Improving Blockchain Security: Integrating Encryption and Hashing Techniques

Authors

  • Ankita Srivastava, Shish Ahamad

Keywords:

Data protection, Encryption methods, Hashing algorithms, EHR (Electronic Health Record), Performance enhancements

Abstract

In real-time systems, the maintenance of patient records and identity management has become increasingly crucial for efficient record-keeping. This study delves into the potential of blockchain technology to bolster data protection. The primary goal is to suggest enhancements through the utilization of hashing and encryption approaches. Under this methodology, each record functions as an operation, with all blockchain transactions securely recorded in a public ledger. The inclusion of data encryption before blockchain storage offers an additional layer of security, currently under scrutiny. The hashing algorithm is employed to further fortify blockchain security. Hashing & encryption are fundamental modules of blockchain, ensuring data confidentiality, legitimacy, and permanence within the distributed ledger. Encryption converts sensitive data into ciphertext, accessible solely with the appropriate cryptographic key, thereby thwarting unauthorized entry. The security of blockchain technology relies on the collaboration between hashing and encryption, providing robust protection against data manipulation and unauthorized entry while upholding the distributed ledger's integrity. This research assesses security and performance enhancements by examining error rates, efficiency, precision, and security protocols. Performance is gauged in terms of time, security is analyzed by identifying external attacks on blocks, and accuracy is evaluated using metrics like recall, precision, and F1-score.

Downloads

Download data is not yet available.

References

K. N. Griggs et al., "Healthcare blockchain system using smart contracts for secure automated remote patient monitoring," J. Med. Syst., vol. 42, pp. 1-7, 2018. doi: 10.1007/s10916-018-0982-x.

I. Radanović and R. Likić, "Opportunities for use of blockchain technology in medicine," Appl. Health Econ. Health Policy, vol. 16, pp. 583-590, 2018. doi: 10.1007/s40258-018-0412-8.

D. Calvaresi et al., "Multi-agent systems and blockchain: Results from a systematic literature review," in Adv. Pract. Appl. Agents Multi-Agent Syst. Complex.: PAAMS Collect., vol. 16, 2018, pp. 110-126. doi: 10.1007/978-3-319-94580-4_9.

A. Zhang and X. Lin, "Towards secure and privacy-preserving data sharing in e-health systems via consortium blockchain," J. Med. Syst., vol. 42, no. 8, p. 140, 2018. doi: 10.1007/s10916-018-0995-5.

X. Liang et al., "Towards decentralized accountability and self-sovereignty in healthcare systems," in Inf. Commun. Secur.: 19th Int. Conf., Beijing, China, 2018, pp. 387-398. doi: 10.1007/978-3-319-89500-0_34.

M. H. Miraz and M. Ali, "Blockchain enabled enhanced IoT ecosystem security," in Emerg. Technol. Comput.: First Int. Conf., London, UK, 2018, pp. 38-46. doi: 10.1007/978-3-319-95450-9_3.

A. Firdaus et al., "Root exploit detection and features optimization: Mobile device and blockchain based medical data management," J. Med. Syst., vol. 42, pp. 1-23, 2018. doi: 10.1007/s10916-018-0966-x.

H. Li et al., "Blockchain-based data preservation system for medical data," J. Med. Syst., vol. 42, pp. 1-13, 2018. doi: 10.1007/s10916-018-0997-3.

G. Epiphaniou et al., "Blockchain and healthcare," in Blockchain Clin. Trial, Springer International Publishing, 2019, pp. 1-29. doi: 10.1007/978-3-030-11289-9_1.

T. Zhou et al., "Med-PPPHIS: Blockchain-based personal healthcare information system for national physique monitoring and scientific exercise guiding," J. Med. Syst., vol. 43, pp. 1-23, 2019. doi: 10.1007/s10916-019-1430-2.

S. Iram et al., "Connecting to smart cities: Analyzing energy times series to visualize monthly electricity peak load in residential buildings," in Proc. Future Technol. Conf. (FTC), Springer International Publishing, 2019, pp. 333-342. doi: 10.1007/978-3-030-02686-8_26.

G. Rathee et al., "A hybrid framework for multimedia data processing in IoT-healthcare using blockchain technology," Multimed. Tools Appl., vol. 79, no. 15-16, pp. 9711-9733, 2020. doi: 10.1007/s11042-019-07835-3.

I. Abu-Elezz et al., "The benefits and threats of blockchain technology in healthcare: A scoping review," Int. J. Med. Inform., vol. 142, article 104246, 2020. doi: 10.1016/j.ijmedinf.2020.104246.

D. J. Munoz et al., "Clinicappchain: A low-cost blockchain hyperledger solution for healthcare," in Blockchain Appl.: Int. Congr., Springer International Publishing, 2020, pp. 36-44. doi: 10.1007/978-3-030-23813-1_5.

R. M. Amir Latif et al., "A remix IDE: Smart contract-based framework for the healthcare sector by using blockchain technology," Multimed. Tools Appl., pp. 1-24, 2020. doi: 10.1007/s11042-020-10087-1.

A. Mubarakali, "Healthcare services monitoring in cloud using secure and robust healthcare-based BLOCKCHAIN (SRHB) approach," Mobile Netw. Appl., vol. 25, pp. 1330-1337, 2020. doi: 10.1007/s11036-020-01551-1.

G. Nagasubramanian et al., "Securing e-health records using keyless signature infrastructure blockchain technology in the cloud," Neural Comput. Appl., vol. 32, pp. 639-647, 2020. doi: 10.1007/s00521-018-3915-1.

A. Hasselgren et al., "Blockchain in healthcare and health sciences-A scoping review," Int. J. Med. Inform., vol. 134, article 104040, 2020. doi: 10.1016/j.ijmedinf.2019.104040.

R. Casado-Vara et al., "Cooperative algorithm to improve temperature control in recovery unit of healthcare facilities," in Int. Symp. Distrib. Comput. Artif. Intell., Springer International Publishing, 2018, pp. 49-62. doi: 10.1007/978-3-030-00524-5_8.

M. P. McBee and C. Wilcox, "Blockchain technology: Principles and applications in medical imaging," J. Digit. Imaging, vol. 33, pp. 726-734, 2020. doi: 10.1007/s10278-019-00310-3.

M. U. Khan and F. Ahamad, "An Affective Framework for Multimodal Sentiment Analysis to Navigate Emotional Terrains," Telematique, vol. 23, no. 01, pp. 70-83, 2024.

A. Srivastava and S. Ahmad, "Bio-Computing Based Algorithms for Cloud Security: A Critical Review," in 2022 IEEE World Conf. Appl. Intell. Comput. (AIC), Sonbhadra, India, 2022, pp. 894-900. doi: 10.1109/AIC55036.2022.9848965.

F. Ahmad and M. M. Tripathi, "Approaches of big data in healthcare: a critical review," Int. J. Adv. Res. Comput. Sci., vol. 9, no. 2, pp. 122-127, 2018.

M. U. Khan and F. Ahamad, "Multimodal Data Analysis and Machine Learning Techniques: A Comparison and Review," NeuroQuantology, vol. 20, no. 22, pp. 4196-4208, Dec. 2022.

Downloads

Published

09.07.2024

How to Cite

Ankita Srivastava. (2024). Improving Blockchain Security: Integrating Encryption and Hashing Techniques. International Journal of Intelligent Systems and Applications in Engineering, 12(22s), 740 –. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/6550

Issue

Vol. 12 No. 22s (2024)

Section

Research Article

License

Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

All papers should be submitted electronically. All submitted manuscripts must be original work that is not under submission at another journal or under consideration for publication in another form, such as a monograph or chapter of a book. Authors of submitted papers are obligated not to submit their paper for publication elsewhere until an editorial decision is rendered on their submission. Further, authors of accepted papers are prohibited from publishing the results in other publications that appear before the paper is published in the Journal unless they receive approval for doing so from the Editor-In-Chief.

IJISAE open access articles are licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. This license lets the audience to give appropriate credit, provide a link to the license, and indicate if changes were made and if they remix, transform, or build upon the material, they must distribute contributions under the same license as the original.