Cryptographic Attestation Against Integrity Attacks in Service Monitoring: A Threat Model and Verifiable Architecture

Service uptime monitoring infrastructure is a high-value target for data-integrity attacks: a single compromised or dishonest monitoring provider can fabricate availability records, retroactively suppress outage evidence, or silently alter historical data, and clients today have no cryptographic means of detecting such manipulation. This study develops a threat model for monitoring-data integrity attacks—covering provider-side tampering, evidence suppression, Sybil-identity flooding, and submission replay—and presents a verification architecture engineered to resist each threat in that model. Independent validator nodes sign availability observations with Ed25519 keys; a quorum-based aggregation rule tolerates up to f < Q/2 Byzantine validators, SHA-256 content-hash commitments bind off-chain evidence to an immutable on-ledger record that any third party can independently re-derive and check without trusting the aggregator; and stake-bonded registration imposes a quantifiable capital cost on Sybil identities. We formalize the adversary model, prove signature unforgeability under the Elliptic Curve Discrete Logarithm assumption, derive the capital cost of quorum capture, and bound the residual attack surface—selective evidence inclusion and round-stalling—that persists even under a semi-honest aggregator. A seven-day, five-validator, three-region deployment achieves 99.7% quorum agreement, sub-6-second worst-case attestation latency, and zero false positives or negatives across 200 independently re-verified historical rounds, confirming that the architecture removes the central point of trust that lets a single compromised provider corrupt monitoring evidence undetected.

@article{Anusuya2026,
  title     = {Cryptographic Attestation Against Integrity Attacks in Service Monitoring: A Threat Model and Verifiable Architecture},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {17},
  number    = {8},
  year      = {2026},
  publisher = {The Science and Information Organization},
  author    = {M A Anusuya and Chayadevi M L and Shraddha C and Vani H Y},
  doi       = {10.14569/IJACSA.2026.0170865},
  url       = {https://doi.org/10.14569/IJACSA.2026.0170865}
}