Skip to main content
Log in

The rise of “blockchain”: bibliometric analysis of blockchain study

  • Published:
Scientometrics Aims and scope Submit manuscript

Abstract

The blockchain is a technology which accumulates and compiles data into a chain of multiple blocks. Many blockchain researchers are adopting it in multiple areas. However, there are still lacks bibliometric reports exhibiting the exploration of an in-depth research pattern in blockchain. This paper aims to address that gap by analyzing the widespread of blockchain research activities conducted thus far. This study analyzed the Scopus database by using bibliometric analysis in a pool of more than 1000 articles that were published between 2013 and 2018. In particular, this paper discusses various aspects of blockchain research conducted by researchers globally. This study also focuses on the utilization of blockchain and its consensus algorithms. This bibliometric analysis discovered the following: (1) Blockchain able to solve security issues in internet of things (IoT) and would be an increasing trend in the future; (2) Researchers begin to adopt blockchain in healthcare area; (3) The most active country in blockchain publication is United States, followed by China and Germany; (4) Switzerland and Singapore are two small size countries that published few publications, however receives many citations. (5) Research collaborations between countries increased the research publications except for Canada, India, and Brazil. (6) Keyword analysis revealed that researchers are adopting blockchain to solve problems in multiple categories of the data research area (data privacy, digital storage, the security of data, big data, and distributed database). This study also highlighted the utilization and consensus of the algorithm in blockchain research.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19

Similar content being viewed by others

References

  • Adewole, K. S., Anuar, N. B., Kamsin, A., Varathan, K. D., & Razak, S. A. (2017). Malicious accounts: Dark of the social networks. Journal of Network and Computer Applications, 79, 41–67.

    Article  Google Scholar 

  • Ahmed, H. A. S., & Zolkipli, M. F. (2016). Data security issues in cloud computing: Review. International Journal of Software Engineering and Computer Systems (IJSECS), 2(February), 58–65.

    Article  Google Scholar 

  • Al Omar, A., Bhuiyan, M. Z. A., Basu, A., Kiyomoto, S., & Rahman, M. S. (2019). Privacy-friendly platform for healthcare data in cloud based on blockchain environment. Future Generation Computer Systems, 95, 511–521.

    Article  Google Scholar 

  • Alonso, S. G., Arambarri, J., López-Coronado, M., & de la Torre Díez, I. (2019). Proposing new blockchain challenges in eHealth. Journal of Medical Systems, 43(3), 64.

    Article  Google Scholar 

  • Aniello, L., Baldoni, R., Gaetani, E., Lombardi, F., Margheri, A., & Sassone, V. (2017). A prototype evaluation of a tamper-resistant high performance blockchain-based transaction log for a distributed database. In 13th European dependable computing conference, (EDCC), pp. 151–154. Campus BiotechGeneva, Switzerland.

  • Arfaoui, A., Ibrahimi, K., & Trabelsi, F. (2019). Biochar application to soil under arid conditions: A bibliometric study of research status and trends. Arabian Journal of Geosciences. https://doi.org/10.1007/s12517-018-4166-2.

  • Aria, M., & Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959–975.

    Article  Google Scholar 

  • Authors, P. (2018). “Parity” (Online). Available at https://www.parity.io/. Accessed July 25, 2018.

  • Authors, G. E. (2018). “Go Ethereum” (Online). Available at https://geth.ethereum.org. Accessed July 25, 2018.

  • Bartoletti, M., Bellomy, B., & Pompianu, L. (2019). A journey into bitcoin metadata. Journal of Grid Computing, 17, 3–22.

    Article  Google Scholar 

  • Bitmain (2019). “Bitmain” (Online). Available at https://shop.bitmain.com/?lang=en. Accessed May 06, 2019.

  • Brito, J., Nassis, G. P., Seabra, A. T., & Figueiredo, P. (2018). Top 50 most-cited articles in medicine and science in football. BMJ Open Sport and Exercise Medicine, 4(1), 1–8.

    Article  Google Scholar 

  • Cao, S., Zhang, G., Liu, P., Zhang, X., & Neri, F. (2019). Cloud-assisted secure eHealth systems for tamper-proofing EHR via blockchain. Information Sciences, 485, 427–440.

    Article  Google Scholar 

  • Casado-Vara, R., Chamoso, P., De la Prieta, F., Prieto, J., & Corchado, J. M. (2019). Non-linear adaptive closed-loop control system for improved efficiency in IoT-blockchain management. Information Fusion, 49, 227–239.

    Article  Google Scholar 

  • Castro, M., & Liskov, B. (1999). Practical byzantine fault tolerance. In Proceedings of the third symposium on operating systems design and implementation (pp. 1–14).

  • Chen, H. C., Irawan, B., & Shae, Z. Y. (2019a). A cooperative evaluation approach based on blockchain technology for IoT application. Advances in Intelligent Systems and Computing, 773, 913–921.

    Article  Google Scholar 

  • Chen, L., Lee, W. K., Chang, C. C., Choo, K. K. R., & Zhang, N. (2019b). Blockchain based searchable encryption for electronic health record sharing. Future Generation Computer Systems, 95, 420–429.

    Article  Google Scholar 

  • Cherian, M., & Chatterjee, M. (2019). Survey of security threats in iot and emerging countermeasures. In 6th international symposium on security in computing and communications, (SSCC), (Vol. 969, pp. 591–604). Bangalore, India.

  • Christian, D. (2019). Decker Christian (Online). Available at https://disco.ethz.ch/alumni/cdecker. Accessed May 15, 2019.

  • Cirillo, A., Mussolino, D., Saggese, S., & Sarto, F. (2018). Looking at the IPO from the ‘top floor’: A literature review. Journal of Management and Governance, 22(3), 661–688.

    Article  Google Scholar 

  • da Silva Filho, A. C., Maganini, N. D., & de Almeida, E. F. (2018). Multifractal analysis of bitcoin market. Physica A: Statistical Mechanics and its Applications, 512, 954–967.

    Article  Google Scholar 

  • De Angelis, S., Aniello, L., Baldoni, R., Lombardi, F., Margheri, A., & Sassone, V. (2018). PBFT vs proof-of-authority: Applying the CAP theorem to permissioned blockchain. In CEUR workshop proceedings (pp. 1–11).

  • Dehdarirad, T., Villarroya, A., & Barrios, M. (2015). Research on women in science and higher education: A bibliometric analysis. Scientometrics, 103(3), 795–812.

    Article  Google Scholar 

  • Dennis, R., & Disso, J. P. (2019). An analysis into the scalability of bitcoin and ethereum. Advances in Intelligent Systems and Computing, 797, 619–627.

    Article  Google Scholar 

  • Docampo, D., & Cram, L. (2019). Highly cited researchers: A moving target. Scientometrics, 118(3), 1011–1025.

    Article  Google Scholar 

  • Drosatos, G., & Kaldoudi, E. (2019). Blockchain applications in the Biomedical Domain: A Scoping Review. Computational and Structural Biotechnology Journal, 17, 229–240.

    Article  Google Scholar 

  • Dwivedi, A. D., Srivastava, G., Dhar, S., & Singh, R. (2019). A decentralized privacy-preserving healthcare blockchain for IoT. Sensors (Switzerland), 19(2), 1–17.

    Article  Google Scholar 

  • Elango, B., & Rajendran, P. (2012). Authorship trends and collaboration pattern in the marine sciences literature : A scientometric study. International Journal of Information Dissemination and Technology, 2(3), 166–169.

    Google Scholar 

  • Essaid, M., Kim, H. W., Guil Park, W., Lee, K. Y., Jin Park, S., & Ju, H. T. (2018). Network usage of bitcoin full node. In 9th international conference on information and communication technology convergence: Ict convergence powered by smart intelligence (ICTC) (pp. 1286–1291). Maison Glad JejuJeju Island, South Korea.

  • Estrada-Galinanes, V., & Wac, K. (2019). Visions and challenges in managing and preserving data to measure quality of life. In IEEE 3rd international workshops on foundations and applications of self systems (FASW) (pp. 92–99). Torento, Italy.

  • Fahimnia, B., Sarkis, J., & Davarzani, H. (2015). Green supply chain management: A review and bibliometric analysis. International Journal of Production Economics, 162, 101–114.

    Article  Google Scholar 

  • Feizollah, A., Anuar, N. B., Salleh, R., & Wahab, A. W. A. (2015). A review on feature selection in mobile malware detection. Digital Investigation, 13, 22–37.

    Article  Google Scholar 

  • Firdaus, A., & Anuar, N. B. (2015). Root-exploit malware detection using static analysis and machine learning. In Proceedings of the fourth international conference on computer science & computational mathematics (ICCSCM 2015) (pp. 177–183). Langkawi, Malaysia.

  • Firdaus, A., Anuar, N. B., Karim, A., & Razak, M. F. A. (2017a). Discovering optimal features using static analysis and genetic search based method for android malware detection. Frontiers of Information Technology & Electronic Engineering, 19, 1–27.

    Google Scholar 

  • Firdaus, A., Anuar, N. B., Razak, M. F. A., Hashem, I. A. T., Bachok, S., & Sangaiah, A. K. (2018). Root exploit detection and features optimization: Mobile device and blockchain based medical data management. Journal of Medical Systems. https://doi.org/10.1007/s10916-018-0966-x.

  • Firdaus, A., Anuar, N. B., Razak, M. F. A., & Sangaiah, A. K. (2017b). Bio-inspired computational paradigm for feature investigation and malware detection: Interactive analytics. Multimedia Tools and Applications, 77(14), 17519–17555.

    Article  Google Scholar 

  • Garcia-Alfaro, J., Navarro-Arribas, G., Hartenstein, H., & Herrera-Joancomartí, J. (2017). Data privacy management, cryptocurrencies and blockchain technology (pp. 1–446).

  • Ghosh, M., Richardson, M., Ford, B., & Jansen, R. (2014). A TorPath to TorCoin: Proof-of-bandwidth altcoins for compensating relays. In 7th workshop on hot topics in privacy enhancing technologies (HotPETs) (pp. 1–13).

  • Glänzel, W., & Schubert, A. (2004). Analyzing scientific networks through co-authorship. Handbook of Quantitative Science and Technology Research (pp. 257–276). Dordrecht: Springer.

    Google Scholar 

  • Governatori, G., Idelberger, F., Milosevic, Z., Riveret, R., Sartor, G., & Xu, X. (2018). On legal contracts, imperative and declarative smart contracts, and blockchain systems. Artificial Intelligence and Law, 26(4), 377–409.

    Article  Google Scholar 

  • Gramoli, V. (2017). From blockchain consensus back to byzantine consensus. Future Generation Computer Systems (pp. 1–10).

  • Griggs, K. N., Ossipova, O., Kohlios, C. P., Baccarini, A. N., Howson, E. A., & Hayajneh, T. (2018). Healthcare blockchain system using smart contracts for secure automated remote patient monitoring. Journal of Medical Systems, 42(7), 130.

    Article  Google Scholar 

  • Gusson, C. (2018). Venezuelan Cryptocurrency Petro receives the Satoshi Nakamoto Prize in Russia (Online). Available at https://www.ccn.com/el-petro-the-venezuelan-cryptocurrency-receives-the-satoshi-nakamoto-prize-in-russia/. Accessed June 12 2018.

  • Han, R., Gramoli, V., & Xu, H. (2018). Evaluating blockchains for IoT. In 9th IFIP international conference on new technologies, mobility and security, NTMS (pp. 1–5). Paris, France.

  • Hazim, M., Anuar, N. B., Ab Razak, M. F., & Abdullah, N. A. (2018). Detecting opinion spams through supervised boosting approach. PLoS ONE, 13(6), 1–23.

    Article  Google Scholar 

  • Hellani, H., Samhat, A. E., Chamoun, M., El Ghor, H., & Serhrouchni, A. (2018). On blockchain technology: Overview of bitcoin and future insights. In IEEE international multidisciplinary conference on engineering technology (IMCET) (pp. 1–8).

  • Hughes, A., Park, A., Kietzmann, J., & Archer-Brown, C. (2019). Beyond bitcoin: What blockchain and distributed ledger technologies mean for firms. Business Horizons, 62, 1–9.

    Article  Google Scholar 

  • Husain, Z., Suliman, A., Salah, K., Abououf, M., & Alblooshi, M. (2018). Monetization of IoT data using smart contracts. IET Networks, 8(1), 32–37.

    Google Scholar 

  • Iefremova, O., Wais, K., & Kozak, M. (2018). Biographical articles in scientific literature: Analysis of articles indexed in web of science. Scientometrics, 117(3), 1695–1719.

    Article  Google Scholar 

  • Jennath, H. S., Adarsh, S., & Anoop, V. S. (2019). Distributed IoT and applications: A Survey. In Studies in computational intelligence (Vol. 771, pp. 333–341). Springer, Singapore.

  • Juhász, P. L., Stéger, J., Kondor, D., & Vattay, G. (2018). A Bayesian approach to identify bitcoin users. PLoS ONE, 13(12), 1–21.

    Article  Google Scholar 

  • Kim, S.-K., Kim, U.-M., & Huh, J.-H. (2019). A study on improvement of blockchain application to overcome vulnerability of IoT multiplatform security. Energies, 12(3), 402.

    Article  Google Scholar 

  • Koskinen, J., et al. (2008). How to use bibliometric methods in evaluation of scientific research? An example from finnish schizophrenia research. Nordic Journal of Psychiatry, 62(2), 136–143.

    Article  MathSciNet  Google Scholar 

  • Kshetri, N. (2017). Blockchain’s roles in strengthening cybersecurity and protecting privacy. Telecommunications Policy, 41(10), 1027–1038.

    Article  Google Scholar 

  • Kumar, S., & Kumar, S. (2008). Collaboration in research productivity in oil seed research institutes of India. In Fourth international conference on webometrics, informetrics and scientometrics & ninth COLLNET meeting Humboldt- Universitat zu Berlin, Institute for Library and Information Science (IBI) (pp. 1–18).

  • Kuo, T. T., Kim, H. E., & Ohno-Machado, L. (2017). Blockchain distributed ledger technologies for biomedical and health care applications. Journal of the American Medical Informatics Association, 24(6), 1211–1220.

    Article  Google Scholar 

  • Lamiri, A., Gueraoui, K., & Zeggwagh, G. (2019). Bitcoin difficulty, a security feature. In 2nd international conference on Europe Middle East and North Africa information systems and technologies to support learning (EMENA-ISTL), (Vol. 111, pp. 367–372). Fez, Morocco.

  • Lee, D. H. (2019). Predictive power of conference-related factors on citation rates of conference papers. Scientometrics, 118(1), 281–304.

    Article  Google Scholar 

  • Li, X., Jiang, P., Chen, T., Luo, X., & Wen, Q. (2017). A survey on the security of blockchain systems. Future Generation Computer Systems, 1–13.

  • Li, J., & Shang, Y. (2019). Research on a suitable blockchain for IoT platform. In Research on a suitable blockchain for IoT platform (pp. 1063–1072).

  • Liu, Y., Lu, Q., Xu, X., Zhu, L., & Yao, H. (2018). Applying design patterns in smart contracts a case study on a blockchain-based traceability. Lecture notes in computer science (including subseries lecture notes in artificial intelligence and lecture notes in bioinformatics) (Vol. 10974, pp. 92–106).

  • Liu, J., Tian, J., Kong, X., Lee, I., & Xia, F. (2018b). Two decades of information systems: A bibliometric review. Scientometrics, 118(2), 617–643.

    Article  Google Scholar 

  • Liu, B., Yu, X. L., Chen, S., Xu, X., & Zhu, L. (2017). Blockchain based data integrity service framework for IoT data. In 24th IEEE international conference on web services, (ICWS) (pp. 468–475). Honolulu, United States.

  • Liu, H., Zhang, Y., & Yang, T. (2018c). Blockchain-enabled security in electric vehicles cloud and edge computing. IEEE Network, 32(3), 78–83.

    Article  Google Scholar 

  • Lo, S. K., Xu, X., Chiam, Y. K., & Lu, Q. (2018). Evaluating suitability of applying blockchain. In Proceedings of the IEEE international conference on engineering of complex computer systems, (ICECCS) (pp. 158–161). Kyushu University, Fukuoka, Japan.

  • Loomes, D. E., & Van Zanten, S. V. (2013). Bibliometrics of the top 100 clinical articles in digestive disease. Gastroenterology, 144(4), 673–676.

    Article  Google Scholar 

  • Lopes, J., & Pereira, J. L. (2019). Blockchain technologies: Opportunities in Healthcare. In International conference on digital science (DSIC), (Vol. 850, pp. 435–442). Budva, Montenegro.

  • Maesa, D. D. F., Marino, A., & Ricci, L. (2019). The graph structure of bitcoin. In 7th international conference on complex networks and their applications, (COMPLEX NETWORKS) (pp. 547–558). Cambridge, United Kingdom.

  • Makhdoom, I., Abolhasan, M., Abbas, H., & Ni, W. (2019). Blockchain’s adoption in IoT: The challenges, and a way forward. Journal of Network and Computer Applications, 125, 251–279.

    Article  Google Scholar 

  • Mao, G., Zou, H., Chen, G., Du, H., & Zuo, J. (2015). Past, current and future of biomass energy research: A bibliometric analysis. Renewable and Sustainable Energy Reviews, 52, 1823–1833.

    Article  Google Scholar 

  • Margheri, A. (2018). Differentially private data sharing in a cloud federation with blockchain. IEEE Cloud Computing, 5(December), 69–79.

    Google Scholar 

  • Marsal-Llacuna, M. L. (2017). Future living framework: Is blockchain the next enabling network? Technological Forecasting and Social Change, 128, 226–234.

    Article  Google Scholar 

  • Memoria, F. (2019). No one knows what Venezuela’s Petro Cryptocurrency is Actually Worth (Online). Available at https://www.ccn.com/no-one-knows-what-venezuelas-petro-cryptocurrency-is-actually-worth. Accessed February 18, 2019.

  • Mendling, J., et al. (2018). Blockchains for business process management—challenges and opportunities. ACM Transaction on Management Information Systems, 9, 1–16.

    Article  Google Scholar 

  • Miau, S., & Yang, J. M. (2018). Bibliometrics-based evaluation of the Blockchain research trend: 2008–March 2017. Technology Analysis & Strategic Management, 30, 1029–1045.

    Article  Google Scholar 

  • Mingxiao, D., Xiaofeng, M., Zhe, Z., Xiangwei, W., & Qijun, C. (2017). A review on consensus algorithm of blockchain. In IEEE international conference on systems, man, and cybernetics (SMC) (pp. 2567–2572).

  • Mustaffa, Z., Sulaiman, M. H., & Kahar, M. N. M. (2015). LS-SVM hyper-parameters optimization based on GWO algorithm for time series forecasting. In 4th international conference on software engineering and computer systems, ICSECS 2015 (pp. 183–188). Virtuous Software Solutions for Big Data, Kuantan, Pahang.

  • Mustaffa, Z., & Yusof, Y. (2012). A hybridization of enhanced artificial bee colony-least squares support vector machines for price forecasting. Journal of Computer Science, 8(10), 1680–1690.

    Article  Google Scholar 

  • Oakleaf, M. (2009). Writing information literacy assessment plans: A guide to best practice. Communications in Information Literacy, 3(2), 80–90.

    Article  Google Scholar 

  • Parino, F., Beiró, M. G., & Gauvin, L. (2018). Analysis of the bitcoin blockchain: Socio-economic factors behind the adoption. EPJ Data Science, 7(1), 1–23.

    Article  Google Scholar 

  • Pass, R. N. (2019). Rafael N. Pass (Online). Available at https://www.engineering.cornell.edu/faculty-directory/rafael-n-pass. Accessed May 15, 2019.

  • Pass, R., & Shi, E. (2017). FruitChains: A fair blockchain Rafael. In Proceedings of the ACM symposium on principles of distributed computing (PODC) (pp. 315–324). DC, USA.

  • Pass, R., Shi, E. (2018). Thunderella: Blockchains with optimistic instant confirmation. Lecture notes in computer science (including subseries lecture notes in artificial intelligence and lecture notes in bioinformatics) (Vol. 10821, pp. 3–33).

  • Puthal, D., & Mohanty, S. P. (2019). Proof of authentication: IoT-friendly blockchains. IEEE Potentials, 38(1), 26–29.

    Article  Google Scholar 

  • Rahouma, K. H. (2017). Reviewing and applying security services with non-english letter coding to secure software applications in light of software trade-offs. International Journal of Software Engineering and Computer Systems (IJSECS), 3(February), 71–87.

    Article  Google Scholar 

  • Razak, M. F. A., Anuar, N. B., Othman, F., Firdaus, A., Afifi, F., & Salleh, R. (2017). Bio-inspired for features optimization and malware detection. Arabian Journal for Science and Engineering, 43(12), 6963–6979.

    Article  Google Scholar 

  • Razak, M. F. A., Anuar, N. B., Salleh, R., & Firdaus, A. (2016). The rise of ‘“malware”’: Bibliometric analysis of malware study. Journal of Network and Computer Applications, 75, 58–76.

    Article  Google Scholar 

  • Razak, M. F. A., Anuar, N. B., Salleh, R., Firdaus, A., Faiz, M., & Alamri, H. S. (2019). ‘Less give more’: Evaluate and zoning android applications. Measurement: Journal of the International Measurement Confederation, 133, 396–411.

    Article  Google Scholar 

  • Reyna, A., Martín, C., Chen, J., Soler, E., & Díaz, M. (2018). On blockchain and its integration with IoT. Challenges and opportunities. Future Generation Computer Systems, 88, 173–190.

    Article  Google Scholar 

  • Rimba, P., Binh, A., Ingo, T., Staples, M., Ponomarev, A., & Xu, X. (2018). Quantifying the cost of distrust : Comparing blockchain and cloud services for business process execution. Information Systems Frontiers, 1–19.

  • Rimba, P., Tran, A. B., Weber, I., Staples, M., Ponomarev, A., & Xu, X. (2017). Comparing blockchain and cloud services for business process execution. In IEEE international conference on software architecture (ICSA) (pp. 257–260). Sweden.

  • Roman, V., & Ordieres-Mere, J. (2019). IoT blockchain technologies for smart sensors based on raspberry pi. In IEEE 11th international conference on service-oriented computing and applications IoT (pp. 216–220). Paris, France.

  • Ryu, J. H., Sharma, P. K., Jo, J. H., & Park, J. H. (2019). A blockchain-based decentralized efficient investigation framework for IoT digital forensics. The Journal of Supercomputing, 1–16.

  • Smith, S. (2018). IoT connections to grow 140% to hit 50 billion by 2022, as edge computing accelerates RoI (Online). Available at https://www.juniperresearch.com/press/press-releases/iot-connections-to-grow-140-to-hit-50-billion. Accessed 6 Jan 2019.

  • Tahaei, H., Salleh, R., Razak, M. F. A., Ko, K., & Anuar, N. B. (2018). Cost effective network flow measurement for software defined networks: A distributed controller scenario. IEEE Access, 6, 5182–5198.

    Article  Google Scholar 

  • Tron Live, (2018). An easy to understand guide to PoW, PoS, DPoS, consensus mechanism and super representative (Online). Available at https://medium.com/tron-foundation/an-easy-to-understand-guide-to-pow-pos-dpos-consensus-mechanism-and-super-representative-eb1f5504a8e. Accessed 10 Dec 2018.

  • Vazirani, A., O’Donoghue, O., Brindley, D., & Meinert, E. (2018). Implementing blockchains for efficient healthcare: A systematic review. Journal of Medical Internet Research, 21(2), 1–12.

    Google Scholar 

  • Wang, B., Chen, S., Yao, L., Liu, B., Xu, X., & Zhu, L. (2018). A simulation approach for studying behavior and quality of blockchain networks. Lecture notes in computer science (including subseries lecture notes in artificial intelligence and lecture notes in bioinformatics) (Vol. 10974, pp. 18–31).

  • Weber, I., Xu, X., Riveret, R., Governatori, G., Ponomarev, A., & Mendling, J. (2016). Untrusted business process monitoring and execution using blockchain. Lecture notes in computer science (including subseries lecture notes in artificial intelligence and lecture notes in bioinformatics) (Vol. 9850, pp. 329–347).

  • Wu, X., Chen, X., Zhan, F. B., & Hong, S. (2015). Global research trends in landslides during 1991–2014: A bibliometric analysis. Landslides, 12(6), 1215–1226.

    Article  Google Scholar 

  • Wu, D., Liu, X. D., Yan, X. B., Peng, R., & Li, G. (2019). Equilibrium analysis of bitcoin block withholding attack: A generalized model. Reliability Engineering and System Safety, 185, 318–328.

    Article  Google Scholar 

  • Xu, X., Pautasso, C., Gramoli, V., Ponomarev, A., & Chen, S. (2016). The blockchain as a software connector. In 13th working IEEE/IFIP conference on software architecture (WICSA) (pp. 182–191). Venice, Italy.

  • Yuan, R., Bin Xia, Y., Chen, H. B., Zang, B. Y., & Xie, J. (2018a). ShadowEth: Private smart contract on public blockchain. Journal of Computer Science and Technology, 33(3), 542–556.

    Article  Google Scholar 

  • Yuan, B., Jin, H., Zou, D., Yang, L. T., & Yu, S. (2018b). A practical byzantine based approach for faulty switch tolerance in software-defined networks. IEEE Transactions on Network and Service Management, 15(2), 825–839.

    Article  Google Scholar 

Download references

Acknowledgements

This work was funded by Universiti Malaysia Pahang, under the Grant Faculty of Computer Systems and Software Engineering (FSK1000), RDU180361.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Mohd Faizal Ab Razak.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Firdaus, A., Razak, M.F.A., Feizollah, A. et al. The rise of “blockchain”: bibliometric analysis of blockchain study. Scientometrics 120, 1289–1331 (2019). https://doi.org/10.1007/s11192-019-03170-4

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11192-019-03170-4

Keywords

Navigation