BlockCap: Blockchain-Based Capability Authorization for IoT

A blockchain-backed capability-based authorization system for enforcing fine-grained, auditable access control in resource-constrained IoT environments.

BlockCap is a capability-based authorization system designed to enforce fine-grained, auditable access control in resource-constrained IoT infrastructures. The system addresses the limitations of centralized identity- and role-based access control in IoT by combining capability tokens with blockchain-backed governance and traceability.
Rather than assuming that IoT endpoints can participate in consensus or store global policy state, BlockCap introduces a role-separated trust model in which authorization decisions are locally enforced while globally governed through smart contracts. The design explicitly targets heterogeneous deployments spanning cloud, fog, edge gateways, and constrained sensors/actuators.

System Model and Trust Assumptions

BlockCap system model showing validators, non-validator gateways, and constrained endpoints. Blockchain participation is restricted to capable nodes, while enforcement occurs at the service boundary.
BlockCap defines a network of nodes \(N = \{n_1, \dots, n_k\}\), each assigned a role:
  • Validators (cloud/fog): maintain blockchain state, execute consensus, and approve policy-critical operations.
  • Non-validator gateways (edge/fog): enforce access decisions and query on-chain capability state.
  • Endpoints (sensors/actuators): expose services but remain blockchain-agnostic.
Authorization is expressed as directed capability grants between nodes and services, enabling least-privilege, flow-specific access control.

Capability-Based Authorization Model

Directed graph representation of BlockCap’s trust model. Capabilities are defined as subject → object → operation tuples and enforced at API boundaries.
BlockCap encodes authorization as capability tokens that specify:
  • Subject node identity
  • Target node and service
  • Permitted operations (READ, WRITE, EXECUTE, TRANSMIT)
  • Issuance time, validity window, and revocation state
Capabilities are:
  • Issued and revoked on-chain via smart contracts
  • Checked off-chain by gateways before request forwarding
  • Auditable through immutable blockchain logs
This design enables decentralized enforcement without pushing cryptographic or blockchain overhead onto constrained devices.

Governance and Consensus

BlockCap is implemented on Hyperledger Besu using a Proof-of-Authority (PoA) network with QBFT for validator consensus. Governance-sensitive actions—such as node registration, validator admission, and capability issuance—are coordinated through smart contracts and validator voting.
This approach ensures:
  • Low-latency block finality
  • Resistance to single-point-of-failure
  • Deterministic authorization state across validators

Security Analysis

The system is analyzed using the STRIDE threat model, covering:
  • Spoofing of node identities
  • Tampering with authorization state
  • Repudiation of access decisions
  • Information disclosure
  • Denial-of-service
  • Elevation of privilege
BlockCap mitigates these threats through cryptographic identities, immutable logging, validator-governed policy changes, and strict capability validation at enforcement points.

Experimental Evaluation

BlockCap is evaluated on a heterogeneous testbed comprising:
  • Cloud and fog nodes (validator-capable)
  • Edge gateways (non-validator enforcers)
  • Resource-constrained IoT endpoints
Measured metrics include:
  • Capability issuance and validation latency
  • CPU and memory overhead on gateways
  • RPC performance under concurrent requests
  • Blockchain synchronization and throughput
Results demonstrate that BlockCap introduces minimal runtime overhead while providing strong security guarantees and full authorization traceability.

Key Contributions

  • Blockchain-backed capability authorization tailored for IoT constraints
  • Decoupled enforcement and governance via role separation
  • Fine-grained, bidirectional access control
  • Formal STRIDE-based security analysis
  • Practical deployment and evaluation on real hardware

References