This article presents an automated framework based on Markov decision processes (MDP) to analyze selfish mining attacks on blockchains. The approach formalizes selfish mining strategies, allows flexible parameter tuning, and provides formal correctness guarantees that facilitate reproducible audits and rigorous analysis.
The model offers a clear advantage by deriving a provable lower bound on adversarial revenue, helping to quantify the worst-case scenario an attacker can achieve under the considered constraints. However, there are inherent limits: the analysis is restricted to a subclass of attacks involving bounded and disjoint forks, meaning it does not cover more complex strategies or chained and overlapping forks that some advanced attackers could employ.
From an automated detection perspective, these restrictions imply that systems based solely on this framework might not identify unmodeled variants of selfish mining. Overcoming these limitations requires combining the MDP approach with complementary techniques such as supervised and unsupervised machine learning, blockchain time-series analysis, and large-scale simulations that consider real network topologies and latencies.
At Q2BSTUDIO, we apply this type of hybrid solution to offer products and services that enhance the security and resilience of blockchain platforms. Our custom software and application development team integrates formal models with artificial intelligence and cybersecurity tools to design more robust detection and mitigation systems. We can adapt MDP frameworks to production architectures and expand analytical scope with deep learning models and AI agents.
Our services include custom software and custom application development, integration with AWS and Azure cloud services, and business intelligence services such as custom Power BI implementations. We design secure and scalable data pipelines that connect blockchain telemetry with dashboards and actionable alerts, leveraging artificial intelligence to improve detection and response.
If your goal is to protect infrastructures against selfish mining attacks or expand monitoring capabilities with formal techniques and machine learning, Q2BSTUDIO offers consulting, development, and deployment. We are specialists in AI for businesses and AI agents that automate research and response tasks, and in cybersecurity solutions tailored to distributed environments. Contact us to design a custom strategy that combines academic rigor with production engineering.
