Special Issue on Information Security and Cryptography: The Role of Advanced Digital Technology

Information security has become a potential prospect that ensures information cannot be breached throughout the process of delivery while being exchanged over the Internet. In recent times, blockchain technology has played a critical role by providing a modular infrastructure, the main objectives of which are to maintain information integrity, transparency, provenance, and trustworthiness in a distributed environment [1].

In this Special Issue, we introduced the role of advanced digital technology (ADT), especially cryptography, such as public key cryptography and private key cryptography, which includes advancements in hash-re-encryption (SHA-256), NuCypher Threshold Proxy Re-Encryption (NTPRE), and authentication [2,3], in information security. We present a set of papers that have been selected after rigorous peer review within the scope of cryptography, blockchain distributed ledger technology, information security, cyber security, and their related sub-domains involved at various levels of system privacy and security.

In a device-to-device- or system-to-system-level environment, various aspects that disintegrate have been highlighted, along with a description of related impacts on the ecosystem in terms of making compromises, such as recycled passwords, the physical theft of sensitive devices, simplifying access permissions, vulnerabilities, and the use of default passwords [4,5].

Recently, cryptography collaborated with the newly developed distributed ledger technology (DLT), which has been proposed as a secure and protected infrastructure for designing a novel environment of information security in almost every domain of information technology (IT). This Special Issue has presented a new paradigm in computing privacy protection and security-related structures to bring new cryptographic principles to the attention of readers and new researchers [6].

In traditional security adaptations, cybersecurity solutions are immature and often considered as an afterthought; they are critical because there is a need to design a system first and then retrofit solutions with cybersecurity. This collaborative approach promotes a proactive environment, which means the design of the ecosystem is tightly exhibited in terms of the provision of a novel and secure infrastructure with the association of cybersecurity that aims to manage flow controls, from the initial design steps to delivery. The fundamental tasks related to this technology include (i) default security management; (ii) proactive and reactive mechanisms; (iii) embedded-enabling design; (iv) end-to-end lifecycles; (v) a fully functional environment; (vi) integrity and transparency; (vii) a secure channel for transmission; and (viii) connected stakeholder environments.

In the blockchain cryptographic technique (BCT), security protocols are one of the core components for securing data from unauthorized access [7,8]. To secure transactions, two nodes of the chain are interconnected in chronological order in the consortium blockchain network. The three main pillars that make this infrastructure more protected are (i) the peer-to-peer (P2P) network [9]; (ii) cryptographic hash encryption [10]; and (iii) distributed storage [11], often referred to as a ledger in the blockchain domain. However, the working scenario of BCT aims to make the system safer within a point-to-point network space, which is difficult to achieve in traditional environments due to weak approaches to system security. In this recent integration, blockchain uses two types of privacy protection and security solutions, namely hashing and NuCypher mechanisms. For instance, the basic difference between these types is that one encrypts information in a P2P network, and the second ensures secure links as blocks of information travel through the chain over the P2P network.

On the other hand, encryption is generally considered a best practice from a security perspective and has recently been applied to the Internet of Things (IoT) environment for data encryption [12]. This application creates a new paradigm in terms of offering stronger protection against malicious threats over the Internet. Undoubtedly, the IoT is considered a significant prospect that contributes significantly to advanced digital technology. However, currently, the risk of unauthorized access due to the connection of a large number of devices over the network is one of the critical challenges [13,14], along with IoT analytics and the IoT process hierarchy.

Acknowledgments

In this Editorial, we thank all the authors and peer reviewers for making this Special Issue, entitled “Cryptography and Information Security”, successful.

Conflicts of Interest

The authors declare no conflict of interest.

List of Contributions

• Por, L.Y.; Yang, J.; Ku, C.S.; Khan, A.A. Special Issue on Cryptography and Information Security. Appl. Sci. 2023, 13, 6042. https://doi.org/10.3390/app13106042.

• Yang, J.; Chen, Y.-L.; Por, L.Y.; Ku, C.S. A Systematic Literature Review of Information Security in Chatbots. Appl. Sci. 2023, 13, 6355. https://doi.org/10.3390/app13116355.

• Cao, Y.; Li, H.; Han, L.; Zhao, X.; Pan, X.; Yao, E. AccFlow: Defending against the Low-Rate TCP DoS Attack in Drones. Appl. Sci. 2023, 13, 11749. https://doi.org/10.3390/app132111749.

• Li, Y.; Kang, F.; Shu, H.; Xiong, X.; Zhao, Y.; Sun, R. APIASO: A Novel API Call Obfuscation Technique Based on Address Space Obscurity. Appl. Sci. 2023, 13, 9056. https://doi.org/10.3390/app13169056.

• López-García, D.A.; Pérez Torreglosa, J.; Vera, D.; Sánchez-Raya, M. Binary-Tree-Fed Mixnet: An Efficient Symmetric Encryption Solution. Appl. Sci. 2024, 14, 966. https://doi.org/10.3390/app14030966.

• Gavrovska, A. Effects on Long-Range Dependence and Multifractality in Temporal Resolution Recovery of High Frame Rate HEVC Compressed Content. Appl. Sci. 2023, 13, 9851. https://doi.org/10.3390/app13179851.

• Al-Shatari, M.; Hussin, F.A.; Aziz, A.A.; Eisa, T.A.E.; Tran, X.-T.; Dalam, M.E.E. IoT Edge Device Security: An Efficient Lightweight Authenticated Encryption Scheme Based on LED and PHOTON. Appl. Sci. 2023, 13, 10345. https://doi.org/10.3390/app131810345.

• Li, H.; Li, J.; Wang, Y.; Zhou, C.; Yin, M. Leaving the Business Security Burden to LiSEA: A Low-Intervention Security Embedding Architecture for Business APIs. Appl. Sci. 2023, 13, 11784. https://doi.org/10.3390/app132111784.

• Yin, J.; Cui, J. Secure Application of MIoT: Privacy-Preserving Solution for Online English Education Platforms. Appl. Sci. 2023, 13, 8293. https://doi.org/10.3390/app13148293.

• Lee, M.; Seo, M. Secure and Efficient Deduplication for Cloud Storage with Dynamic Ownership Management. Appl. Sci. 2023, 13, 13270. https://doi.org/10.3390/app132413270.

• Shyaa, G.S.; Al-Zubaidie, M. Utilizing Trusted Lightweight Ciphers to Support Electronic-Commerce Transaction Cryptography. Appl. Sci. 2023, 13, 7085. https://doi.org/10.3390/app13127085.

• Alhamarneh, R.A.; Mahinderjit Singh, M. Strengthening Internet of Things Security: Surveying Physical Unclonable Functions for Authentication, Communication Protocols, Challenges, and Applications. Appl. Sci. 2024, 14, 1700. https://doi.org/10.3390/app14051700.

Footnotes

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References

1. Khan, A.A.; Shaikh, A.A.; Laghari, A.A. IoT with Multimedia Investigation: A Secure Process of Digital Forensics Chain-of-Custody Using Blockchain Hyperledger Sawtooth. Arab. J. Sci. Eng.; 2023; 48, pp. 10173-10188. [DOI: https://dx.doi.org/10.1007/s13369-022-07555-1]

2. Wu, T.-Y.; Meng, Q.; Chen, Y.-C.; Kumari, S.; Chen, C.-M. Toward a Secure Smart-Home IoT Access Control Scheme Based on Home Registration Approach. Mathematics; 2023; 11, 2123. [DOI: https://dx.doi.org/10.3390/math11092123]

3. Wu, T.-Y.; Meng, Q.; Yang, L.; Kumari, S.; Pirouz, M. Amassing the Security: An Enhanced Authentication and Key Agreement Protocol for Remote Surgery in Healthcare Environment. Comput. Model. Eng. Sci.; 2023; 134, pp. 317-341. [DOI: https://dx.doi.org/10.32604/cmes.2022.019595]

4. Rana, M.; Mamun, Q.; Islam, R. Lightweight Cryptography in IoT Networks: A Survey. Future Gener. Comput. Syst.; 2022; 129, pp. 77-89. [DOI: https://dx.doi.org/10.1016/j.future.2021.11.011]

5. Mehic, M.; Michalek, L.; Dervisevic, E.; Burdiak, P.; Plakalovic, M.; Rozhon, J.; Mahovac, N.; Richter, F.; Kaljic, E.; Lauterbach, F. et al. Quantum cryptography in 5g networks: A comprehensive overview. IEEE Commun. Surv. Tutor.; 2023; 26, pp. 302-346. [DOI: https://dx.doi.org/10.1109/COMST.2023.3309051]

6. Tanwar, S.; Kumar, A. Secure Key Issuing Scheme in ID-Based Cryptography with Revocable ID. Inf. Secur. J. Glob. Perspect.; 2022; 31, pp. 676-685. [DOI: https://dx.doi.org/10.1080/19393555.2022.2033366]

7. Alhayani, B.S.A.; Hamid, N.; Almukhtar, F.H.; Alkawak, O.A.; Mahajan, H.B.; Kwekha-Rashid, A.S.; İlhan, H.; Marhoon, H.A.; Mohammed, H.J.; Chaloob, I.Z. et al. Optimized Video Internet of Things Using Elliptic Curve Cryptography Based Encryption and Decryption. Comput. Electr. Eng.; 2022; 101, 108022. [DOI: https://dx.doi.org/10.1016/j.compeleceng.2022.108022]

8. Binbeshr, F.; Kiah, M.M.; Por, L.Y.; Zaidan, A.A. A systematic review of PIN-entry methods resistant to shoulder-surfing attacks. Comput. Secur.; 2021; 101, 102116. [DOI: https://dx.doi.org/10.1016/j.cose.2020.102116]

9. Kairaldeen, A.R.; Abdullah, N.F.; Abu-Samah, A.; Nordin, R. Peer-to-Peer User Identity Verification Time Optimization in IoT Blockchain Network. Sensors; 2023; 23, 2106. [DOI: https://dx.doi.org/10.3390/s23042106] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/36850701]

10. Singh, M.; Singh, A.K. A comprehensive survey on encryption techniques for digital images. Multimed. Tools Appl.; 2023; 82, pp. 11155-11187. [DOI: https://dx.doi.org/10.1007/s11042-022-12791-6]

11. Li, J.; Zhang, Y.; Lu, S.; Gunawi, H.S.; Gu, X.; Huang, F.; Li, D. Performance Bug Analysis and Detection for Distributed Storage and Computing Systems. ACM Trans. Storage; 2023; 19, pp. 1-33. [DOI: https://dx.doi.org/10.1145/3580281]

12. Condon, F.; Franco, P.; Martínez, J.M.; Eltamaly, A.M.; Kim, Y.-C.; Ahmed, M.A. EnergyAuction: IoT-Blockchain Architecture for Local Peer-to-Peer Energy Trading in a Microgrid. Sustainability; 2023; 15, 13203. [DOI: https://dx.doi.org/10.3390/su151713203]

13. Nanjappan, M.; Pradeep, K.; Natesan, G.; Samydurai, A.; Premalatha, G. DeepLG SecNet: Utilizing deep LSTM and GRU with secure network for enhanced intrusion detection in IoT environments. Clust. Comput.; 2024; [DOI: https://dx.doi.org/10.1007/s10586-023-04223-3]

14. Aboukadri, S.; Ouaddah, A.; Mezrioui, A. Machine Learning in Identity and Access Management Systems: Survey and Deep Dive. Comput. Secur.; 2024; 139, 103729. [DOI: https://dx.doi.org/10.1016/j.cose.2024.103729]