IoT Device Security: 20-Year Quantum Protection

Secure IoT devices for their entire lifespan with quantum-resistant encryption

🚀 Encrypt IoT telemetry in 10 minutes

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Quick Start: IoT Encryption

Estimated time: 10 minutes What you'll achieve: Encrypt IoT device data with ML-KEM for 20-year protection Requirements: AnkaSecure API access, IoT device (or simulator)

Step 1/3: Device enrollment (2 minutes)

# Generate ML-KEM key for IoT device
curl -X POST https://api.ankatech.co/keys \
  -H "Authorization: Bearer $TOKEN" \
  -d '{
    "algorithm": "ML_KEM_768",  # Lower overhead than 1024
    "purpose": "IOT_DEVICE_TELEMETRY",
    "deviceId": "sensor-12345",
    "lifespan": "20_YEARS"
  }'

✅ Result: Device key provisioned (quantum-resistant for 20 years)

{
  "keyId": "iot-sensor-12345",
  "publicKey": "MIIBIjAN...",  # Provision on device
  "algorithm": "ML_KEM_768",
  "quantumSafeUntil": "2046-01-07"
}

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Step 2/3: Device encrypts telemetry (3 minutes)

Embedded code (C for constrained devices):

#include <ankasecure_lite.h>

void send_telemetry() {
  // Telemetry data
  uint8_t telemetry[256] = "temp=25.5,humidity=60,status=OK";

  // Encrypt with ML-KEM (library handles complexity)
  uint8_t ciphertext[1024];
  size_t ciphertext_len;

  mlkem768_encrypt(
    telemetry, 256,
    device_public_key,  // Provisioned during enrollment
    ciphertext, &ciphertext_len
  );

  // Send to cloud (over TLS + ML-KEM double encryption)
  https_post("https://api.ankatech.co/iot/telemetry",
    ciphertext, ciphertext_len);
}

Overhead: ~6ms on ARM Cortex-M4 (80 MHz, embedded)

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Step 3/3: Cloud decrypts telemetry (5 minutes)

Cloud backend (Python):

from ankasecure import Client

ankasecure = Client(api_key="your-key")

@app.route('/iot/telemetry', methods=['POST'])
def receive_telemetry():
    ciphertext = request.data

    # Decrypt IoT data
    plaintext = ankasecure.decrypt(
        ciphertext=ciphertext,
        key_id="iot-sensor-12345"
    )

    # Process telemetry
    telemetry = parse_telemetry(plaintext)
    database.insert(telemetry)

    return {'status': 'received'}

✅ Result: IoT data encrypted end-to-end (device → cloud)

🎯 Security: 20-year protection (device lifespan covered)

What's next? - Bulk device provisioning: Enroll 10,000 devices - Firmware encryption: Protect firmware updates - Medical devices: FDA cybersecurity

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IoT Challenges

Challenge 1: Long Device Lifespan (10-20 Years)

Problem: Industrial IoT devices deployed for 20 years

Quantum timeline: Quantum computers arrive ~2030-2035 (within device lifespan!)

Vulnerability:

2026: Deploy device with RSA encryption
2035: Quantum computer breaks RSA
Device still deployed (10 years remaining)
      ↓
All future telemetry can be decrypted by adversary ❌

AnkaSecure solution: ML-KEM quantum-resistant from day 1

2026: Deploy device with ML-KEM-768
2035: Quantum computer cannot break ML-KEM
2046: Device decommissioned (20-year lifespan complete)
      ↓
All telemetry quantum-protected for entire lifespan ✅

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Challenge 2: Constrained Compute (Embedded Devices)

Problem: IoT devices have limited CPU, RAM, battery

Traditional PQC concern: "Post-quantum algorithms too slow for embedded"

Reality with ML-KEM:

RSA-2048 decrypt: 50-100ms (on ARM Cortex-M4)
ML-KEM-768 decrypt: 8-15ms (on ARM Cortex-M4)

ML-KEM 3-6× FASTER than RSA on embedded! ✅

Battery impact: Minimal (ML-KEM uses less CPU cycles)

Recommendation: Use ML-KEM-768 for IoT (lower overhead than ML-KEM-1024, still quantum-resistant)

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Challenge 3: Firmware Updates (Security Critical)

Problem: Firmware updates must be authenticated (prevent malicious firmware)

Attack: Adversary injects malicious firmware → compromises all devices

AnkaSecure solution: Quantum-resistant firmware signing

# Sign firmware with ML-DSA (quantum-resistant signature)
curl -X POST https://api.ankatech.co/sign \
  -d '{
    "algorithm": "ML_DSA_87",
    "document": "firmware-v2.0.bin",
    "purpose": "FIRMWARE_SIGNING"
  }'

Device verification (embedded):

// Device verifies signature before installing firmware
int verify_result = mldsa87_verify(
  firmware_signature,
  firmware_data,
  manufacturer_public_key  // Embedded in ROM
);

if (verify_result == SIGNATURE_VALID) {
  install_firmware(firmware_data);  // Safe to install
} else {
  reject_firmware();  // Malicious or corrupted
}

Security: Quantum-resistant signature (valid for device lifetime)

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IoT Use Cases by Sector

Industrial IoT (Manufacturing, Energy)

Devices: Sensors, actuators, PLCs (20-year deployment)

Data: Temperature, pressure, vibration, energy consumption

Challenge: Long deployment, quantum threat during lifespan

AnkaSecure solution:

# Enroll industrial sensor
curl -X POST https://api.ankatech.co/keys \
  -d '{
    "algorithm": "ML_KEM_768",
    "purpose": "INDUSTRIAL_SENSOR",
    "deviceType": "PRESSURE_SENSOR",
    "lifespan": "20_YEARS",
    "industry": "MANUFACTURING"
  }'

Benefits: - ✅ Quantum-resistant (20-year protection) - ✅ Low overhead (ML-KEM-768 fast on ARM) - ✅ Secure firmware updates (ML-DSA signatures)

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Medical Devices (Pacemakers, Insulin Pumps)

Devices: Implantable, wearables (10-20 year lifespan)

Data: Patient vitals, dosing, alerts (PHI)

Regulations: FDA cybersecurity guidance, HIPAA

AnkaSecure solution:

# Enroll medical device (HIPAA-compliant)
curl -X POST https://api.ankatech.co/keys \
  -d '{
    "algorithm": "ML_KEM_768",
    "purpose": "MEDICAL_DEVICE_TELEMETRY",
    "deviceType": "INSULIN_PUMP",
    "compliance": "FDA_CYBERSECURITY",
    "phi": true,
    "lifespan": "15_YEARS"
  }'

FDA compliance: Quantum-resistant encryption for PHI

Example telemetry:

// Insulin pump sends encrypted dose data
uint8_t dose_data[128] = "insulin_dose=5.2_units,bg_level=110";

mlkem768_encrypt(dose_data, 128, device_key, ciphertext);

https_post("https://api.cloud.medtech.com/telemetry", ciphertext);

Security: Patient data protected for device lifetime (15 years)

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Smart Home (Cameras, Locks, Thermostats)

Devices: Cameras, door locks, thermostats (5-10 year lifespan)

Data: Video, access logs, usage patterns

Privacy concern: Manufacturer or cloud provider snooping

AnkaSecure solution: End-to-end encryption (manufacturer cannot decrypt)

# Generate key pair (device keeps private key)
curl -X POST https://api.ankatech.co/keys \
  -d '{
    "algorithm": "ML_KEM_1024",
    "purpose": "SMART_HOME_PRIVACY",
    "exportable": true  # Export private key to device
  }'

# Export private key to device
curl https://api.ankatech.co/keys/KEY_ID/export-private \
  -H "Authorization: Bearer $TOKEN" > device-private-key.pem

Device encrypts locally (only owner can decrypt, not manufacturer!)

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Connected Vehicles (Automotive)

Devices: OBD-II dongles, telematics, autonomous driving (10-year vehicle lifespan)

Data: Location, speed, diagnostics, driver behavior

Challenge: Long deployment (10 years), privacy-sensitive

AnkaSecure solution:

# Enroll vehicle telematics
curl -X POST https://api.ankatech.co/keys \
  -d '{
    "algorithm": "ML_KEM_768",
    "purpose": "VEHICLE_TELEMATICS",
    "vehicleId": "VIN-12345",
    "lifespan": "10_YEARS"
  }'

Use case: Fleet management, usage-based insurance, predictive maintenance

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Bulk Device Enrollment

Provision 10,000 Devices

Scenario: Manufacturing 10,000 IoT sensors, need to provision keys

Bulk enrollment API:

curl -X POST https://api.ankatech.co/iot/bulk-enroll \
  -H "Authorization: Bearer $TOKEN" \
  -d '{
    "deviceIds": ["sensor-00001", "sensor-00002", ..., "sensor-10000"],
    "algorithm": "ML_KEM_768",
    "purpose": "INDUSTRIAL_IOT",
    "exportKeys": true  # Get keys for device provisioning
  }'

Response: ZIP file with 10,000 device key pairs

Manufacturing process: 1. Generate 10,000 keys via API (1 request) 2. Download key bundle 3. Provision each device during manufacturing (flash to secure storage)

Timeline: 1 hour total (vs 10,000 individual API calls = days)

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What's Next?

Secure your IoT devices: - 🚀 Quick start (10-minute device enrollment) - 📥 Download embedded SDK (C library for ARM, AVR, ESP32) - 📥 Download bulk enrollment script (provision 1000s) - 📧 Request IoT consultation (device integration assistance)

IoT-specific use cases: - Industrial IoT - Medical devices - Smart home - Connected vehicles

Related topics: - ML-KEM performance - Embedded device benchmarks - Firmware signing

Have questions? Email [email protected]

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Last updated: 2026-01-07 | ML-KEM optimized for ARM Cortex-M4, ESP32, and other embedded platforms