Improved Image Security in Internet of Thing (IOT) Using Multiple Key AES

Encryption of data is translating data to another shape or symbol which enables people only with an access to the secret key or a password that can read it. The data which are encrypted are generally referred to as cipher text, while data which are unencrypted are known plain text. Entropy can be used as a measure which gives the number of bits that are needed for coding the data of an image. As the values of pixel within an image are dispensed through further gray-levels, the entropy increases. The aim of this research is to compare between CAST-128 with proposed adaptive key and RSA encryption methods for video frames to determine the more accurate method with highest entropy. The first method is achieved by applying the "CAST-128" and the second is achieved by applying the "RSA ". CAST-128 utilizes a pair of sub-keys for each round as a quantum of five bits that was utilized as a key of rotation for each round and a quantum of 32 (bits) was utilized as a key of masking into a round . The proposed adaptive 128-bits key can be extracted from the main diagonal of each frame before encryption. RSA is a public-key cryptographic technique which can be known as (asymmetric) cryptography. An asymmetry of a key depends on factoring a product of two big prime values. A comparison was applied on several videos and the results showed that CAST-128 method proved the highest degree of entropy even if the frames have lots of distorted data or unclear image pixels. For example, the entropy value of a sample of a girl video is 2581.921 when using CAST-128, while it is 2271.329 when using the RSA; also the entropy value of a sample of a scooter video is 2569.814 when using the CAST-128, while it is 2282.844 when using RSA.

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“…Entropy can be employed to reflect the cryptographic algorithms' performance 24 . We can calculate entropy using Eq.1 25 .…”

Section: Entropymentioning

confidence: 99%

Comparison between RSA and CAST-128 with Adaptive Key for Video Frames Encryption with Highest Average Entropy

2022

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“…A histogram is indispensable for image normalization. Long bars mean an image has a high frequency of pixels in that value, which gives a sensible variation [20,25]. The histogram normalized, which will increase the area of the pixels and give the best variation of the image.…”

Section: Histogrammentioning

confidence: 99%

“…The histogram normalized, which will increase the area of the pixels and give the best variation of the image. Equation ( 8) defines the balance of a new pixel value when used in this manner [19,24,25].…”

Section: Histogrammentioning

confidence: 99%

“…Let e1, e2,..., em be m possibility items for :probability P (e1), P (e2), ..., P (em). The entropy is given as; 𝐻(𝑒) = − ∑ 𝑚−1 𝑖=0 𝑃(𝑒 𝑖 )𝑙𝑜𝑔 2 𝑃(𝑒 𝑖 ) …………..(9) The neutralization outputs a rating of the area of lower numerical bits in order to encipher a string of bits on the basis of frequency of character [8,24,25].…”

Section: Information Entropy(ie)mentioning

confidence: 99%

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Steganography Encryption Secret Message in Video Raster Using DNA and Chaotic Map

Ali

Mahmoud²,

Jabbar³

2022

Iraqi Journal of Science

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Recently, much secured data has been sent across the internet and networks. Steganography is very important because it conceals secure data in images, texts, audios, protocols, videos, or other mediums. Video steganography is the method of concealing data in frames of video format. A video is a collection of frames or images used for hidden script messages. This paper proposes a technique to encrypt secret messages using DNA and a 3D chaotic map in video frames using the raster method. This technique uses three steps: Firstly, converting video frames into raster to extract features from each frame. Secondly, encryption of secret messages using encoded forms of DNA bases, inverse/inverse complements of DNA, and utilizing 3D chaotic maps, Thirdly, hiding encryption secret messages in that raster video frame by using a secret key in the four corners of each video frame. This technique hides large amounts of secret data because the video frame is large and accepts any message size. The outcomes are efficient, robust, highly secure, and can tolerate high capacity. These outcomes have been obtained from a set of tests like: peak signal to noise ratio (PSNR), mean square error (MSE), entropy, correlation coefficient, and histogram and capacity.

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“…According to earlier studies, video encryption techniques have been increasingly put under studying to enable secure picture transfer in order to safeguard photos from illegal access via communication channels [4][5][6] . Text encryption inside video is a crucial task in the field of information security, as it provides a secure way of transmitting confidential messages 7 . Some of the gaps of the earlier studies involve:…”

Section: Introductionmentioning

confidence: 99%

A Proposed Text Encryption inside Video Using Harris Corner Detection and Salas20 Encryption Algorithm

Fadhil,

Hussien,

Khairi

et al. 2024

Baghdad Sci.J

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Text encryption in video is a vital tool in many industries where protecting sensitive information is of highest concern. Algorithms and automated detection methods commonly struggle to locate hidden text in video frames. This resistance increases the security of the concealed information because it is challenging for uninvited parties to detect the presence of encrypted text. This research suggests a novel method for text encryption inside video utilizing the Salsa20 encryption algorithm and Harris Corner Detection. The goal of this study is to increase the secrecy and security of textual information that is embedded in video content. First step is locateing important corners or spots inside the video frames, the Harris Corner Detection method is first used. These corners act as strong feature points that can be used to incorporate text. Without degrading the video's overall visual quality, the Harris Corner Detection method aids in precisely localizing the places where text may be concealed. Second, the encryption key is generated using the Salsa20 encryption technique. Salsa20 is a popular stream cipher that offers reliable encryption and effective operation. The embedded text is converted into a cipher text by XOR it with the encryption key before embedding it in the video, guaranteeing its confidentiality and protecting it from unauthorized access. Comparing the suggested method to current text encryption methods reveals a number of advantages. The Harris Corner Detection technique integrates text into video frames so that it blends in less noticeably, making it more difficult for adversaries to identify the existence of hidden information. Salsa20's use further guarantees the encrypted text's high level of security and protection, defending it against potential attacks. The proposed system is evaluated using MSE, PSNR, correlation, NPCR, UACI and entropy, these evaluation metrics provide excellent results.

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Improved Image Security in Internet of Thing (IOT) Using Multiple Key AES

Cited by 8 publications

References 12 publications

Comparison between RSA and CAST-128 with Adaptive Key for Video Frames Encryption with Highest Average Entropy

Comparison between RSA and CAST-128 with Adaptive Key for Video Frames Encryption with Highest Average Entropy

Steganography Encryption Secret Message in Video Raster Using DNA and Chaotic Map

A Proposed Text Encryption inside Video Using Harris Corner Detection and Salas20 Encryption Algorithm

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