Blockchain

Achieving a consensus among a large number of nodes has always been a challenge for any decentralized system. Consensus algorithms are the building blocks for any decentralized network that is susceptible to malicious activities from authorized and unauthorized nodes. Proof-of-Work is one of the first modern approaches to achieve at least a 51% consensus, and ever since many new consensus algorithms have been introduced with different approaches of consensus achievement. These decentralized systems, also called blockchain systems, have been implemented in many applications such as supply chains, medical industry, and authentication. However, it is mostly used as a cryptocurrency foundation for token exchange. For these systems to operate properly, they are required to be robust, scalable, and secure. This dissertation provides a different approach of using consensus algorithms for allowing information sharing among nodes in a secured fashion while maintaining the security and immutability of the consensus algorithm. The consensus algorithm proposed in this dissertation utilizes a trust parameter to enforce cooperation, i.e., a trust value is assigned to each node and it is monitored to prevent malicious activities over time. This dissertation also proposes a new solution, named localized consensus, as a method that allows nodes in small groups to achieve consensus on information that is only relevant to that small group of nodes, thus reducing the bandwidth of the system. The proposed models can be practical solutions for immense and highly dynamic environments with validation through trust and reputation values. Application for such localized consensus can be communication among autonomous vehicles where traffic data is relevant to only a small group of vehicles and not the entirety of the system.

In this research, a new reputation-based model is utilized to disincentivize collusion
of defenders and attackers in Software Defined Networks (SDN), and also, to disincentivize
dishonest mining strategies in Blockchain. In the context of SDN, the model uses the
reputation values assigned to each entity to disincentivize collusion with an attacker. Our
analysis shows that not-colluding actions become Nash Equilibrium using the reputationbased
model within a repeated game setting. In the context of Blockchain and mining,
we illustrate that by using the same socio-rational model, miners not only are incentivized
to conduct honest mining but also disincentivized to commit to any malicious activities
against other mining pools. We therefore show that honest mining strategies become Nash
Equilibrium in our setting.
This thesis is laid out in the following manner. In chapter 2 an introduction to
game theory is provided followed by a survey of previous works in game theoretic network
security, in chapter 3 a new reputation-based model is introduced to be used within the
context of a Software Defined Network (SDN), in chapter 4 a reputation-based solution
concept is introduced to force cooperation by each mining entity in Blockchain, and finally,
in chapter 5, the concluding remarks and future works are presented.