Introduction to the Special Issue on DNA-centric Modeling and Practice for Next-generation Computing and Communication Systems

Deoxyribonucleic Acid (DNA) computing is an emerging branch of computing that uses the DNA sequence, biochemistry, and hardware for encoding genetic information in computers. This concept was first used in the field of computation in 1994. In DNA computing, information is represented by using the four genetic alphabets or DNA bases, namely, A (Adenine), G (Guanine), C (Cytosine), and T (Thymine), instead of the binary representation (1 and 0) used in traditional computers. This is achieved because short DNA molecules of any arbitrary sequence of A, G, C, and T can be synthesized to order. DNA computing is mainly popular for three reasons: (i) speed (ii) minimal storage requirements, and (iii) minimal power requirements. While DNA computing has been extensively studied in various fields of computer science, its applications in the cloud computing arena are still in their infancy. In a cloud environment, DNA computing can be used for improving data security through a DNA computing-based data encryption process. As four DNA bases are used in the encryption process, DNA computing supports more randomness and makes the encryption process more complex for attackers or malicious users to hack. Automated cloud data storage approaches using DNA computing are another emerging trend in the computer science domain. This topic is now receiving significant attention due to the rapid advancement of Internet of Things (IoT) technologies by which a massive amount of data is generated and processed in daily life. DNA computing can tackle this issue, since merely one gram of DNA can store approximately 700 TB of data. Furthermore, DNA computing can play a key role in the security of Wireless Sensor Network (WSN) composed of hundreds of distributed sensing systems.

The intent of this special issue is to invite scholars, researchers, engineers, and other innovators to collectively show their state-of-the-art knowledge and their cutting-edge innovations in the area of DNA-centric modeling and practice for next-generation computing and communication systems. Call for Papers of this special issue received 21 high-quality submissions. All articles were reviewed by at least three independent potential referees. The articles were evaluated based on their quality and relevance to the theme of this special issue. After a rigorous review process, 3 articles were finally accepted. The following articles of this special issue explore use cases of DNA computing for next-generation computing and communication systems.

The first article, by Zeng et al., entitled “ Towards Intelligent Attack Detection Using DNA Computing,” proposes a novel scheme based on an unbalanced index and an optimal feature index to improve the robustness of the existing cyberattack detection methods. Here, DNA computing is used for encoding and decoding features of network data that support obtaining a better subset of features by using biochemical reactions. After that, the detection balance is optimized through non-dominated ranking. Four datasets are considered in this novel scheme to evaluate the performance. Experimental results show the efficiency of this scheme over some well-known existing schemes in detecting cyberattacks.

The article entitled “ DNA Computing-based Multi-source Data Storage Model in Digital Twins,” by Wang et al., utilizes DNA computing to store data in digital twins. Here, the raptor code has been improved from the design direction of the degree distribution function. Also, six degree function distribution schemes have been proposed in this scheme and a Huffman coding technique is used for DNA computing-based data storage process. The results of the experiments show that the bit error rate is decreased and the signal-to-noise ratio is increased.

In “ A DNA-based Color Image Encryption Scheme Using a Convolutional Autoencoder,” a novel scheme has been proposed by using a convolutional autoencoder, chaos theory, and DNA computing to improve the security of color images. There are two main modules in this scheme: (i) dimensionality conversion and (ii) encryption/decryption module. Here, the original dimension of color images is reduced using the encoder, and then the encryption and decryption processes are performed to improve security. This scheme supports high security because of using DNA computing with substitution boxes and multiple chaotic sequences. Several parameters such as entropy, key sensitivity, histogram of the cipher image, and many more, are considered to evaluate the performance of the proposed scheme, which shows its efficiency.

Finally, the guest editors wish to thank Editors-in-Chief Abdulmotaleb El Saddik, immediate past Editor-in-Chief Alberto Del Bimbo, information director M. Anwar Hossein, immediate past information director Stefano Berretti, and other editorial members and officials of ACM TOMM for giving the opportunity to edit this special issue. The guest editors are also thankful to the reviewers for their constructive comments and to the authors for submitting their contributions.

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