| Internet-Draft | LICET Human Intent Protocol | June 2026 |
| Pereira | Expires 31 December 2026 | [Page] |
Autonomous AI agents executing consequential actions in high-stakes domains — medical prescribing, financial transactions, critical infrastructure control — require authorization mechanisms that go beyond classical identity verification. Existing mechanisms (passwords, static biometrics, digital signatures) verify who authorized an action but cannot verify whether the authorizing human was genuinely conscious, uncoerced, and cognitively capable at the moment of authorization.¶
This document specifies LICET (Latin: "it is permitted"), a cryptographic middleware protocol that binds AI agent authorization events to the real-time physiological state of the authorizing human. LICET defines: (1) a biometric capture and coercion-detection procedure using wearable sensor data; (2) per-event session-key derivation using HKDF (RFC 5869); (3) a biometric temporal signature using HMAC (RFC 2104); (4) a Schnorr zero-knowledge proof over the BN128 elliptic curve enabling third-party audit without biometric data exposure; and (5) a SHA-256 hash-chained ledger for tamper-evident authorization records.¶
A reference implementation is publicly deployed at https://licet.dev/v1/ and available as open source at https://github.com/christianrp45/licet-protocol.¶
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Artificial intelligence agents are transitioning from passive tools to autonomous actors capable of executing actions with real, irreversible consequences. A medical AI agent may adjust medication dosages. A financial AI may execute wire transfers. An infrastructure AI may modify power-grid parameters. In each case, the assumed safeguard is human authorization.¶
Contemporary authorization primitives are designed to answer one question: is this person who they claim to be? They are silent on a second, equally critical question: is this person currently in a state that constitutes genuinely free, conscious, and cognitively competent intent?¶
This gap is the intent gap — the absence of a cryptographically verifiable mechanism to attest that a human was genuinely capable of and free to form the intent they expressed. The EU AI Act [EUAIACT] mandates human oversight for high-risk AI systems (Article 14) but specifies no technical standard for what constitutes verifiable human oversight. LICET provides the technical substrate for this regulatory requirement.¶
The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", "SHOULD", "SHOULD NOT", "RECOMMENDED", "NOT RECOMMENDED", "MAY", and "OPTIONAL" in this document are to be interpreted as described in BCP 14 [RFC2119] [RFC8174] when, and only when, they appear in all capitals, as shown here.¶
The LICET authorization protocol proceeds as follows:¶
Request. Agent A submits an authorization request to LICET Server S specifying: action descriptor (a), agent identifier (id_A), target entity (tgt), and Unix timestamp (ts).¶
Biometric Capture. Server S instructs Wearable W to capture physiological data over a window t_c (default: 10 seconds): heart rate (f_HR), peripheral oxygen saturation (s_O2), and heart rate variability (v_HRV).¶
Coercion Detection. Server S evaluates the captured signals according to Section 3. If Coercion Risk is MEDIUM or HIGH, or cognitive impairment is detected, authorization MUST be denied.¶
Intent Hash Generation. Server S computes:¶
h = SHA-256(a || id_A || tgt || ts)¶
Session Key Derivation. Server S derives a per-event session key using HKDF [RFC5869]:¶
k_s = HKDF-SHA256(k_m, h)¶
Biometric Signature. Server S computes:¶
sigma = HMAC-SHA256(h || f_HR || s_O2 || v_HRV || ts, k_s)¶
Zero-Knowledge Proof. Server S generates a Schnorr proof as specified in Section 5.¶
Ledger Append. Server S appends an entry to the hash-chained ledger as specified in Section 6.¶
Authorization Token. Server S returns to Agent A: intent hash h, biometric signature sigma, ZKP proof, ledger record identifier, and timestamp.¶
LICET MUST accept biometric input from any of the following sources:¶
Three signals MUST be captured over window t_c:¶
The coercion detection function C maps physiological signals to a risk level:¶
C(f_HR, v_HRV) = HIGH if f_HR > 130 AND v_HRV < 20 MEDIUM if f_HR > 100 AND v_HRV < 35 LOW otherwise¶
Physiological basis: under acute psychological coercion, the sympathetic branch of the autonomic nervous system simultaneously elevates heart rate and suppresses HRV [THAYER2012]. This dual-axis collapse distinguishes coercion from aerobic exercise, where HRV may be maintained or recover rapidly.¶
I(s_O2) = IMPAIRED if s_O2 < 90 NORMAL otherwise¶
Authorization MUST be denied if any of the following conditions hold:¶
The intent hash uniquely identifies the requested action:¶
h = SHA-256(a || id_A || tgt || ts)¶
where || denotes concatenation, a is the UTF-8 encoded action descriptor, id_A is the UTF-8 encoded agent identifier, tgt is the UTF-8 encoded target entity, and ts is the Unix timestamp encoded as a 64-bit big-endian integer.¶
A per-event session key SHALL be derived using HKDF [RFC5869]:¶
k_s = HKDF(hash=SHA-256, IKM=k_m, info=h, L=32)¶
where k_m is the server master key (minimum 256 bits, generated using a cryptographically secure random number generator) and h is the intent hash. Session key isolation ensures that compromise of k_s for event i does not expose k_s for any other event j, nor the master key k_m.¶
sigma = HMAC-SHA256(h || f_HR || s_O2 || v_HRV || ts, k_s)¶
The biometric values f_HR, s_O2, v_HRV MUST be encoded as IEEE 754 double-precision (64-bit) big-endian floating-point values.¶
Properties:¶
LICET uses a non-interactive Schnorr proof over the BN128 elliptic curve with the Fiat-Shamir heuristic [FIAT1987]. Let G be the BN128 generator point and q the group order.¶
1. w = SHA-256(sigma || h) mod q 2. PK = w * G 3. r randomly sampled from Z_q 4. R = r * G 5. c = SHA-256(R || PK || h) mod q 6. s = (r - c * w) mod q Proof: pi = (R, c, s, PK)¶
Given pi = (R, c, s, PK) and intent hash h, a verifier V checks:¶
s * G + c * PK =?= R AND c =?= SHA-256(R || PK || h) mod q¶
If both equalities hold, V is convinced that the prover possessed knowledge of the biometric signature sigma for this intent hash, without learning sigma, f_HR, s_O2, or v_HRV.¶
L_0 = SHA-256(entry_0 || "LICET-GENESIS")
L_n = SHA-256(entry_n || L_{n-1}), n >= 1
¶
Any retroactive modification to entry i invalidates L_i through L_n, making tampering mathematically detectable by any party recomputing the chain.¶
Implementations MUST provide a publicly accessible mechanism to verify the full hash chain and return a boolean integrity result, without requiring authentication.¶
Each authorization event produces a unique intent hash h binding the action, agent identifier, target, and timestamp. Implementations MUST reject authorization requests with timestamps outside a configurable window (RECOMMENDED: 60 seconds).¶
The concurrent HR/HRV threshold is a statistical, not absolute, protection. Population-level thresholds may produce false positives for individuals with baseline tachycardia or false negatives for highly trained individuals. Future versions of this protocol SHOULD define a personalized baseline calibration procedure.¶
Raw biometric values MUST NOT be stored in the ledger. The ZKP mechanism defined in Section 5 ensures that auditors can verify authorization validity without accessing biometric data, satisfying data minimization principles of privacy regulations.¶
Implementations MUST protect the master key k_m using hardware security modules or equivalent mechanisms. Key rotation procedures MUST be defined by each deployment.¶
This document has no IANA actions at this time.¶
The LICET protocol was first documented and registered on the Bitcoin blockchain via OpenTimestamps on February 25, 2026. The SHA-256 hash of the original protocol document is publicly archived as a tamper-evident timestamp predating this Internet-Draft.¶
A reference implementation of this protocol is publicly available:¶