# Nik Defense: An Artificial Intelligence Based Defense Mechanism against Selfish Mining in Bitcoin

arXiv: https://arxiv.org/abs/2301.11463 · HTML: https://mlsanity.com/paper/2301.11463/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 12 of its 44 references that are in the map.
- First posted on arXiv 26 Jan 2023.

## Builds on (most cited first, 12 of 12)

- [A Survey on Consensus Mechanisms and Mining Strategy Management in Blockchain Networks](https://mlsanity.com/paper/1805.02707/) (2018)
- [Optimal Selfish Mining Strategies in Bitcoin](https://mlsanity.com/paper/1507.06183/) (2015)
- [Transaction Fee Mechanism Design](https://mlsanity.com/paper/2106.01340/) (2021)
- [When Blockchain Meets AI: Optimal Mining Strategy Achieved By Machine Learning](https://mlsanity.com/paper/1911.12942/) (2019)
- [Majority is not Enough: Bitcoin Mining is Vulnerable](https://mlsanity.com/paper/1311.0243/) (2013)
- [The Miner's Dilemma](https://mlsanity.com/paper/1411.7099/) (2014)
- [Countering Selfish Mining in Blockchains](https://mlsanity.com/paper/1811.09943/) (2018)
- [Theoretical Bitcoin Attacks with less than Half of the Computational Power (draft)](https://mlsanity.com/paper/1312.7013/) (2013)
- [On Subversive Miner Strategies and Block Withholding Attack in Bitcoin Digital Currency](https://mlsanity.com/paper/1402.1718/) (2014)
- [A Deep Dive into Blockchain Selfish Mining](https://mlsanity.com/paper/1811.08263/) (2018)
- [BitcoinF: Achieving Fairness for Bitcoin in Transaction-Fee-Only Model](https://mlsanity.com/paper/2003.00801/) (2020)
- [Analysis of Difficulty Control in Bitcoin and Proof-of-Work Blockchains](https://mlsanity.com/paper/1812.10792/) (2018)

## Built on by (most cited first, 2 of 2)

- [VDHLA: Variable Depth Hybrid Learning Automaton and Its Application to Defense Against the Selfish Mining Attack in Bitcoin](https://mlsanity.com/paper/2302.12096/) (2023)
- [New intelligent defense systems to reduce the risks of Selfish Mining and Double-Spending attacks using Learning Automata](https://mlsanity.com/paper/2307.00529/) (2023)

## Abstract (arXiv)

The Bitcoin cryptocurrency has received much attention recently. In the network of Bitcoin, transactions are recorded in a ledger. In this network, the process of recording transactions depends on some nodes called miners that execute a protocol known as mining protocol. One of the significant aspects of mining protocol is incentive compatibility. However, literature has shown that Bitcoin mining's protocol is not incentive-compatible. Some nodes with high computational power can obtain more revenue than their fair share by adopting a type of attack called the selfish mining attack. In this paper, we propose an artificial intelligence-based defense against selfish mining attacks by applying the theory of learning automata. The proposed defense mechanism ignores private blocks by assigning weight based on block discovery time and changes current Bitcoin's fork resolving policy by evaluating branches' height difference in a self-adaptive manner utilizing learning automata. To the best of our knowledge, the proposed protocol is the literature's first learning-based defense mechanism. Simulation results have shown the superiority of the proposed mechanism against tie-breaking mechanism, which is a well-known defense. The simulation results have shown that the suggested defense mechanism increases the profit threshold up to 40% and decreases the revenue of selfish attackers.