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Random number generation models applied to ethereum roulette gameplay

Sheri gill 11 hours ago 3 min read

Generating unpredictable outcomes in deterministic blockchain environments creates unique technical challenges. Ethereum roulette at https://crypto.games/roulette/ethereum requires randomness sources that no party can manipulate while remaining verifiable by players. Multiple approaches exist for producing the random numbers determining where virtual balls land during gameplay.

Block hash utilization

Many implementations derive randomness from ethereum block hashes produced during mining processes. These hashes result from computational work solving proof-of-work puzzles, creating values that appear random and unpredictable. A contract might use the hash from block 15234567 as the randomness seed for determining that round’s outcome. Since miners cannot predict their block hashes before finding valid solutions, they cannot manipulate outcomes to favor specific bets. Players can verify outcomes by checking that the specified block hash was indeed used in calculations. This approach’s weakness involves miners potentially discarding unfavorable blocks if the financial gain from manipulating outcomes exceeds mining rewards, though this attack becomes impractical when game stakes stay reasonable relative to mining profitability.

Commit-reveal schemes

Two-phase processes let players contribute to randomness generation without enabling prediction or manipulation:

Commit phase: Players submit hashed random values they’ve generated locally without revealing the actual numbers to anyone yet
Collection period: The contract gathers multiple player commitments creating a pool of hidden randomness contributions from independent sources
Reveal window: Players expose their original random values allowing verification that revealed numbers match their earlier cryptographic commitments
Combination logic: The contract combines all revealed values through hashing or XOR operations producing final randomness no individual controlled
Outcome calculation: The combined random number determines where the ball lands with results depending on all participants’ inputs collectively

This model prevents any single party from controlling outcomes since the final randomness incorporates contributions from multiple independent sources that cannot be predicted before reveal phases complete.

Hybrid combination approaches

Some implementations combine multiple randomness sources to reduce single points of failure or manipulation. A contract might use block hashes XORed with oracle-provided random numbers and player commitments from reveal schemes. This layered approach means attackers must compromise all randomness sources simultaneously to manipulate outcomes. If block hashes prove vulnerable to miner manipulation, oracle randomness still contributes unpredictability. If oracles get compromised, block hashes and player commitments maintain outcome uncertainty. The complexity trade-off involves more elaborate code requiring careful implementation to avoid introducing bugs while combining multiple systems. Players benefit from enhanced security but face more complicated verification processes when auditing that randomness generation followed proper procedures.

Verifiable delay functions

Advanced cryptographic techniques create provably unpredictable random numbers through time-locked computations. These functions require specific sequential steps taking minimum time to complete, preventing anyone from computing results early enough to influence bet placement. A verifiable delay function might take ten seconds to compute regardless of available computing power. The contract initiates computation after betting closes, then uses the result as randomness for outcome determination. Players can verify correct execution since the functions are designed to make verification faster than initial computation. This approach eliminates most manipulation vectors since outcomes cannot be known until after bets are locked in. Implementation complexity and gas costs currently limit widespread adoption though technology continues evolving toward practical deployment in production gaming systems.

Each approach balances different tradeoffs between security, decentralization, verifiability, and implementation complexity. Players should verify which randomness source their chosen platform uses and whether that approach provides adequate protection against manipulation for their risk tolerance.