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import hashlib
import time
import numpy as np
from scipy import stats
class TemporalLock:
"""
Geophysical Cycle-Based Cryptographic Validation
Applications:
- Secure log timestamping
- Event chronology forensics
"""
def __init__(self):
self.cycles = {
'schumann': 7.83, # Schumann resonance (Hz)
'solar': 11.2 # Solar cycle (years)
}
def stamp(self, data: str) -> dict:
"""Generate time-anchored signature"""
t = time.time()
moduli = [t % freq for freq in self.cycles.values()]
return {
'timestamp': t,
'hash': hashlib.blake3(
f"{data}_{t}_{moduli[0]}".encode()
).hexdigest(),
'cycle_alignments': moduli
}
def validate(self, events: list) -> float:
"""Calculate anomaly confidence (0.0-1.0)"""
errors = sum(e['errors'] for e in events)
total = sum(e['observations'] for e in events)
return min(0.99, 1 - stats.binomtest(
k=errors, n=total, p=0.05
).pvalue) |