Amino Acid Encryption Method Using Genetic Algorithm for Key Generation

Cloud computing is an extensive technology from which the client could access several services through a remote server. Authentication of the remote services needs a common key between the client and the server in a secured manner. The existing key agreement protocols utilized various techniques for the preservation of the data security. The proposed work attempted to provide a high secure data by optimizing the key generation for encryption and decryption process. Hybridization of a novel ECC (Elliptic Curve Cryptography) algorithm and homomorphic ElGamal algorithm for encryption and decryption and also employment of a bio-inspired Genetic algorithm for the generation of maximum secured key is performed. A random 128 bit hash have been developed for the generation of two input points to run the homomorphic property in the ElGamal algorithm secures the key and make it as a non breakable one. The integrated property of ECC and the ElGamal associated with the Genetic algorithm makes the key more stabilized and a confidential one that is more resistant to the various kinds of attacks. The performance analysis depicted that the proposed technique outperform the existing with respect to computational time.

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A New Image Encryption Method Based on Improved Cipher Block Chaining with Optimization Technique

Securing the Internet of Things ◽

10.4018/978-1-5225-9866-4.ch041 ◽

2020 ◽

pp. 939-955

Author(s):

Kuppusamy Krishnamoorthy ◽

Mahalakshmi Jeyabalu

Keyword(s):

Optimization Technique ◽

Dynamic Environment ◽

Block Ciphers ◽

Generation Process ◽

Key Generation ◽

Generation Algorithm ◽

Unauthorized Access ◽

Encryption Method ◽

Block Chaining

Security of images in transmission medium is most prime issue found in literature. Encryption of images is a way to secure it from unauthorized access. The authors in this chapter insist on the encryption of images via block ciphers. Block ciphers works simultaneously as well as on chunks. In this chapter, an encryption method using improved cipher block chaining is proposed to encrypt RGB color images. For every encryption methodology, key generation process is the most important phase. The authors proposed sub-optimal key generation algorithm and this nature inspired optimization technique reveals complex keys, remains very useful for decision making in dynamic environment. Key generation is crafted as complex with this mathematical model that overcomes the predicament key problem exists in existing methods and upgrades quality of encryption. Results of the proposed algorithm show the efficiency and its resistance against various cryptanalytic attacks.

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A High Security Symmetric Key Generation by Using Genetic Algorithm Based on a Novel Similarity Model

Mobile Networks and Applications ◽

10.1007/s11036-021-01753-1 ◽

2021 ◽

Author(s):

Min-Yan Tsai ◽

Hsin-Hung Cho

Keyword(s):

Genetic Algorithm ◽

Key Generation ◽

High Security ◽

Similarity Model ◽

Symmetric Key

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Protein Structure Prediction Based on Improved Genetic Algorithm

International Journal of Environmental Science and Development ◽

10.18178/ijesd.2020.11.9.1289 ◽

2020 ◽

Vol 11 (9) ◽

pp. 450-454

Author(s):

Jiaxi Liu ◽

Keyword(s):

Genetic Algorithm ◽

Protein Structure ◽

Amino Acid ◽

Protein Structure Prediction ◽

Structure Prediction ◽

Protein Structures ◽

Three Dimensional ◽

Dimensional Structure ◽

Improved Genetic Algorithm ◽

Research Areas

The prediction of protein three-dimensional structure from amino acid sequence has been a challenge problem in bioinformatics, owing to the many potential applications for robust protein structure prediction methods. Protein structure prediction is essential to bioscience, and its research results are important for other research areas. Methods for the prediction an才d design of protein structures have advanced dramatically. The prediction of protein structure based on average hydrophobic values is discussed and an improved genetic algorithm is proposed to solve the optimization problem of hydrophobic protein structure prediction. An adjustment operator is designed with the average hydrophobic value to prevent the overlapping of amino acid positions. Finally, some numerical experiments are conducted to verify the feasibility and effectiveness of the proposed algorithm by comparing with the traditional HNN algorithm.

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Characterization of the hypothetical proteins of Human Papillomavirus DNA consensus sequence

Research Journal of Biotechnology ◽

10.25303/167rjbt19721 ◽

2021 ◽

Vol 16 (7) ◽

pp. 197-202

Author(s):

Suruchi Jamkhedkar

Keyword(s):

Genetic Algorithm ◽

Human Papillomavirus ◽

Amino Acid ◽

High Risk ◽

Amino Acid Sequence ◽

Drug Development ◽

Dna Sequences ◽

Consensus Sequence ◽

Software Tool ◽

Molecular Techniques

The diagnosis of HPV infection is generally carried out using immunological and molecular techniques based on high risk to probable high-risk HPV strains. The aim of this work is to generate a global representation of HPV strains for diagnosis and drug development. In this work, all the complete genomic DNA sequences of registered Human Papillomavirus (HPV) strains available in NCBI GenBank were used to obtain a consensus sequence of HPV using the Genetic Algorithm. The consensus DNA sequence was translated using the ExPASy software tool. In all, six longest amino acids frames were selected from the six translated frames. The amino acid sequence identity was carried out using the BLAST tool. The six amino acid sequences were identified as E1, E2, E6, E7, L1 and L2. The homology modeling method (Modeller Software Tool) was used to determine the secondary structure of these six identified primary amino acid sequence. The percentage of similarity ranged from 24% in L2 to 100% in E7 and L1. The functions of these structural domains were also determined from PDB databank, InterProScan and CATH. Hence the consensus sequence built using a genetic algorithm is representative of the HPV genome which can be used for diagnostics and drug development purposes.

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