Week7-discussion-data science & big data analy

Category: Information System

Course: Data Science & Big Data Analy

LATE SUBMISSION WILL NOT BE ACCEPTED BY PROF.

Due Date – 2 days

Discussion Question:    

Tokenization  

This week we explored the concept of Tokenization.  Three important  protocols discussed were Secure Multi-Party Computation (SMPC),  Policy-Backed Token (PBT) and Open Asset Protocol (OAP).  Compare and  contrast these three protocols and explain which industries can benefit  the most from each of these protocols. 

Prof. Guidelines 

  • Provide extensive additional information on the topic
  • Explain, define, or analyze the topic in detail
  • Share an applicable personal experience
  • Provide an outside source (for example, an article from the     University Library) that applies to the topic, along with additional     information about the topic or the source (please cite properly in   APA)
  • At least one scholarly source should be used in the initial     discussion thread. Be sure to use information from your readings and     other sources from the UC Library. Use proper citations and  references    in your post.

Reading Assignments 

X. Li, X. Wu, X. Pei and Z. Yao, “Tokenization: Open Asset Protocol   on Blockchain,” 2019 IEEE 2nd International Conference on Information   and Computer Technologies (ICICT), Kahului, HI, USA, 2019, pp. 204-209.   doi: 10.1109/INFOCT.2019.8711021 http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8711021&isnumber=8710850 

S. Sayadi, S. Ben Rejeb and Z. Choukair, “Blockchain Challenges and   Security Schemes: A Survey,” 2018 Seventh International Conference on   Communications and Networking (ComNet), Hammamet, Tunisia, 2018, pp.   1-7.  doi: 10.1109/COMNET.2018.8621944 http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8621944&isnumber=8621920 

A. Ali, S. Latif, J. Qadir, S. Kanhere, J. Singh, “Blockchain and   the Furture of the Internet: A Comprehensive Review”, arxiv.org, https://arxiv.org/pdf/1904.00733v1.pdf?

Books and Resources Required Text

Eyupoglu, C. (2019). Big Data in Cloud Computing and Internet of Things. 2019     3rd International Symposium on Multidisciplinary Studies and    Innovative  Technologies (ISMSIT), Multidisciplinary Studies and    Innovative  Technologies (ISMSIT), 2019 3rd International Symposium On, 1–5. https://doi.org/10.1109/ISMSIT.2019.8932815

L. Zhao, Y. Huang, Y. Wang and J. Liu, “Analysis on the Demand of Top     Talent Introduction in Big Data and Cloud Computing Field in China     Based on 3-F Method,” 2017 Portland International Conference on     Management of Engineering and Technology (PICMET), Portland, OR,   2017,    pp. 1-3. https://doi.org/10.23919/PICMET.2017.8125463

Saiki, S., Fukuyasu, N., Ichikawa, K., Kanda, T., Nakamura, M.,     Matsumoto, S., Yoshida, S., & Kusumoto, S. (2018). A Study of     Practical Education Program on AI, Big Data, and Cloud Computing    through  Development of Automatic Ordering System. 2018 IEEE    International  Conference on Big Data, Cloud Computing, Data Science    & Engineering  (BCD), Big Data, Cloud Computing, Data Science  &   Engineering (BCD),  2018 IEEE International Conference on, BCD, 31–36. https://doi.org/10.1109/BCD2018.2018.00013

Psomakelis, E., Aisopos, F., Litke, A., Tserpes, K., Kardara, M., & Campo, P. M. (2016). Big     IoT and social networking data for smart cities: Algorithmic     improvements on Big Data Analysis in the context of RADICAL city     applications.

Liao, C.-H., & Chen, M.-Y. (2019). Building social computing     system in big data: From the perspective of social network analysis. Computers in Human Behavior, 101, 457–465. https://doi.org/10.1016/j.chb.2018.09.040 

“APA Format”

 https://academicwriter.apa.org/6/  

“NO PLAGIARISM” 

Plagiarism includes copying and pasting material     from the internet into assignments without properly citing the source     of the material.  

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