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Editor-in-Chief
Nikiforov
Vladimir O.
D.Sc., Prof.
Partners
doi: 10.17586/2226-1494-2024-24-5-797-805
Enhancing attribute-based access control with Ethereum and ZK-SNARK technologies
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Article in English
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Abstract
For citation:
Maalla M., Bezzateev S.V. Enhancing attribute-based access control with Ethereum and ZK-SNARK technologies. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2024, vol. 24, no. 5, pp. 797–805. doi: 10.17586/2226-1494-2024-24-5-797-805
Abstract
Attribute Based Access Control (ABAC) is one the most efficient, scalable, and well used access control. It’s based on attributes not on users, but even when the users want to get access to some resource, they must submit their attributes for the verification process which may reveal the privacy of the users. Many research papers suggest blockchain-based ABAC which provides an immutable and transparent access control system. However, the privacy of the system may be compromised depending on the nature of the attributes. A Zero-Knowledge Proof, Ethereum-Based Access Control (ZK‑ABAC) is proposed in this paper to simplify the management of access to the devices/objects and provide an efficient and immutable platform that keeps track of all actions and access management and preserve the privacy of the attributes. Our ZK-ABAC model utilizes smart contracts to facilitate access control management, Zero-Knowledge Succinct NonInteractive Argument of Knowledge (ZK-SNARK) protocol to add privacy to attributes, InterPlanetary File System (IPFS) network to provide distributed storage system, and Chainlink to manage communications and data between on/ off-chain systems. Comprehensive experiments and tests were conducted to evaluate the performance of our model, including the implementation of ZK-SNARK on the Ethereum blockchain. The results demonstrated the scalability challenges in the setup and proving phases, as well as the efficiency gains in the verification phase, particularly when scaled to higher numbers of users. These findings underscore the practical viability of our ZK-ABAC model for secure and privacy-preserving access control in decentralized environments.
Keywords: ABAC, Ethereum, ZK-SNARK, zero-knowledge proofs, privacy, blockchain
References
References
- Goldwasser S., Micali S., Rackoff C. The knowledge complexity of interactive proof-systems. Providing Sound Foundations for Cryptography: On the Work of Shafi Goldwasser and Silvio Micali, 2019, pp. 203–225. https://doi.org/10.1145/3335741.3335750
- Chiesa A., Hu Y., Maller M., Mishra P., Vesely N., Ward N. Marlin: Preprocessing zkSNARKs with universal and updatable SRS. Lecture Notes in Computer Science, 2020, vol. 12105, pp. 738–768. https://doi.org/10.1007/978-3-030-45721-1_26
- Campanelli M., Gailly N., Gennaro R., Jovanovic P., Mihali M., Thaler J. Linear time prover snarks with constant size proofs and square root size universal setup. Lecture Notes in Computer Science, 2023, vol. 14168, pp. 331–351. https://doi.org/10.1007/978-3-031-44469-2_17
- Fuchsbauer G., Orrù M., Seurin Y. Aggregate cash systems: A cryptographic investigation of mimblewimble. Lecture Notes in Computer Science, 2019, vol. 11476, pp. 657–689. https://doi.org/10.1007/978-3-030-17653-2_22
- Ozdemir A., Wahby R. Scaling verifiable computation using efficient set accumulators. Proc. of the 29th USENIX Conference Security Symposium, 2020, pp. 2075–2092.
- Xie T., Zhang J., Cheng Z., Zhang F., Zhang Y., Jia Y., Boneh D., Song D. zkbridge: Trustless cross-chain bridges made practical. Proc. of the 2022 ACM SIGSAC Conference on Computer and Communications Security, 2022, pp. 3003–3017. https://doi.org/10.1145/3548606.3560652
- Parno B., Howell J., Gentry C., Raykova M. Pinocchio: Nearly practical verifiable computation. Communications of the ACM, 2016, vol. 59, no. 2, pp. 103–112. https://doi.org/10.1145/2856449
- Luong D.A., Park J.H. Privacy-preserving blockchain-based healthcare system for IoT devices using ZK-SNARK. IEEE Access, 2022, vol. 10, pp. 55739–55752. https://doi.org/10.1109/access.2022.3177211
- Lin X., Zhang Y., Huang C., Xing B., Chen L., Hu D., Chen Y. An access control system based on blockchain with zero-knowledge rollups in high-traffic IoT environments. Sensors, 2023, vol. 23, no. 7, pp. 3443. https://doi.org/10.3390/s23073443
- Norvill R., Pontiveros B.B.F., State R., Cullen A. IPFS for reduction of chain size in Ethereum. Proc. of the IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData), 2018, pp. 1121–1128. https://doi.org/10.1109/cybermatics_2018.2018.00204
- Breidenbach L., Cachin C., Chan B., Coventry A., Ellis S., Juels A., Koushanfar F., Miller A., Magauran B., Moroz D., Nazarov S., Topliceanu A., Tramer F., Zhang F. Chainlink 2.0: Next steps in the evolution of decentralized oracle networks. Chainlink Labs, 2021, 136 p.
- Ouaddah A. A blockchain based access control framework for the security and privacy of IoT with strong anonymity unlinkability and intractability guarantees. Advances in Computers, 2019, vol. 115, pp. 211–258. https://doi.org/10.1016/bs.adcom.2018.11.001
- Figueroa S., Anorga J., Arrizabalaga S., Irigoyen I., Monterde M. An attribute-based access control using chaincode in RFID systems. Proc. of the 10th IFIP International Conference on New Technologies, Mobility and Security (NTMS), 2019, pp. 1–5. https://doi.org/10.1109/ntms.2019.8763824
- Cruz J.P., Kaji Y., Yanai N. RBAC-SC: Role-based access control using smart contract. IEEE Access, 2018, vol. 6, pp. 12240–12251. https://doi.org/10.1109/access.2018.2812844
- Wang S., Zhang Y., Zhang Y. A blockchain-based framework for data sharing with fine-grained access control in decentralized storage systems. IEEE Access, 2018, vol. 6, pp. 38437–38450. https://doi.org/10.1109/access.2018.2851611
- Khan F., Li H., Zhang L., Shen J. An expressive hidden access policy CP-ABE. Proc. of the IEEE Second International Conference on Data Science in Cyberspace (DSC), 2017, pp. 178–186. https://doi.org/10.1109/dsc.2017.29
- Xu R., Chen Y., Blasch E., Chen G. BlendCAC: A smart contract enabled decentralized capability-based access control mechanism for the IoT. Computers, 2018, vol. 7, no. 3, pp. 39. https://doi.org/10.3390/computers7030039
- Nishide T., Yoneyama K., Ohta K. Attribute-based encryption with partially hidden encryptor-specified access structures. Lecture Notes in Computer Science, 2008, vol. 5037, pp. 111–129. https://doi.org/10.1007/978-3-540-68914-0_7
- Liu H., Han D., Li D. Fabric-IoT: A blockchain-based access control system in IoT. IEEE Access, 2020, vol. 8, pp. 18207–18218. https://doi.org/10.1109/access.2020.2968492
- Ding S., Cao J., Li C., Fan K., Li H. A novel attribute-based access control scheme using blockchain for IoT. IEEE Access, 2019, vol. 7, pp. 38431–38441. https://doi.org/10.1109/access.2019.2905846
- Zhou Z., Huang D., Wang Z. Efficient privacy-preserving ciphertext-policy attribute based-encryption and broadcast encryption. IEEE Transactions on Computers, 2015, vol. 64, no. 1, pp. 126–138. https://doi.org/10.1109/tc.2013.200
- Maalla M.A., Bezzateev S.V. An Ethereum based attribute-based access control for IoT. Proceedings of the Instittute for Systems Analysis Russian Academy of Sciences (ISA RAS), 2024, vol. 74, no. 1, pp. 29–34. https://doi.org/10.14357/20790279240104
- Eberhardt J., Tai S. ZoKrates - scalable privacy-preserving off-chain computations. Proc. of the IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData), 2018, pp. 1084–1091. https://doi.org/10.1109/cybermatics_2018.2018.00199
- Baghery K., Pindado Z., Ràfols C. Simulation extractable versions of Groth’s ZK-SNARK revisited. Lecture Notes in Computer Science, 2020, vol. 12579, pp. 453–461. https://doi.org/10.1007/978-3-030-65411-5_22
- Baghery K., Kohlweiss M., Siim J., Volkhov M. Another look at extraction and randomization of Groth’s ZK-SNARK. Lecture Notes in Computer Science, 2021, pp. 457–475. https://doi.org/10.1007/978-3-662-64322-8_22