Biblio

Blockchain, the technology behind the popular Bitcoin, is considered a "security by design" system as it is meant to create security among a group of distrustful parties yet without a central trusted authority. The security of blockchain relies on the premise of honest-majority, namely, the blockchain system is assumed to be secure as long as the majority of consensus voting power is honest. And in the case of proof-of-work (PoW) blockchain, adversaries cannot control more than 50% of the network's gross computing power. However, this 50% threshold is based on the analysis of computing power only, with implicit and idealistic assumptions on the network and node behavior. Recent researches have alluded that factors such as network connectivity, presence of blockchain forks, and mining strategy could undermine the consensus security assured by the honest-majority, but neither concrete analysis nor quantitative evaluation is provided. In this paper we fill the gap by proposing an analytical model to assess the impact of network connectivity on the consensus security of PoW blockchain under different adversary models. We apply our analytical model to two adversarial scenarios: 1) honest-but-potentially-colluding, 2) selfish mining. For each scenario, we quantify the communication capability of nodes involved in a fork race and estimate the adversary's mining revenue and its impact on security properties of the consensus protocol. Simulation results validated our analysis. Our modeling and analysis provide a paradigm for assessing the security impact of various factors in a distributed consensus system.

The consistency checking of network security policy is an important issue of network security field, but current studies lack of overall security strategy modeling and entire network checking. In order to check the consistency of policy in distributed network system, a security policy model is proposed based on network topology, which checks conflicts of security policies for all communication paths in the network. First, the model uniformly describes network devices, domains and links, abstracts the network topology as an undirected graph, and formats the ACL (Access Control List) rules into quintuples. Then, based on the undirected graph, the model searches all possible paths between all domains in the topology, and checks the quintuple consistency by using a classifying algorithm. The experiments in campus network demonstrate that this model can effectively detect the conflicts of policy globally in the distributed network and ensure the consistency of the network security policies.