Koustav Kumar Mondal

Research

My thesis builds a trust architecture that runs from hardware to consensus. These are the threads it pulls together, and the projects and testbeds behind them.

Scroll sideways to see the whole diagram.

Hardware-anchored trust architectureFive layers from a silicon PUF fingerprint at the base, through device authentication, post-quantum cryptography and blockchain consensus, up to IoT and vehicle applications.TRUSTBUILDS UPL5IoT, vehicle and energy applicationsIoV, IoEV energy trading, CPSL4Blockchain consensusreputation-aware proof-of-energyL3Post-quantum cryptographyquantum-safe keys and signaturesL2Device authenticationlightweight PUF protocolsL1Silicon fingerprint (PUF)SRAM, arbiter and MEMS PUFs
Trust from silicon to consensus. Each layer only trusts what the layer below can prove. The PUF at the base gives every device an identity that cannot be copied, so nothing above it depends on a stored secret key.

Hardware identity with PUFs

A PUF lets a device prove who it is without storing a secret key in memory. My work builds PUF-based authentication protocols for vehicles and IoT, evaluation tooling (PUFAnalytics), a blockchain-integrated PUF framework, and a MEMS-based PUF device with a filed Indian patent.

Related papers

Blockchain consensus

Consensus protocols that stay fast on constrained hardware: reputation-aware proof-of-energy for EV energy trading, reputation-based consensus, and ledgers that anchor device identity from the PUF upwards.

Related papers

Quantum-era security

At the qCLOUDS Lab, University of Melbourne, I work on fault-tolerant distributed quantum computing: keeping computations correct when they run across many networked quantum processors. Earlier work prepares distributed systems for quantum adversaries with post-quantum cryptography in the trust stack, quantum-aware distributed ledgers and quantum-driven sensing for vehicles.

Related papers

Vehicles, edge and robots

Software-defined fog computing for VANETs, drone-assisted IoV security, EV intrusion response, predictive maintenance across edge, fog and cloud, and LoRa localization for robots in GPS-denied spaces.

Related papers

How a PUF login works

Scroll sideways to see the whole diagram.

PUF authentication with a blockchain ledgerAn IoT device asks an edge verifier to authenticate it; the verifier fetches a stored challenge and response hash from the ledger, challenges the device, checks the PUF response, logs the event and issues a session key.AUTH REQUESTFETCH CRPC, H(R)CHALLENGE CRESPONSE RLOG EVENTSESSION KEYR = PUF(C)CHECK H(R)IoT devicePUF on chipEdge verifiergateway or RSUBlockchain ledgerCRP commitmentscallreplyone-way eventsuccessful outcome
How a device proves who it is. The ledger stores only a hash of each expected response, so a stolen ledger copy does not reveal the PUF. The device never stores a key: it regenerates its answer from the silicon each time.

Now: fault-tolerant distributed quantum computing

At the qCLOUDS Lab, University of Melbourne, I study how to keep a quantum computation correct when it is spread across several smaller quantum processors.

Scroll sideways to see the whole diagram.

Fault-tolerant distributed quantum computingA distributed compiler splits a circuit across three error-corrected quantum processors, which share entangled pairs through an entanglement network to run gates between processors.SUBCIRCUITSEPR PAIRSREMOTE GATESDistributed compilerpartition and scheduleQPU Aerror-corrected qubitsQPU Berror-corrected qubitsQPU Cerror-corrected qubitsEntanglement networkEPR pair distributionquantum link (entanglement)classical controlshared, fault-prone resource
Splitting one computation across many quantum processors. No single QPU has enough qubits, so the circuit is partitioned. Gates that cross processors consume entangled pairs, and every link, qubit and pair is a place where faults must be detected and corrected.

Projects and infrastructure

  1. Sep 2026 – presentVisiting research · qCLOUDS Lab, University of Melbourne

    Fault-tolerant distributed quantum computing

    • Fault tolerance for quantum computations distributed across networked quantum processors.
  2. Dec 2024 – Aug 2026Funded project · Joint DST–NSF

    Secure and Resilient Collaborative Autonomous Driving (CoAD)

    • Collaborative sensing and path planning for secure, resilient autonomous driving.
    • Friction-aware kinematic model for mobile robots on varying surfaces.
    • LoRa-based localization for positioning in GPS-denied environments.
  3. Jan 2022 – Dec 2024Funded project · MOST Taiwan–GITA India

    Lightweight Anonymous Authentication for the Internet of Vehicles

    • Lightweight PUF-based, hardware-assisted authentication for anonymous IoV communication.
    • Decentralized blockchain architecture for secure data ledgering.
    • Real-time evaluation on Jetson Xavier NX, Raspberry Pi and UP Squared testbeds.
  4. Oct – Dec 2024Research infrastructure

    Heterogeneous edge cluster for blockchain, security and ECU testing

    • 16 nodes: 8 Raspberry Pi 5, 4 Jetson Xavier NX 16 GB, 4 UP Squared Edge AI. 72 cores, about 160 GB memory, up to 84 TOPS.
    • Kubernetes and Docker across ARM64 and x86; Ethereum, Solidity, MQTT and Node-RED for consensus and telemetry.
    • Vehicle-ECU and hardware-in-the-loop rigs over CAN, GPIO, UART, SPI and I²C; Verilog on Intel MAX 10.
  5. Dec 2022 – Feb 2023Research infrastructure

    VANET Lab private cloud and Kubernetes cluster

    • Four-node Proxmox VE and Kubernetes cluster for reproducible research workloads.
    • GPU node with dual Xeon Silver 4216, 252 GiB RAM and an RTX A5000.
    • 124 logical CPUs and about 345 GiB RAM in total.
  6. Apr – Aug 2021Pilot project · BSF, India

    Blockchain-based data storage system for the Border Security Force

    • Engineered a blockchain query mechanism for efficient, secure data retrieval.
    • End-to-end integrity and auditability through custom smart contracts.
  7. Aug 2020 – Jun 2021M.Tech research

    Security enhancement for IoT using blockchain

    • Zone-based identification so IoT devices establish mutual trust dynamically.
    • Ethereum smart contracts in Solidity for exchange among authenticated devices.
  8. Jul 2018 – Apr 2019Pilot project · Techno India

    Smart grid survey using drones and PTZ cameras

    • SHIFT algorithm for GPS-less navigation and adaptive path planning.
    • PTZ cameras and IoT telemetry for remote grid monitoring.
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