Medical Image Cryptanalysis using Adaptive, Lightweight Neural Network based Algorithm for IoT based Secured Cloud Storage

Narayana, Mahinsasa; Lakshmi, C.; Sayal, Rishi

doi:10.14569/ijacsa.2022.0130120

Cited by 2 publications

(2 citation statements)

References 14 publications

(18 reference statements)

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“…The sensitive data were secured efficiently using the OHHGA model. In Reference 96, an adaptive IoT‐based Hopfield neural network (AIHNN) model was introduced to improve and estimate a lightweight asymmetric block cipher cryptosystem. AIHNN was suitable for IoT to attain data security while sustaining quality control.…”

Section: Lightweight Homomorphic Cryptographic Algorithmsmentioning

confidence: 99%

Hybrid homomorphic‐asymmetric lightweight cryptosystem for securing smart devices: A review

Mathews,

Jose

2023

Trans Emerging Tel Tech

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The Internet of Things (IoT) has emerged as a new concept in information and communication technology, and its structure depends on smart device communications. It was evolving as a significant factor of the Internet and made the interconnection of huge devices likely, accumulating huge amounts of information through innovative technologies. Thus, the requirement for IoT security is more significant. Scalable services and applications are susceptible to information leakage and attacks, demanding higher privacy and security. Cryptography is a technique to secure data integrity, confidentiality, authentication, and network access control. Owing to several limitations of IoT devices, the classical cryptographic protocols are not appropriate for all IoT smart devices like smart cities, smart homes and so forth. Consequently, researchers have introduced numerous lightweight cryptographic (LWC) protocols and algorithms for IoT security. Numerous solutions are available in the research field regarding security using cryptographic algorithms in IoT environments; however, such solutions have not attained satisfactory outcomes. So, finding a solution by examining the recent issues is open research. This article investigates the various LWC protocols for IoT devices and provides a reasonable enquiry into existing ubiquitous ciphers. Furthermore, the article appraises various recently presented lightweight (LW) block ciphers and hybrid homomorphic LWC regarding security. In addition, this article assists in comprehending the significance of security features and progression in cryptographic algorithms. Finally, the article reports on the necessary changes and recommends upcoming research focuses. Also, this article assists in realizing the importance of security and progressions in cryptographic algorithms.

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Section: Lightweight Homomorphic Cryptographic Algorithmsmentioning

confidence: 99%

Hybrid homomorphic‐asymmetric lightweight cryptosystem for securing smart devices: A review

Mathews,

Jose

2023

Trans Emerging Tel Tech

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“…In order to protect the image from new generations of attacks, encoding solutions must guarantee image confidentiality. Confidentiality can be achieved by encoding the data so that the data becomes unusable and unintelligible, when it is hacked or lost [7][8][9]. Among the available encoding schemes, symmetric encoding is the best cryptographic solution that provides heavy security for huge volumes of data [10].…”

Section: Introductionmentioning

confidence: 99%

Improved Multileader Optimization with Shadow Encryption for Medical Images in IoT Environment

Duhayyim¹,

Maray²,

Qahmash³

et al. 2023

Computers, Materials &Amp; Continua

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Nowadays, security plays an important role in Internet of Things (IoT) environment especially in medical services' domains like disease prediction and medical data storage. In healthcare sector, huge volumes of data are generated on a daily basis, owing to the involvement of advanced health care devices. In general terms, health care images are highly sensitive to alterations due to which any modifications in its content can result in faulty diagnosis. At the same time, it is also significant to maintain the delicate contents of health care images during reconstruction stage. Therefore, an encryption system is required in order to raise the privacy and security of healthcare data by not leaking any sensitive data. The current study introduces Improved Multileader Optimization with Shadow Image Encryption for Medical Image Security (IMLOSIE-MIS) technique for IoT environment. The aim of the proposed IMLOSIE-MIS model is to accomplish security by generating shadows and encrypting them effectively. To do so, the presented IMLOSIE-MIS model initially generates a set of shadows for every input medical image. Besides, shadow image encryption process takes place with the help of Multileader Optimization (MLO) with Homomorphic Encryption (IMLO-HE) technique, where the optimal keys are generated with the help of MLO algorithm. On the receiver side, decryption process is initially carried out and shadow image reconstruction process is conducted. The experimentation analysis was carried out on medical images and the results inferred that the proposed IMLOSIE-MIS model is an excellent performer compared to other models.

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Medical Image Cryptanalysis using Adaptive, Lightweight Neural Network based Algorithm for IoT based Secured Cloud Storage

Cited by 2 publications

References 14 publications

Hybrid homomorphic‐asymmetric lightweight cryptosystem for securing smart devices: A review

Hybrid homomorphic‐asymmetric lightweight cryptosystem for securing smart devices: A review

Improved Multileader Optimization with Shadow Encryption for Medical Images in IoT Environment

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