To prevent 51% attacks, there is a need to understand some things. In a general classification, the key factors for the survival of blockchain networks include the following:
- Blockchain Technology
- Social Engineering
- Blockchain Management
In a blockchain network, if any of these things suffer from defects, it can lead to the vulnerability of that network against 51% attacks. Of course, in most cases, the presence of defects in all factors provides a suitable situation for an attack. In this notebook, the degree of vulnerability of blockchain networks has been examined. By presenting the regression model, the probability of being attacked by a blockchain network is checked. However, our study has flaws in this modeling that will definitely affect its results:
- Low number of data (The number of attacks is small)
- There is not enough information in this field
- This is a suggested model, not an optimal model
Notice: This notebook necessarily presents a basic idea for identifying blockchains at risk, and its modeling lacks compliance with a series of general principles. For example, the dataset used in this model has less than 20 rows, which practically disqualifies it. Such amount of data lacks any value for processing or modeling.
It is noteworthy that as this dataset becomes more complete over time, better modeling will be done.