An analysis and a comparative study of cryptographic algorithms used on the Internet of Things (IoT) based on avalanche effect

Muthavhine, Khumbelo Difference; Sumbwanyambe, Mbuyu

doi:10.1109/icoiact.2018.8350759

Cited by 23 publications

(34 citation statements)

References 33 publications

(99 reference statements)

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“…Muthavhine and Sumbwanyambe [21] indicated that IoT devices were substantially tiny in size and memory allocation. Algorithms like AES were generically rejected due to memory constraints required before installation.…”

Section: Related Worǩmentioning

confidence: 99%

“…Security and memory are the main concerns on IoT devices [1] - [7], [21]. The security of information, data, and network should be equipped with a strong cryptographic algorithm like Advanced Encryption Standard (AES) on each IoT devices to achieve identification of users, the confidentiality of data, integrity (correctness) of exact information, and deniability of unauthorized users including connection of unwanted devices [6].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Converting AES Algorithm to be LWCAES using LCPoAES for Ease Installation on IoT Devices

Muthavhine¹

2021

Preprint

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Section: Related Worǩmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Converting AES Algorithm to be LWCAES using LCPoAES for Ease Installation on IoT Devices

Muthavhine¹

2021

Preprint

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“…Penelitian ini menggunakan Avalanche Effect sebagai alat ukur untuk mengevaluasi model super enkripsi yang diusulkan. Pengukuran dalam avalanche effect dilakukan dengan melihat setiap perubahan bit yang terjadi dalam data tersandi yang diakibatkan oleh perubahan yang dilakukan terhadap data awal maupun kunci, dalam avalanche effect semakin banyak perubahan bit maka semakin baik model tersebut [15]- [17]. Proses yang terdapat dalam avalanche effect dapat dilihat pada Persamaan (3).…”

Section: Pengujian Model Kriptografiunclassified

Pengamanan Data melalui Model Super Enkripsi Autokey Cipher dan Transposisi Kolom

Fadlan¹,

Haryansyah²,

Rosmini³

2021

RESTI

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One of the essential instruments in the cyber era is data. Therefore, maintaining data security is an important thing to do. One way that can be done to maintain data security is through cryptography. In cryptography, two basic techniques are commonly used, namely substitution techniques and transposition techniques. One of the weaknesses of the basic cryptographic techniques is the lower level of data security. This study proposed a super encryption model in securing data by combining cryptographic algorithms with substitution techniques, i.e., autokey cipher and transposition, i.e., columnar transposition cipher. This study used the Avalanche Effect method as a measurement tool for the proposed super encryption model. The test results have shown that the proposed super encryption model can provide a better level of security. The avalanche effect test on the five data test shows that the average AE value of the proposed super encryption model is 30.76%. This value is higher than the single autokey cipher algorithm of 1.66% and column transposition with a value of 18.03%. Other results from the five data test have shown that the proposed model has a high level of accuracy of 100% in terms of the decryption process results, which is the same as the initial data before going through the encryption process.

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“…IoT devices and platforms are advancing boundless while initiating a seamless combination of computer networks with things or objects [1,2]. IoT is an open network platform and a new communication standard for the latest innovations, connecting multiple heterogeneous devices to render new conventional services [3,4].…”

Section: Introductionmentioning

confidence: 99%

“…Consequently, new services provided by IoT devices have to be sufficiently secured utilizing solid cryptographic algorithms such as AES [1,2]. A cryptographic algorithm is a mathematical method that converts plaintext (simple messages) into ciphertext (unclear messages), and vice versa [5,6].…”

Section: Introductionmentioning

confidence: 99%

Preventing Differential Cryptanalysis Attacks Using a KDM Function and the 32-Bit Output S-Boxes on AES Algorithm Found on the Internet of Things Devices

Muthavhine

Sumbwanyambe

2022

Cryptography

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Many Internet of Things (IoT) devices use an Advanced Encryption Standard (AES) algorithm to secure data stored and transmitted during the communication process. The AES algorithm often suffers DC (DC) attacks. Little has been done to prevent DC attacks, particularly on an AES algorithm. This study focuses on preventing Differential Cryptanalysis attacks. DC attacks are practiced on an AES algorithm that is found on IoT devices. The novel approach of using a Khumbelo Difference Muthavine (KDM) function and changing the 8 × 8 S-Boxes to be the 8 × 32 S-Boxes successfully prevents DC attacks on an AES algorithm. A KDM function is a newly mathematically developed function, coined and used purposely in this study. A KDM function was never produced, defined, or utilized before by any researcher except for in this study. A KDM function makes a new 32-Bit S-Box suitable for the new Modified AES algorithm and confuses the attacker since it comprises many mathematical modulo operators. Additionally, these mathematical modulo operators are irreversible. The study managed to prevent the DC attack of a minimum of 70% on AES and a maximum of 100% on a Simplified DES. The attack on the new Modified AES Algorithm is 0% since no S-Box is used as a building block.

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An analysis and a comparative study of cryptographic algorithms used on the Internet of Things (IoT) based on avalanche effect

Cited by 23 publications

References 33 publications

Converting AES Algorithm to be LWCAES using LCPoAES for Ease Installation on IoT Devices

Converting AES Algorithm to be LWCAES using LCPoAES for Ease Installation on IoT Devices

Pengamanan Data melalui Model Super Enkripsi Autokey Cipher dan Transposisi Kolom

Preventing Differential Cryptanalysis Attacks Using a KDM Function and the 32-Bit Output S-Boxes on AES Algorithm Found on the Internet of Things Devices

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