Deoxyribonucleic Acid Computing Research Articles

Key dependent information confidentiality scheme based on deoxyribonucleic acid (DNA) and circular shifting

In this era of advanced information technology, the exploration and development of novel mechanisms to ensure information confidentiality have consistently captivated the attention of upcoming researchers. In this article, we present a pioneering approach that combines DNA sequencing with a four-dimensional (4D) hyperchaotic map to bolster the security of digital information. Our primary focus is on the design of a robust and secure scheme for encrypting color images, leveraging DNA cryptography and hyperchaos. By extracting three distinct DNA sequences, we generate encryption keys through the integration of DNA computing and 4D hyperchaotic maps. Notably, these keys are intricately linked to the plaintext and vary with any alterations in the input. Consequently, the proposed encryption method stands resilient against an array of potential cryptographic attacks. To gauge the algorithm's security, we subject it to rigorous standard statistical analysis. Our findings underscore the efficiency and robustness of the proposed framework, establishing its potential for facilitating secure communication.

Hash Based DNA Computing Algorithm for Image Encryption

Deoxyribonucleic Acid (DNA) computing has demonstrated great potential in data encryption due to its capability of parallel computation, minimal storage requirement, and unbreakable cryptography. Focusing on high-dimensional image data for encryption with DNA computing, we propose a novel hash encoding-based DNA computing algorithm, which consists of a DNA hash encoding module and content-aware encrypting module. Inspired by the significant properties of the hash function, we build a quantity of hash mappings from image pixels to DNA computing bases, properly integrating the advantages of the hash function and DNA computing to boost performance. Considering the correlation relationship of pixels and patches for modeling, a content-aware encrypting module is proposed to reorganize the image data structure, resisting the crack with non-linear and high dimensional complexity originating from the correlation relationship. The experimental results suggest that the proposed method performs better than most comparative methods in key space, histogram analysis, pixel correlation, information entropy, and sensitivity measurements.

Review on DNA Cryptography

Cryptography is the science that secures data and communication over the network by applying mathematics and logic to design strong encryption methods. In the modern era of e-business and e-commerce the protection of confidentiality, integrity and availability (CIA triad) of stored information as well as of transmitted data is very crucial. Deoxyribonucleic acid (DNA) is a genetic molecule consisting of two linked strands that wind around each other to form a double helical structure. The backbone of each strand is made of alternating deoxyribose sugar and phosphate groups. To each sugar one of four bases are attached i.e., adenine (A), cytosine (C), guanine (G) and thymine (T). DNA molecules, having the capacity to store, process and transmit information, inspires the idea of DNA cryptography. It is the rapid emerging unconventional techniques which combines the chemical characteristics of biological DNA sequences with classical cryptography to ensure non-vulnerable transmission of data. This innovative method is based on the notion of DNA computing. The methodologies of DNA cryptography are not coded mathematically; thus, it could be too secure to be cracked easily.

Medical Image Encryption by Content-Aware DNA Computing for Secure Healthcare

There exists a rising concern on security of healthcare data and service. Even small lost, stolen, displaced, hacked, or communicated in personal health data could bring huge damage to patients. Therefore, we propose a novel content-aware deoxyribonucleic acid (DNA) computing system to encrypt medical images, thus guaranteeing privacy and promoting secure healthcare environment. The proposed system consists of sender and receiver to perform tasks of encryption and decryption, respectively, where both contain the same structure design, but perform opposite operations. In either sender or receiver, we design a randomly DNA encoding and a content-aware permutation and diffusion module. Considering introducing random mechanism to increase difficulty of cracking, the former module builds a random encryption rule selector in DNA encoding process by randomly mapping quantity of medical image pixels to outputs. Meanwhile, the latter module constructs a permutation sequence, which not only encodes information of pixel values, but also involves redundant correlation between adjacent pixels located in a patch. Such design brings awareness property of medical image content to greatly increase complexity in cracking by embedding semantical information for encryption. We demonstrate that the proposed system successfully improve cybersecurity of medical images against various attacks in robustness and effectiveness when transmitting data in wireless broadcasting scenarios.

DNA Computing with Water Strider Based Vector Quantization for Data Storage Systems

The exponential growth of data necessitates an effective data storage scheme, which helps to effectively manage the large quantity of data. To accomplish this, Deoxyribonucleic Acid (DNA) digital data storage process can be employed, which encodes and decodes binary data to and from synthesized strands of DNA. Vector quantization (VQ) is a commonly employed scheme for image compression and the optimal codebook generation is an effective process to reach maximum compression efficiency. This article introduces a new DNA Computing with Water Strider Algorithm based Vector Quantization (DNAC-WSAVQ) technique for Data Storage Systems. The proposed DNAC-WSAVQ technique enables encoding data using DNA computing and then compresses it for effective data storage. Besides, the DNAC-WSAVQ model initially performs DNA encoding on the input images to generate a binary encoded form. In addition, a Water Strider algorithm with Linde-Buzo-Gray (WSA-LBG) model is applied for the compression process and thereby storage area can be considerably minimized. In order to generate optimal codebook for LBG, the WSA is applied to it. The performance validation of the DNAC-WSAVQ model is carried out and the results are inspected under several measures. The comparative study highlighted the improved outcomes of the DNAC-WSAVQ model over the existing methods.

A dynamic S-box generation based on a hybrid method of new chaotic system and DNA computing

S-box is one of the most significant structures used to construct encryption that is strong and resistant to attacks in encryption algorithms. The new 4D-hyper chaotic system and deoxyribonucleic acid (DNA) computing are used in this paper to provide a new dynamic S-box generating approach. The 4D generated numbers are processed to generate a hexadecimal number that will encode using the DNA coding method and using addition, subtraction, and exclusive-or operations to produce the final DNA string decoded to make the S-Box. The dynamic form of s-boxes is represented by a minor change in the initial conditions of the proposed chaotic method that will generate dynamic sequences of numbers. The proposed method enhances the security criteria of the block ciphers. The S-box testing criteria were done like strict avalanche, balanced, and bit independence criteria, in addition to differential approximation probability and linearity approximation probability, to test the security of the new S-Box. The results show that the new S-box has good security and is resistant to attacks.

An efficient hybrid encryption model based on deep convolutional neural networks, deoxyribonucleic acid computing and chaotic system

An efficient hybrid encryption model based on deep convolutional neural networks, deoxyribonucleic acid computing and chaotic system

Anti-attacks encryption algorithm based on DNA computing and data encryption standard

Data Encryption Standard (DES) is the first 56-bits secret-key standard that is widely used as a symmetric-key 64-bits block encryption/decryption algorithm. Unfortunately, the rapid increase in computing power makes it possible to find the required bits combination of the secret-key in a short time. Due to the promising trends of Deoxyribonucleic Acid (DNA) in cryptography, this paper presents a DES-DNA based symmetric-key block encryption/decryption algorithm called iEncrypt. iEncrypt has two versions, each of them uses a 64-nucleotides secret-key that makes the secret-key of the proposed algorithm intractable as 128-bits secret-key. The experimental works show that the two versions of iEncrypt are intractable against brute force attacks. Moreover, the reduced version of the proposed algorithm, to 4-rounds, shows the intractability of the first version against differential cryptanalysis attacks in addition to the invisibility of attacking the second version. Plain images data are used as one of the rich characteristics data in the statistical evaluation. Statistically, the encrypted images confirm the intractability of both versions of the proposed algorithm.

Data protection based neural cryptography and deoxyribonucleic acid

The need to a robust and effective methods for secure data transferring makes the more credible. Two disciplines for data encryption presented in this paper: machine learning and deoxyribonucleic acid (DNA) to achieve the above goal and following common goals: prevent unauthorized access and eavesdropper. They used as powerful tool in cryptography. This paper grounded first on a two modified Hebbian neural network (MHNN) as a machine learning tool for message encryption in an unsupervised method. These two modified Hebbian neural nets classified as a: learning neural net (LNN) for generating optimal key ciphering and ciphering neural net CNN) for coding the plaintext using the LNN keys. The second granulation using DNA nucleated to increase data confusion and compression. Exploiting the DNA computing operations to upgrade data transmission security over the open nets. The results approved that the method is effective in protect the transferring data in a secure manner in less time

Interconnects for DNA, Quantum, In-Memory, and Optical Computing: Insights From a Panel Discussion

The computing world is witnessing a proverbial Cambrian explosion of emerging paradigms propelled by applications, such as artificial intelligence, big data, and cybersecurity. The recent advances in technology to store digital data inside a deoxyribonucleic acid (DNA) strand, manipulate quantum bits (qubits), perform logical operations with photons, and perform computations inside memory systems are ushering in the era of emerging paradigms of DNA computing, quantum computing, optical computing, and in-memory computing. In an orthogonal direction, research on interconnect design using advanced electro-optic, wireless, and microfluidic technologies has shown promising solutions to the architectural limitations of traditional von-Neumann computers. In this article, experts present their comments on the role of interconnects in the emerging computing paradigms, and discuss the potential use of chiplet-based architectures for the heterogeneous integration of such technologies.

A A Biological-Inspired Cryptosystem based on DNA Cryptography and Morse Code Ciphering Technique

Due to its prominent facility to hide colossal datasets with a high calibre of randomness and subsequent protection, the famous genomic Deoxyribonucleic Acid (DNA) has been presented as a hiding medium, known as DNA steganography. An incipient information-securing technique using the organic DNA structure called DNA Computing was introduced. In this paper, cryptosystem based DNA computation and Morse code cipher is proposed to bulwark the delicate knowledge within the demanding environment. The plaintext is changed over to DNA sequences utilising the encoding table. The encoded information is actually transcribed and translated by the Ribonucleic Acid (RNA) arrangements. Translated RNA is stego by the standard genetic code utilising organic compounds, and the stego DNA is ciphered by Morse code pattern. Avalanche Effect achieves 96.86% bits of average changes occurred in ciphertext. Therefore, the proposed cryptosystem shows strong randomisation and provides complex mapping between plaintext and ciphertext. Also, the designed bio explores analysis and results shows that the security of the transmission is high, and it preserves the biological process.

A new color image encryption technique using DNA computing and Chaos-based substitution box

In many cases, images contain sensitive information and patterns that require secure processing to avoid risk. It can be accessed by unauthorized users who can illegally exploit them to threaten the safety of people’s life and property. Protecting the privacies of the images has quickly become one of the biggest obstacles that prevent further exploration of image data. In this paper, we propose a novel privacy-preserving scheme to protect sensitive information within images. The proposed approach combines deoxyribonucleic acid (DNA) sequencing code, Arnold transformation (AT), and a chaotic dynamical system to construct an initial S-box. Various tests have been conducted to validate the randomness of this newly constructed S-box. These tests include National Institute of Standards and Technology (NIST) analysis, histogram analysis (HA), nonlinearity analysis (NL), strict avalanche criterion (SAC), bit independence criterion (BIC), bit independence criterion strict avalanche criterion (BIC-SAC), bit independence criterion nonlinearity (BIC-NL), equiprobable input/output XOR distribution, and linear approximation probability (LP). The proposed scheme possesses higher security wit NL = 103.75, SAC ≈ 0.5 and LP = 0.1560. Other tests such as BIC-SAC and BIC-NL calculated values are 0.4960 and 112.35, respectively. The results show that the proposed scheme has a strong ability to resist many attacks. Furthermore, the achieved results are compared to existing state-of-the-art methods. The comparison results further demonstrate the effectiveness of the proposed algorithm.

Scaling up DNA digital data storage by efficiently predicting DNA hybridisation using deep learning

Deoxyribonucleic acid (DNA) has shown great promise in enabling computational applications, most notably in the fields of DNA digital data storage and DNA computing. Information is encoded as DNA strands, which will naturally bind in solution, thus enabling search and pattern-matching capabilities. Being able to control and predict the process of DNA hybridisation is crucial for the ambitious future of Hybrid Molecular-Electronic Computing. Current tools are, however, limited in terms of throughput and applicability to large-scale problems. We present the first comprehensive study of machine learning methods applied to the task of predicting DNA hybridisation. For this purpose, we introduce an in silico-generated hybridisation dataset of over 2.5 million data points, enabling the use of deep learning. Depending on hardware, we achieve a reduction in inference time ranging from one to over two orders of magnitude compared to the state-of-the-art, while retaining high fidelity. We then discuss the integration of our methods in modern, scalable workflows.

A novel auto-encoder induced chaos based image encryption framework aiding DNA computing sequence

The day-to-day progress in communication plays a vital role in transmitting millions and trillions of data through the unsecured network channels. It creates a way where the user’s data becomes the victim of various security threats. Among those users’ data, images act as primary data, and its encryption security methodologies are fascinating. The conventional encryption techniques don’t work well against the various other hidden security threats but require substantial computational time and cost with poor permutation performance. Hence to deal with this, an auto-encoder induced DNA (Deoxyribonucleic acid) sequence via chaotic image encryption framework is designed in our proposed work. It integrates the properties of DNA encoding and the chaotic maps to handle the data losses effectively and resist several attacks such as statistical attacks, chosen-plaintext attacks, etc. Moreover, an auto-encoder is used to control the data noises, thereby ensuring a better encryption performance. Here, the auto-encoder is activated to generate a permuted image with less time complexity and noise. A secret key is then initialized with the aid of SHA-256. Finally, image encryption and decryption are achieved, followed by the successful transmission of data over a digital network. The performance of the proposed work is analyzed with varied metrics to strengthen its efficiency over the prior techniques.

Asymmetric DNA encryption and decryption technique for Arabic plaintext

The security of transmitting information from one point to another through different media is an important issue in the modern digital society. Researchers have consistently developed and proposed modern data transfer systems in order to transfer data in a safe manner. DNA (deoxyribonucleic acid) based encryption technology is a new encryption model used to protect data during transmission. Current systems that use DNA technology to encrypt Arabic texts are virtually non-existent and intended to hide data rather than encrypting it (i.e., steganography). In this research, an asymmetric DNA encryption technology is offered to encrypt and decrypt simple Arabic scripts. This technology depends on the integrity between asymmetric cryptography (i.e. RSA algorithm), dynamic encoding, and data dependency with the scope of DNA computing technology. Asymmetric cryptosystem is used only to begin the process of encryption and decryption, which is then processed fully using DNA computing. The idea of the proposed algorithm aims to generate a dynamic DNA table that depend on plain text, that aims to generate a dynamically generating 14 circular keys based on a multi-level security. Here, JAVA platform is used to implement the proposed work, and the randomization and avalanche effect are used to prove the efficiency of the proposed algorithm. This technique provides a significant change in the encoded text with an average of 53% of the avalanche characteristic.

An efficient medical image encryption using hybrid DNA computing and chaos in transform domain.

In this growing era, a massive amount of digital electronic health records (EHRs) are transferred through the open network. EHRs are at risk of a myriad of security threats, to overcome such threats, encryption is a reliable technique to secure data. This paper addresses an encryption algorithm based on integer wavelet transform (IWT) blended with deoxyribo nucleic acid (DNA) and chaos to secure the digital medical images. The proposed work comprises of two phases, i.e. a two-stage shuffling phase and diffusion phase. The first stage of shuffling starts with initial block confusion followed by row and column shuffling of pixels as the second stage. The pixels of the shuffled image are circularly shifted bitwise at the first stage of diffusion to enhance the security of the system against differential attack. The second stage of diffusion operation is based on DNA coding and DNA XOR operations. The experimental analyses have been carried out with 100 DICOM test images of 16-bit depth to evaluate the strength of the algorithm against statistical and differential attacks. By the results, the maximum entropy has been obtained an average of 15.79, NPCR of 99.99, UACI of 33.31, and larger keyspace of 10140, which infer that our technique overwhelms various other state-of-the-art techniques.

Fast and Secure Data Accessing by Using DNA Computing for the Cloud Environment

In a cloud environment, traditional approaches are used to encrypt any data by using 0 and 1 that increase data security issues because of the presence of numerous malicious users and hackers over the internet. Deoxyribonucleic Acid (DNA) computing can be one of the best solutions to improve data security in which data are encrypted using the DNA bases: Thymine (T), Guanine (G), Cytosine (C) and Adenine (A). Along with data security, access control is another major issue of a cloud environment as the searching time of the owner of any data, the system overheard and the accessing time of a file or data are high during data access. A novel DNA computing based secure and fast Access Control Model (ACM) is proposed in this article to solve all these major problems. In the proposed scheme, the Cloud Service Provider (CSP) keeps a table or list for fast data accessing. Here, a 1024-bit DNA computing based random key is generated by using the user's secret information, and the same key is utilized for data encryption. Theoretical analysis along with many experimental results prove the efficiency and effectiveness of the proposed access control model over some well-known existing models.

A DNA algorithm for the job shop scheduling problem based on the Adleman-Lipton model.

A DNA (DeoxyriboNucleic Acid) algorithm is proposed to solve the job shop scheduling problem. An encoding scheme for the problem is developed and DNA computing operations are proposed for the algorithm. After an initial solution is constructed, all possible solutions are generated. DNA computing operations are then used to find an optimal schedule. The DNA algorithm is proved to have an O(n2) complexity and the length of the final strand of the optimal schedule is within appropriate range. Experiment with 58 benchmark instances show that the proposed DNA algorithm outperforms other comparative heuristics.

Securing Multimedia by Using DNA-Based Encryption in the Cloud Computing Environment

Today, the size of a multimedia file is increasing day by day from gigabytes to terabytes or even petabytes, mainly because of the evolution of a large amount of real-time data. As most of the multimedia files are transmitted through the internet, hackers and attackers try to access the users’ personal and confidential data without any authorization. Thus, maintaining a strong security technique has become a significant concerned to protect the personal information. Deoxyribonucleic Acid (DNA) computing is an advanced field for improving security, which is based on the biological concept of DNA. A novel DNA-based encryption scheme is proposed in this article for protecting multimedia files in the cloud computing environment. Here, a 1024-bit secret key is generated based on DNA computing and the user's attributes and password to encrypt any multimedia file. To generate the secret key, the decimal encoding rule, American Standard Code for Information Interchange value, DNA reference key, and complementary rule are used, which enable the system to protect the multimedia file against many security attacks. Experimental results, as well as theoretical analyses, show the efficiency of the proposed scheme over some well-known existing schemes.

DNA computing and table based data accessing in the cloud environment

The attractive benefits of cloud computing environment motivate Information Technology (IT) companies to move their IT infrastructure on the cloud server. In a cloud environment, companies must depend on the untrusted Cloud Service Provider (CSP), which raises data security issues due to the presence of numerous hackers and malicious users. Apart from data security, high searching time of data owner, high data accessing time and high system overheard are other issues during data accessing from the cloud environment. To solve all these issues, in this paper, a novel DNA based fast and secure data access control model has been introduced for the cloud environment. Here, the cloud service provider maintains a table for fast and efficient data accessing. In this proposed scheme, a long 1024-bit Deoxyribonucleic Acid (DNA) based password or secret key is used to encrypt users' confidential or personal data. Experimental results along with theoretical analysis prove the efficiency of the proposed model over the existing models.