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Robustness of Proof of Team Sprint (PoTS) Against Attacks: A Simulation-Based Analysis

Naoki Yonezawa

TL;DR

The paper tackles the problem of achieving robust, energy-efficient consensus in blockchain by introducing Proof of Team Sprint (PoTS), a team-based scheme where participants are randomly reassigned into teams to generate blocks. A simulation framework analyzes how attacker strength ($\alpha$) and team size ($N$) affect attacker win rates, computation time, and the longest consecutive attacker streak, and it defines Normalized Computation Efficiency ($NCE$) as $NCE(N)=\dfrac{T_1}{T_N}$. Key findings show attacker success probability declines exponentially with increasing $N$, achieving negligible levels for moderate $\alpha$ when $N$ is large, while $NCE$ improves with team size albeit sublinearly due to variability in node execution times $\gamma_i$. These results demonstrate that PoTS offers a scalable, secure alternative to PoW/PoS by leveraging randomized team formation and synchronization to suppress adversarial dominance without sacrificing efficiency.

Abstract

This study evaluates the robustness of Proof of Team Sprint (PoTS) against adversarial attacks through simulations, focusing on the attacker win rate and computational efficiency under varying team sizes (\( N \)) and attacker ratios (\( α\)). Our results demonstrate that PoTS effectively reduces an attacker's ability to dominate the consensus process. For instance, when \( α= 0.5 \), the attacker win rate decreases from 50.7\% at \( N = 1 \) to below 0.4\% at \( N = 8 \), effectively neutralizing adversarial influence. Similarly, at \( α= 0.8 \), the attacker win rate drops from 80.47\% at \( N = 1 \) to only 2.79\% at \( N = 16 \). In addition to its strong security properties, PoTS maintains high computational efficiency. We introduce the concept of Normalized Computation Efficiency (NCE) to quantify this efficiency gain, showing that PoTS significantly improves resource utilization as team size increases. The results indicate that as \( N \) grows, PoTS not only enhances security but also achieves better computational efficiency due to the averaging effects of execution time variations. These findings highlight PoTS as a promising alternative to traditional consensus mechanisms, offering both robust security and efficient resource utilization. By leveraging team-based block generation and randomized participant reassignment, PoTS provides a scalable and resilient approach to decentralized consensus.

Robustness of Proof of Team Sprint (PoTS) Against Attacks: A Simulation-Based Analysis

TL;DR

The paper tackles the problem of achieving robust, energy-efficient consensus in blockchain by introducing Proof of Team Sprint (PoTS), a team-based scheme where participants are randomly reassigned into teams to generate blocks. A simulation framework analyzes how attacker strength () and team size () affect attacker win rates, computation time, and the longest consecutive attacker streak, and it defines Normalized Computation Efficiency () as . Key findings show attacker success probability declines exponentially with increasing , achieving negligible levels for moderate when is large, while improves with team size albeit sublinearly due to variability in node execution times . These results demonstrate that PoTS offers a scalable, secure alternative to PoW/PoS by leveraging randomized team formation and synchronization to suppress adversarial dominance without sacrificing efficiency.

Abstract

This study evaluates the robustness of Proof of Team Sprint (PoTS) against adversarial attacks through simulations, focusing on the attacker win rate and computational efficiency under varying team sizes () and attacker ratios (). Our results demonstrate that PoTS effectively reduces an attacker's ability to dominate the consensus process. For instance, when , the attacker win rate decreases from 50.7\% at to below 0.4\% at , effectively neutralizing adversarial influence. Similarly, at , the attacker win rate drops from 80.47\% at to only 2.79\% at . In addition to its strong security properties, PoTS maintains high computational efficiency. We introduce the concept of Normalized Computation Efficiency (NCE) to quantify this efficiency gain, showing that PoTS significantly improves resource utilization as team size increases. The results indicate that as grows, PoTS not only enhances security but also achieves better computational efficiency due to the averaging effects of execution time variations. These findings highlight PoTS as a promising alternative to traditional consensus mechanisms, offering both robust security and efficient resource utilization. By leveraging team-based block generation and randomized participant reassignment, PoTS provides a scalable and resilient approach to decentralized consensus.

Paper Structure

This paper contains 20 sections, 5 equations, 4 figures, 2 tables.

Table of Contents

  1. Introduction
  2. Related Work and Background
  3. Comparison of PoW, PoS, and PoTS
  4. Attack Resistance in Blockchain Consensus
  5. Related Work
  6. Simulation Model
  7. Simulation Parameters
  8. Network Setup
  9. Computation Time Model
  10. Attacker Strategy
  11. Simulation Results
  12. Comparison of Simulation and Theoretical Predictions
  13. Comparison of Simulation and Theoretical Predictions
  14. Attacker Win Rate
  15. Normalized Computation Efficiency (NCE)
  16. ...and 5 more sections

Figures (4)

  • Figure 1: Comparison of Block Generation Process in PoW and PoTS. Adapted from yonezawa2024pots.
  • Figure 2: Attacker win rate vs. team size for different attacker ratios. Larger teams significantly reduce the attacker's success probability.
  • Figure 3: Normalized Computation Efficiency (NCE) vs. team size for attacker ratio $\alpha = 0.5$. Higher values indicate better energy efficiency.
  • Figure 4: Maximum consecutive attacker wins vs. team size for different attacker ratios. Larger teams significantly limit an attacker's ability to sustain consecutive wins.