Tuesday, 23 March 2021

Engineering Blockchain Applications


 

Course Description

Blockchain technology is revolutionizing digitalization prospects for many industries and emerging as an exciting and rapidly growing field. By detailing the architecture of the technology, this course ensures that learners will be well versed in blockchain fundamentals. At the same time, it is designed to put learners on the leading edge by presenting the abstract nature of blockchain technology and emphasizing its broad applicability. Topics include the mathematical and cryptographic underpinnings of the technology, as well as mining, consensus protocols, networking, and decentralized governance.

 

Learning Outcomes

By completing this course you will be able to:

 

·         Apply the Elliptic Curve Digital Signature Algorithm to identity management and computer security

·         Determine the validity of chains given general consensus rules

·         Determine whether changes in consensus rules for a Nakamoto network will result in a successful protocol fork

·         Compare proof-of-work secured blockchains’ security to alternate security methods

·         Evaluate an optimal mix of network design and operational parameters to ensure network scalability and throughput

·         Evaluate the trade-off between security and computational complexity

·         Use Hyperledger Fabric to build a custom network configuration

·         Use Hyperledger Composer to build a business application

·         Create your own decentralized blockchain network

·         Change/add logic to a code base of a dash blockchain (forked from bitcoin)

 

Estimated Workload/Time Commitment

Average of 15-20 hours per week

 

Required Prior Knowledge and Skills

        Algebra

        Programming in Python and C++

 

Recommended Prior Knowledge and Skills

        Programming in node.js, Docker, Unix

 

Technology Requirements


 

Hardware

Standard with recent major OS NOTE: Linux recommended.

Software and Other

Standard

 

 

Textbook

There is no required textbook for this course; however, the course creators recommend the following text:

 

Bitcoin and Cryptocurrency TechnologiesA Comprehensive Introduction, Arvind Narayanan, Joseph Bonneau, Edward Felten, Andrew Miller & Steven Goldfeder (2016)

 

Required course readings are provided within or accessible through the course. You will find them in the week each one is assigned.

 

 

Course Content

 

Instruction                                                      Assessments


Video lectures

Other video or media Readings

Virtual office hours Live events


Practice quizzes and assignments (auto- graded)

Graded assignments (instructor graded) Individual projects (instructor-graded) Final exam (proctored, auto-graded


 

 

 

 

Details of the main instructional and assessment elements this course comprises follow:

 

Lecture videos. In each module the concepts you need to know will be presented through a collection of short video lectures. You may stream these videos for playback within the browser by clicking on their titles or download the videos. You may also download the slides that are used in the videos. The lecture slides for each module are provided in a reading preceding the introduction to the first lesson in each module. (NOTE: The exception is Module 1, where the slides are in the introduction to the second lesson.)

Graded Quizzes. Each unit includes one graded quiz (“Unit Quiz”). There is no time limit on how long you take to complete each attempt at the quiz. Each attempt may


present a different selection of questions to you. Your highest score will be used when calculating your final grade in the class.

Graded Discussion. Select units include one or more graded discussion prompts. You will find these asssignments among units’ other content. Each prompt provides a space for you to respond. After responding, you can see and comment on your peers' responses. All prompts and responses are also accessible from the general discussion forum and the module discussion forum.

Readings. Modules may include suggested readings or other recommended resources. They are supplementary materials selected to help you better understand or further explore the course topics.

Proctored Exams: You will have one (1) proctored exam, a final. ProctorU is an online proctoring service that allows students to take exams online while ensuring the integrity of the exam for the institution. Additional information and instructions are provided in Week 1 of the course (also the MCS Onboarding Course).

Course projects: This course includes two major projects, and both are to be completed individually (i.e., they are not team projects).

 

 

Course Grade Breakdown


NOTICE: The projects for this course are eligible, together, for inclusion in your MCS Portfolio. You may submit your portfolio report for consideration by the course instructor within the course at its conclusion.

 

Grade Scale

 

NOTE: You must earn a cumulative grade of 70% to earn a “C” in this course. Grades in this course will not include pluses


 














Key Course Dates

Class begins: January 7, 2019

Holiday: January 21, 2019: Martin Luther King Jr. Day (university closed)

Project 1: February 1, 2019

Project 2: February 22, 2019

Final exam and class ends: February 26, 2019

Grades due: March 3, 2019

 

Important Notice: Unless otherwise noted, all graded work is due at 11:59 p.m. on the Friday of the week for which it is assigned. Late penalties will be applied for work received or completed after the scheduled due date and time:

 

·         Graded assignments: One-time 20% penalty

·         Graded quizzes: One-time 15% penalty

 

Live Events - Weekly (meet with the course instructor and your classmates to learn more about course topics and discuss assignments):


 

Tuesday from 10:00-1100 a.m. Arizona time (check the Live Events page in the course for your local time and access details)

 

Note: These events will be recorded and uploaded to the course.

 

ATTENTION: The live event for the week of 1/21/19 will be held on Wednesday (not Tuesday) from 10:00-11:00 a.m. Arizona time. The Zoom link is unchanged.

 

Virtual Office Hours - Weekly (another chance to get your questions answered from the course instructor):

 

Wednesday from 1:00-200 p.m. Arizona time (check the Live Events page in the course for your local time and access details)

Course Outline

 

Week/Unit 1: The Blockchain’s Abstractions and Applications

Module 1: Introduction to Blockchain Technology Module 2: Benefits of Blockchain Technology Module 3: Blockchain Applications

Module 4: The Blockchain Ecosystem

 

Week/Unit 2: Hash Functions

Module 1: Introduction to Hash Functions


Module 2: Hash Functions for Password Handling Module 3: Application-Appropriate Hash Function Module 4: Merkle Trees and Merkle Proofs

 

Week/Unit 3: Cryptographic and Mathematical Foundations of the Blockchain

Module 1: Elliptical Curves Digital Signatures Module 2: Private Key Handling

Module 3: Other Mathematical Concepts

 

Week/Unit 4: Transactions on the Blockchain

Module 1: Introduction to Transactions Module 2: Scripts

Module 3: State Channels Module 4: Wallets

 

Week/Unit 5: Mining

Module 1: Introduction to Mining Module 2: Mining and Network Attacks Module 3: Mining Pools

Module 4: Mining Considerations

 

Week/Unit 6: Blockchain Consensus

Module 1: Introduction to Blockchain Consensus Module 2: Consensus Algorithms

 

Week/Unit 7: Peer-to-Peer Networks

Module 1: Introduction to Computer Network Architecture Module 2: Nodes

Module 3: Block Propagation Module 4: SPV Clients

 

Week/Unit 8: Governance

Module 1: Decision-Making on Decentralized Networks Module 2: Hard and Soft Forks

Module 3: Network Signaling

Module 4: Two-Tiered Network Governance

 

 

Policies

All ASU and Coursera policies will be enforced during this course. For policy details, please consult the MCS Graduate Handbook 2018 •- 2019 and/or the MCS Onboarding Course.

 

 

Course Creators


 

The following faculty members created this course.

 

Dragan Boscovic



Dragan Boscovic is a research professor in the School of Computing, Informatics, & Decision Systems Engineering (CIDSE), as well as Technical Director of CIDSE’s Center for Assured and Scalable Data Engineering and Distinguished Visiting Scholar, mediaX, at Stanford University. Dr. Boscovic also leads ASU’s Blockchain Research Lab, where his team’s mission is to advance the research and development of blockchain-based technologies for use in business, finance, economics, mathematics, computer science, and all other areas of potential impact.

 

He holds a Ph.D. in EE and CS, Numerical Electromagnetic Modeling from University of Bath, United Kingdom (1991) and a Magistar in EE, eq. Ph.D., Microwave and Optoelectronics from

University of Belgrade, Serbia (1988). He has 25 years of high tech experience acquired in an international set up (i.e. UK, France, China, USA) and is uniquely positioned to help data-driven technical advances within today’s global data-intensive technology arena. He is a lateral thinker with broad exposure to a wide range of scientific methods and business practices and has a proven track record in conceiving strategies and managing development, investment and innovation efforts as related to advanced data analysis services, user experience, and mobile and IoT solutions and platforms.

 

Darren Tapp


 



 

Darren Tapp was involved in the development of Bitcoin and is now a researcher on the digital cash (cryptocurrency) development team at dash.org, a non-profit blockchain technology startup. He earned his doctorate in mathematics from Purdue University in 2007 and holds both a bachelor’s degree in physics and mathematics and a master’s degree in mathematics from the University of Kentucky. Most recently he has taught both on-ground and online at schools including Southern New Hampshire University, NHTI - Concord's Community College, and Hesser College. He lives in New Hampshire, where he volunteers promoting STEM subjects to high-school-aged members of the Big Fish Learning Community.

Acknowledgements

The faculty wish to thank the following students and blockchain community members for their contributions to this course:

 

Jeremy Liu Nakul Chawla Raj Sadaye

 

About ASU

 

Established in Tempe in 1885, Arizona State University (ASU) has developed a new model for the American Research University, creating an institution that is committed to access, excellence and impact.

 

As the prototype for a New American University, ASU pursues research that contributes to the public good, and ASU assumes major responsibility for the economic, social and cultural vitality of the communities that surround it. Recognizing the university’s groundbreaking initiatives, partnerships, programs and research, U.S. News and World Report has named ASU as the most innovative university all three years it has had the category.


 

The innovation ranking is due at least in part to a more than 80 percent improvement in ASU’s graduation rate in the past 15 years, the fact that ASU is the fastest-growing research university in the country and the emphasis on inclusion and student success that has led to more than 50 percent of the school’s in-state freshman coming from minority backgrounds.

 

 

About Ira A. Fulton Schools of Engineering

 

Structured around grand challenges and improving the quality of life on a global scale, the Ira A. Fulton Schools of Engineering at Arizona State University integrates traditionally separate disciplines and supports collaborative research in the multidisciplinary areas of biological and health systems; sustainable engineering and the built environment; matter, transport and energy; and computing and decision systems. As the largest engineering program in the United States, students can pursue their educational and career goals through 25 undergraduate degrees or 39 graduate programs and rich experiential education offerings. The Fulton Schools are dedicated to engineering programs that combine a strong core foundation with top faculty and a reputation for graduating students who are aggressively recruited by top companies or become superior candidates for graduate studies in medicine, law, engineering and science.

 

 

About the School of Computing, Informatics, & Decision Systems Engineering

 

The School of Computing, Informatics, and Decision Systems Engineering advances developments and innovation in artificial intelligence, big data, cybersecurity and digital forensics, and software engineering. Our faculty are winning prestigious honors in professional societies, resulting in leadership of renowned research centers in homeland security operational efficiency, data engineering, and cybersecurity and digital forensics. The school’s rapid growth of student enrollment isn’t limited to the number of students at ASU’s Tempe and Polytechnic campuses as it continues to lead in online education. In addition to the Online Master of Computer Science, the school also offers an Online Bachelor of Science in Software Engineering, and the first four-year, completely online Bachelor of Science in Engineering program in engineering management.


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