Mixed Radix Conversion based RSA Encryption System

Abdul-Mumin, Salifu; Gbolagade, Kazeem Alagbe

doi:10.5120/ijca2016911455

Cited by 2 publications

(8 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The prosed scheme outperformed the classical RSA encryption scheme in terms of security with respect to messages such that m e < N. The key-length is also enhanced in the proposed scheme. The proposed scheme outperformed the scheme proposed in [20] in terms of propagation delay and cost. The dynamic range of the proposed scheme is also more than the dynamic range in the scheme proposed in [20].…”

Section: Performance Evaluationmentioning

confidence: 90%

“…The proposed scheme outperformed the scheme proposed in [20] in terms of propagation delay and cost. The dynamic range of the proposed scheme is also more than the dynamic range in the scheme proposed in [20]. This means that more information can be represented in the proposed scheme than that in [20].…”

Section: Performance Evaluationmentioning

confidence: 90%

“…The dynamic range of the proposed scheme is also more than the dynamic range in the scheme proposed in [20]. This means that more information can be represented in the proposed scheme than that in [20].…”

Section: Performance Evaluationmentioning

confidence: 97%

“…The hardware implementation of the second level of decryption stage is based on equation (20) and (21). In figure 2, u1, u2, and u3 are added by CSA1 with end around carry (EAC) producing s1 and c1.…”

Section: Hardware Implementationmentioning

confidence: 99%

“…In the scheme proposed in [20], the total delay for stage-2 encryption and stage-1 decryption is (12 + 10) FA and the total cost or area for both forward and reverse conversion is (15 + 5)D FA…”

Section: Performance Evaluationmentioning

confidence: 99%

See 4 more Smart Citations

Rivest Shamir Adleman Encryption Scheme Based on the Chinese Remainder Theorem

Abdul-Mumin¹

2018

NET

Self Cite

View full text Add to dashboard Cite

Sensitive information is transmitted across the internet every day and keeping such information as sacred is an important adventure. This is because malicious activities are on the increase as hackers are doing everything possible to steal such information. In this paper, we have implemented a new Rivest Shamir Adleman (RSA) encryption scheme based on the Chinese Remainder Theorem (CRT). The scheme consists of two level of encryption and two level of decryption. The first level of encryption is the classical RSA encryption and in the second level of encryption, we used forward conversion technique in Residue Number System. In the first level of decryption, we employed the CRT and the classical RSA decryption process is used for the second level of decryption. This new scheme will ensure that smaller messages, m for which c=m e

show abstract

Section: Performance Evaluationmentioning

confidence: 90%

Section: Performance Evaluationmentioning

confidence: 90%

Section: Performance Evaluationmentioning

confidence: 97%

Section: Hardware Implementationmentioning

confidence: 99%

Section: Performance Evaluationmentioning

confidence: 99%

See 3 more Smart Citations

Rivest Shamir Adleman Encryption Scheme Based on the Chinese Remainder Theorem

Abdul-Mumin¹

2018

NET

Self Cite

View full text Add to dashboard Cite

show abstract

CryptoDL: Predicting Dyslexia Biomarkers from Encrypted Neuroimaging Dataset Using Energy-Efficient Residue Number System and Deep Convolutional Neural Network

Usman

Muniyandi

2020

Symmetry

View full text Add to dashboard Cite

The increasing availability of medical images generated via different imaging techniques necessitates the need for their remote analysis and diagnosis, especially when such datasets involve brain morphological biomarkers, an important biological symmetry concept. This development has made the privacy and confidentiality of patients’ medical records extremely important. In this study, an approach for a secure dyslexia biomarkers classification is proposed using a deep learning model and the concept of residue number system (RNS). A special moduli set of RNS was used to develop a pixel-bitstream encoder that encrypts the 7-bit binary value of each pixel present in the training and testing brain magnetic resonance imaging (MRI) dataset (neuroimaging dataset) prior to classification using cascaded deep convolutional neural network (CNN). Theoretical analysis of our encoder design shows that the proposed pixel-bitstream encoder is a combinational circuit that requires fewer fast adders, with area complexity of 4n AFA and time delay of (3n + 3) DFA for n ≥ 3. FPGA implementation of the proposed encoder shows 23.5% critical path delay improvement and saves up to 42.4% power. Our proposed cascaded deep CNN also shows promising classification outcomes, with the highest performance accuracy of 73.2% on the encrypted data. Specifically, this study has attempted to explore the potencies of CNN to discriminate cases of dyslexia from control subjects using encrypted dyslexia biomarkers neuroimaging dataset. This kind of research becomes expedient owing to the educational and medical importance of dyslexia.

show abstract

Mixed Radix Conversion based RSA Encryption System

Cited by 2 publications

References 7 publications

Rivest Shamir Adleman Encryption Scheme Based on the Chinese Remainder Theorem

Rivest Shamir Adleman Encryption Scheme Based on the Chinese Remainder Theorem

CryptoDL: Predicting Dyslexia Biomarkers from Encrypted Neuroimaging Dataset Using Energy-Efficient Residue Number System and Deep Convolutional Neural Network

Contact Info

Product

Resources

About