion

Replacement

Arrangement

Ultimate

Encrypted

2D –LS collective

key stream

An Investigation into the Usage of Bounding Boxes in Discriminating Image Encryption Algorithms

399

Figure 2: Square Chart of SSIE Decryption Process.

4 RESULT ANALYSIS AND

DISCUSSION

This experiment is performed using MATLAB

R2010a, with key generation based on randomness.

Here, authors have discussed about the connection

coefficients, key space inquiry, key affectability

research, and differential investigation that were run

on the proposed plot.

1.5. Association analysis: The first image's

neighbouring pixels are very closely related along

the horizontal, vertical, and oblique axes. Pixels

in the encrypted image should have relationship

coefficients that are sufficiently small to

withstand quantifiable attacks if the encryption

computation was performed correctly.

(1)

A random comparison of 2000 pairs of nearby

pixels in each direction is made with the encoded

equivalents of the images. This is done so that the

associations between close pixels in the plain and

figure images can be analysed and thought about.

Figure 3 presents the correlation coefficient for both

the unencrypted and encrypted versions of the image.

Images that have been encrypted have a more

consistent grayscale than their plain counterparts.

Figure 3: Association of Input Images and the analogous

Ciphered Images.

1.6. Information Entropy Analysis: In order to

objectively assess risks, one can use data entropy.

The information entropy of a figure picture is

calculated in order to evaluate his eccentric

behaviour. The maximum entropy for a grayscale

image is log (28) = 8 and will be attained if the

pixels appear with equal probability, as there are

28 possible grayscale quality.

1.7. We use two quantitative metrics—the

Number of Pixel Change Rate and the United

Average Changing Intensity—to examine the

effect of a single pixel change in the plain-image

on the cipher-image, ensuring the proposed

encryption system is resistant to differential

attack.

(2)

Any modification to the plaintext picture must

result in a corresponding modification to the cipher

text image. The average pixel-wise intensity

difference between the two images can be determined

with the aid of UACI. Images 'C1' and 'C2' are of the

same size.

(3)

Table 1: Different evaluation parameter comparison.

S.

No.

data

Evaluation parameters

Entropy

NPCR

UACI

1

Lungs

7.97

99.76

33.34

2

Eye

7.96

99.45

33.57

3

Heart

7.95

99.32

33.61

4

Bone

7.96

99.84

33.71

Collective

Key stream

Encrypted

image

Inverse

Fusion

Replaceme

nt system

Inverse

Image

transforma

tion

Decrypted

Image

AI4IoT 2023 - First International Conference on Artiﬁcial Intelligence for Internet of things (AI4IOT): Accelerating Innovation in Industry

and Consumer Electronics

400

The entropy of several example photos is

displayed in Figure 4. The ability of the suggested

cryptosystem to withstand entropy attacks has been

widely established. The lungs are the most entropic

organ in the body. This can be checked by comparing

the cypher images derived from a standard photo to

one derived from a picture with a single altered pixel.

Adjusted pixel count is the foundation of NPCR. The

NPCR value of several test photos is displayed in

Figure 4. Here, the NPCR and UACI values in bone

are the highest.

Figure 4: Different evaluation parameter comparison.

5 CONCLUSION

Substitution systems were used in the selective image

encryption. The majority of critiques in this field rely

on confusing pixel-based substitution schemes and

other forms of random substitution. While effective,

such encryption methods are unlikely to provide as

much protection as do conventional numbers, which

are less vulnerable to attacks. Therefore, specific

encryption of restorative images based on

substitution computation is a better trade-off between

security and efficiency.

This work presents a hybrid confusion-based

strategy for selective picture encryption that makes

use of bounded boxes. There was a significant

decrease in required processing time and a noticeable

improvement in security. The proposed approach

promises a universally applicable selective

encryption algorithm that may be implemented across

a wide variety of computer distributed systems for

safe, scalable cloud data storage.

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