Privacy-Preserving DLT: Zero-Knowledge Proofs, Confidential Computing, and Swiss Regulatory Alignment

The tension between transparency and confidentiality is one of the defining challenges of enterprise and institutional DLT adoption. Distributed ledgers derive their trust properties from transparency — the ability of participants to independently verify transactions and ledger state. Yet commercial and regulatory requirements demand confidentiality — the protection of sensitive transaction data, proprietary business information, and personal data from unauthorised disclosure. Privacy-preserving DLT technologies resolve this tension by enabling verification without disclosure, allowing participants to prove the validity of transactions without revealing the underlying data.

The Privacy Paradox

The fundamental value proposition of DLT — a shared, tamper-resistant record maintained by consensus — creates an inherent privacy challenge. In the simplest DLT architecture, every participant processes and stores every transaction, meaning that all transaction data is visible to all network participants. While this transparency enables trustless verification, it is incompatible with the confidentiality requirements of most commercial and financial applications.

For Swiss financial institutions, the privacy paradox is particularly acute. Banking secrecy obligations under Article 47 of the Banking Act prohibit the unauthorised disclosure of client information. Competition law requires that commercially sensitive information — pricing, trading strategies, client relationships — remain confidential. Data protection law mandates the protection of personal data. And regulatory requirements for financial market infrastructure demand that the details of individual transactions be accessible to supervisory authorities but not to other market participants.

These requirements cannot be satisfied by a DLT architecture in which all transaction data is visible to all participants. Privacy-preserving technologies are therefore essential for the institutional adoption of DLT in Switzerland.

Zero-Knowledge Proofs

Zero-knowledge proofs (ZKPs) are cryptographic techniques that enable a prover to convince a verifier that a statement is true without revealing any information beyond the truth of the statement itself. In the DLT context, ZKPs enable the validation of transactions without disclosing the transaction details to the validators.

Several ZKP systems are relevant to institutional DLT applications.

zk-SNARKs (Zero-Knowledge Succinct Non-Interactive Arguments of Knowledge) produce compact proofs that can be verified quickly and with minimal computational resources. The succinctness property makes zk-SNARKs suitable for on-chain verification, where computational resources are limited and verification must be efficient. However, zk-SNARKs typically require a trusted setup phase, during which cryptographic parameters are generated in a process that must be conducted securely to avoid compromising the proof system.

zk-STARKs (Zero-Knowledge Scalable Transparent Arguments of Knowledge) eliminate the trusted setup requirement, using public randomness instead of secret parameters. zk-STARKs produce larger proofs than zk-SNARKs but offer stronger security assumptions and resistance to quantum computing attacks. The scalability properties of zk-STARKs — proof generation time scales quasi-linearly with computation complexity — make them suitable for large-scale applications.

Bulletproofs are a type of zero-knowledge proof that does not require a trusted setup and produces relatively compact proofs. Bulletproofs are particularly efficient for range proofs — proving that a value lies within a specified range without revealing the value itself. This property is useful for financial applications, such as proving that an account balance is sufficient to cover a transaction without revealing the exact balance.

The application of ZKPs to Swiss institutional DLT encompasses several use cases. Confidential transactions use ZKPs to prove that a transaction is valid — that the sender has sufficient funds, that the amounts balance, that regulatory constraints are satisfied — without revealing the transaction amount, the sender, or the recipient to other network participants. Compliant privacy solutions use ZKPs to prove regulatory compliance — for example, that a transaction participant is not on a sanctions list or that a token transfer satisfies investor qualification requirements — without revealing the underlying identity data.

Multi-Party Computation

Secure multi-party computation (MPC) enables multiple parties to jointly compute a function over their inputs while keeping those inputs private. Each party contributes its input to the computation, but no party learns anything about the other parties’ inputs beyond what can be inferred from the output.

In the DLT context, MPC has several applications relevant to Swiss institutional users.

Key management using MPC distributes the control of private keys across multiple parties or multiple devices, ensuring that no single party or device has sufficient information to reconstruct the key. This approach provides enhanced security for the custody of digital assets and the control of validator nodes, addressing the key-person risk and single-point-of-failure vulnerabilities associated with traditional key management.

Private smart contract execution using MPC enables the computation of smart contract logic on encrypted inputs, producing encrypted outputs that are decrypted only by the authorised parties. This approach enables the benefits of programmable logic — automated execution, deterministic outcomes, audit trails — without exposing the computation inputs or outputs to the broader network.

Collaborative analytics using MPC enables multiple institutions to compute aggregate statistics, detect patterns (such as fraud indicators), or assess systemic risk across their combined datasets without revealing individual-level data to each other. This application is relevant to Swiss financial regulators, who require aggregate market data for supervisory purposes, and to industry bodies, who benefit from cross-institutional analytics for fraud detection and risk management.

Trusted Execution Environments

Trusted execution environments (TEEs) are hardware-based security mechanisms that create isolated computing environments — enclaves — in which code and data are protected from access or modification by the host operating system, the hypervisor, or other software running on the same hardware. TEEs provide confidentiality and integrity guarantees that are enforced by the hardware, offering a complementary approach to cryptographic privacy techniques.

In the DLT context, TEEs enable the processing of confidential data within an enclave, with the results attested by the hardware and published to the ledger. Validators can confirm that the computation was performed correctly within a genuine TEE without having access to the data processed within the enclave. This approach offers performance advantages over cryptographic techniques — particularly for complex computations — but introduces hardware trust assumptions and supply chain dependencies.

Intel SGX (Software Guard Extensions) and ARM TrustZone are the most widely deployed TEE technologies. Swiss institutional DLT users evaluating TEE-based privacy solutions must assess the trust assumptions associated with these technologies, including the risk of hardware vulnerabilities, the dependency on specific chip manufacturers, and the attestation mechanisms used to verify enclave integrity.

Regulatory Alignment

Privacy-preserving DLT technologies align well with several elements of the Swiss regulatory framework.

Banking secrecy requirements are satisfied by privacy-preserving architectures that prevent the disclosure of client information to unauthorised parties while maintaining the ability of the bank and the regulator to access the underlying data. ZKP-based confidential transactions, for example, can ensure that transaction details are visible only to the transacting parties and the regulatory authority, with other network participants seeing only the cryptographic proof of validity.

Data protection requirements under the FADP are addressed by privacy-preserving techniques that implement data minimisation (revealing only the data necessary for the specific purpose), purpose limitation (enabling selective disclosure based on the verifier’s authorised purpose), and data security (protecting personal data from unauthorised access through cryptographic or hardware-based mechanisms).

AML/KYC compliance can be maintained within privacy-preserving frameworks through the use of verifiable credentials and ZKP-based compliance proofs. A transaction participant can prove that they have been identified and verified by a regulated financial institution, that they are not on a sanctions list, and that the transaction does not exceed applicable thresholds — all without revealing their identity or the transaction details to other network participants.

Regulatory access is a critical design consideration. Privacy-preserving DLT architectures must provide regulatory authorities with the ability to access transaction data for supervisory, investigative, and enforcement purposes. Regulatory trapdoors — cryptographic mechanisms that enable designated authorities to decrypt or access confidential data — are a common design pattern, though they introduce complexity and must be governed carefully to prevent abuse.

Outlook

The maturation of privacy-preserving DLT technologies is accelerating, driven by advances in cryptographic research, hardware capabilities, and the increasing demand for confidential DLT applications in institutional finance. The convergence of ZKPs, MPC, and TEEs into hybrid privacy architectures — combining the strengths of each approach — is producing solutions that offer both strong privacy guarantees and practical performance for enterprise applications.

For Swiss financial institutions, the adoption of privacy-preserving DLT is transitioning from a technical research topic to an operational requirement. As DLT-based financial infrastructure expands and the volume of institutional transactions processed on distributed ledgers grows, the ability to maintain confidentiality while preserving verifiability becomes a prerequisite for regulatory compliance and commercial viability.

For related analysis, see our coverage of DLT identity solutions and DLT scalability solutions.

Donovan Vanderbilt is a contributing editor at ZUG DLT, covering distributed ledger technology law, regulation, and institutional adoption from Zurich. The Vanderbilt Portfolio AG provides research and analysis on Swiss digital asset infrastructure.