ECE Oral Comprehensive Exam for Doctoral Candidacy By: Chencheng Zhou
When: Thursday,
January 7, 2021
8:00 AM
-
10:00 AM
Where: > See description for location
Cost: Free
Description: Topic: Dependability and Resilience for Blockchain-Based Systems
Zoom Teleconference: https://umassd.zoom.us/j/96015890363
Abstract:
The blockchain technology has immense potential in many different applications, including but not limited to cryptocurrencies, financial services, smart contracts, supply chains, healthcare services, and energy trading. Due to the critical nature of these applications, it is pivotal to model and evaluate dependability of the blockchain-based systems, contributing to their reliable and robust design and operation.
In this dissertation proposal, potential risks to the blockchain-based systems are examined. Impacts of critical parameters like block size, block interval, stale block rate on the system performance are investigated through case studies. We then model and analyze the dependability of Bitcoin, a peer-to-peer cryptocurrency system built upon the blockchain technology that enables an individual user to trade freely without the involvement of banks or any other types of intermediate agents. However, a node in the Bitcoin is vulnerable to the Eclipse attack, which aims to monopolize the information flow of the victim node. A continuous time Markov chain-based approach is proposed to model the Eclipse attack behavior and possible mitigation activities that may prevent the attack from being successful during the attack process. Effects of several model parameters (related to the miner’s habits in system protection, restart, and mining frequency) on the dependability of a Bitcoin node are demonstrated through numerical examples. As the continuous time Markov chain-based approach is limited to the exponential state transition time distribution, we further propose a semi-Markov process-based approach to determine the steady-state dependability of Bitcoin nodes subject to arbitrary types of state transition time distribution. We also examine the influence of time to restart the Bitcoin software and time to detect and delete the malicious message on the Bitcoin node dependability.
Future research directions on the probabilistic modeling and analysis of Bitcoin network-level dependability, and design and analysis of resilience strategies to mitigate impacts of reliability and security risks on the blockchain-based systems are outlined.
NOTE: All ECE Graduate Students are ENCOURAGED to attend.
All interested parties are invited to attend. Open to the public.
Advisor: Dr. Liudong Xing
Committee Members: Dr. Honggang Wang, Department of Electrical& Computer Engineering, UMASS Dartmouth; Dr. Yuzhu Li, Department of Decision and Information Sciences, UMASS Dartmouth; Dr. Jun Guo, College of Software, Northeastern University, China
*For further information, please contact Dr. Liudong Xing via email at lxing@umassd.edu.
Zoom Teleconference: https://umassd.zoom.us/j/96015890363
Abstract:
The blockchain technology has immense potential in many different applications, including but not limited to cryptocurrencies, financial services, smart contracts, supply chains, healthcare services, and energy trading. Due to the critical nature of these applications, it is pivotal to model and evaluate dependability of the blockchain-based systems, contributing to their reliable and robust design and operation.
In this dissertation proposal, potential risks to the blockchain-based systems are examined. Impacts of critical parameters like block size, block interval, stale block rate on the system performance are investigated through case studies. We then model and analyze the dependability of Bitcoin, a peer-to-peer cryptocurrency system built upon the blockchain technology that enables an individual user to trade freely without the involvement of banks or any other types of intermediate agents. However, a node in the Bitcoin is vulnerable to the Eclipse attack, which aims to monopolize the information flow of the victim node. A continuous time Markov chain-based approach is proposed to model the Eclipse attack behavior and possible mitigation activities that may prevent the attack from being successful during the attack process. Effects of several model parameters (related to the miner’s habits in system protection, restart, and mining frequency) on the dependability of a Bitcoin node are demonstrated through numerical examples. As the continuous time Markov chain-based approach is limited to the exponential state transition time distribution, we further propose a semi-Markov process-based approach to determine the steady-state dependability of Bitcoin nodes subject to arbitrary types of state transition time distribution. We also examine the influence of time to restart the Bitcoin software and time to detect and delete the malicious message on the Bitcoin node dependability.
Future research directions on the probabilistic modeling and analysis of Bitcoin network-level dependability, and design and analysis of resilience strategies to mitigate impacts of reliability and security risks on the blockchain-based systems are outlined.
NOTE: All ECE Graduate Students are ENCOURAGED to attend.
All interested parties are invited to attend. Open to the public.
Advisor: Dr. Liudong Xing
Committee Members: Dr. Honggang Wang, Department of Electrical& Computer Engineering, UMASS Dartmouth; Dr. Yuzhu Li, Department of Decision and Information Sciences, UMASS Dartmouth; Dr. Jun Guo, College of Software, Northeastern University, China
*For further information, please contact Dr. Liudong Xing via email at lxing@umassd.edu.
Contact:
ECE: Electrical & Computer Engineering Department 508.999.9164 http://www.umassd.edu/engineering/ece/
Topical Areas: General Public, University Community, College of Engineering, Electrical and Computer Engineering