Overview and Assumptions

In this section, we provide an overview of the Canton architecture, illustrate the high-level flows, entities (defining trust domains) and components. We then state the trust assumptions we make on the different entities, and the assumptions on communication links.

Canton is designed to fulfill its high-level requirements. Before reading this section, you should be familiar with the Daml language and the hierarchical transactions of the DA ledger model.

Canton 101

A Basic Example

We will use a simple delivery-versus-payment (DvP) example to provide some background on how Canton works. Alice and Bob want to exchange an IOU given to Alice by a bank for some shares that Bob owns. We have four parties: Alice (aka A), Bob (aka B), a Bank and a share registry SR. There are also three types of contracts:

1. an Iou contract, always with Bank as the backer
2. a Share contract, always with SR as the registry
3. a DvP contract between Alice and Bob

Assume that Alice has a “swap” choice on a DvP contract instance that exchanges an Iou she owns for a Share that Bob has. We assume that the Iou and Share contract instances have already been allocated in the DvP. Alice wishes to commit a transaction executing this swap choice; the transaction has the following structure:

Transaction Processing in Canton

In Canton, committing the example transaction consists of two steps:

1. Alice’s participant prepares a confirmation request for the transaction. The request provides different views on the transaction; participants see only the subtransactions exercising, fetching or creating contracts on which their parties are stakeholders (more precisely, the subtransactions where these parties are informees). The views for the DvP, and their recipients, are shown in the figure below. Alice’s participant submits the request to a sequencer, who orders all confirmation requests on a Canton domain; whenever two participants see the same two requests, they will see them according to this sequencer order. The sequencer has only two functions: ordering messages and delivering them to their stated recipients. The message contents are encrypted and not visible to the sequencer.

   

   Views in the transaction; each box represents a transaction part visible to the participants in its bottom-right corner. A participant might receive several views, some of which can be nested.

2. The recipients then check the validity of the views that they receive. The validity checks cover four aspects:

   1. validity as defined in the DA ledger model: consistency, (mainly: no double spends), conformance (the view is a result of a valid Daml interpretation) and authorization (guaranteeing that the actors and submitters are allowed to perform the view’s action)
   2. authenticity (guaranteeing that the submitters are who they claim to be).
   3. transparency (guaranteeing that participants who should be notified get notified).
   4. consensus (guaranteeing that participants commit projections of the same transaction)

   Conformance, authorization, authenticity, transparency, and consensus problems arise only due to submitter malice. Consistency problems can arise with no malice. For example, the Iou that is to be transferred to Bob might simply have already been spent. Based on the check’s result, a subset of recipients called confirming participants then prepares a (positive or negative) mediator response for each view separately. A confirmation policy associated with the request specifies which participants must confirm, given the transaction’s informees.

   The confirming participants send their responses to a mediator, another special entity that aggregates the responses into a single verdict for the entire confirmation request. The mediator serves to hide the participants’ identities from each other (so that Bank and SR do not need to know that they are part of the same transaction). Like the sequencer, the mediator does not learn the transactions’ contents. Instead, Alice’s participant, in addition to sending the request, also simultaneously notifies the mediator about the informees of each view. The mediator receives a version of the transaction where only the informees of a view are visible and the contents blinded, as conceptually visualized in the diagram below.

   

   In the informee tree for the mediator, all transaction contents are blinded.

   From this, the mediator derives which (positive) mediator responses are necessary in order to decide the confirmation request as approved.

   Requests submitted by malicious participants can contain bogus views. As participants can see only parts of requests (due to privacy reasons), upon receiving an approval for a request, each participant locally filters out the bogus views that are visible to it, and accepts all remaining valid views of an approved confirmation request. Under the confirmation policy’s trust assumptions, the protocol ensures that the local decisions of honest participants match for all views that they jointly see. The protocol thus provides a virtual shared ledger between the participants, whose transactions consist of such valid views. Once approved, the accepted views are final, i.e., they will never be removed from the participants’ records or the virtual ledger.

We can represent the confirmation workflow described above by the following message sequence diagram, assuming that each party in the example runs their own participant node.

The sequencer and the mediator, together with a so-called topology manager (described shortly), constitute a Canton domain. All messages within the domain are exchanged over the sequencer, which ensures a total order between all messages exchanged within a domain.

The total ordering ensures that participants see all confirmation requests and responses in the same order. The Canton protocol additionally ensures that all non-Byzantine (i.e. not malicious or compromised) participants see their shared views (such as the exercise of the Iou transfer, shared between the participants of Bank and A) in the same order, even with Byzantine submitters. This has the following implications:

1. The correct mediator response for each view is always uniquely determined, because Daml is deterministic. However, for performance reasons, we allow occasional incorrect negative responses, when participants start behaving in a Byzantine fashion or under contention. The system provides the honest participants with evidence of either the correctness of their responses or the reason for the incorrect rejections.
2. The global ordering creates a (virtual) global time within a domain, measured at the sequencer; participants learn that time has progressed whenever they receive a message from the sequencer. This global time is used for detecting and resolving conflicts and determining when timeouts occur. Conceptually, we can therefore speak of a step happening at several participants simultaneously with respect to this global time, although each participant performs this step at a different physical time. For example, in the above message sequence diagram, Alice, Bob, the Bank, and the share registry’s participants receive the confirmation request at different physical times, but conceptually this happens at the timestamp ts1 of the global time, and similarly for the result message at timestamp ts6.

In this document, we focus on the basic version of Canton, with just a single domain. Canton also supports connecting a participant to multiple domains and transferring contracts between domains (see composability).

As mentioned in the introduction, the main challenges for Canton are reconciling integrity and privacy concerns while ensuring progress with the confirmation-based design, given that parties might be overloaded, offline, or simply refusing to respond. The main ways we cope with this problem are as follows:

• We use timeouts: if a transaction’s validity cannot be determined after a timeout (which is a domain-wide parameter), the transaction is rejected.

• Flexible confirmation policies: To offer a trade-off between trust, integrity, and liveness, we allow Canton domains to choose their confirmation policies. Confirmation policies specify which participants need to confirm which views. This enables the mediator to determine the sufficient conditions to declare a request approved. Of particular interest is the VIP confirmation policy, applicable to transactions which involve a trusted (VIP) party as an informee on every action. An example of a VIP party is a market operator. The policy ensures ledger validity assuming the VIP party’s participants behave correctly; incorrect behavior can still be detected and proven in this case, but the fallout must be handled outside of the system. Another important policy is the signatory confirmation policy, in which all signatories and actors are required to confirm. This requires a lower level of trust compared to the VIP confirmation policy sacrificing liveness when participants hosting signatories or actors are unresponsive. Another policy is the full confirmation policy, in which all informees are required to confirm. This requires the lowest level of trust, but sacrifices liveness when some of the involved participants are unresponsive.

Conflict Detection

Participants detect conflicts between concurrent transactions by locking the contracts that a transaction consumes. The participant locks a contract when it validates the confirmation request of a transaction that archives the contract. The lock indicates that the contract might be archived. When the mediator’s decision arrives later, the contract is either archived or unlocked, depending on whether the transaction is committed or rolled back. Transactions that attempt to use a locked (i.e., potentially archived) contract are rejected. This design decision is based on the optimistic assumption that transactions are typically accepted; the later conflicting transaction can therefore be pessimistically rejected.

The next three diagrams illustrate locking and pessimistic rejections using the counteroffer example from the DA ledger model. There are two transactions and three parties and every party runs their own participant node.

• The painter P accepts A‘s Counteroffer in transaction tx1. This transaction consumes two contracts:

  • The Iou between A and the Bank, referred to as c1.
  • The Counteroffer with stakeholders A and P, referred to as c2.

  The created contracts (the new Iou and the PaintAgreement) are irrelevant for this example.

• Suppose that the Counteroffer contains an additional consuming choice controlled by A, e.g., Alice can retract her Counteroffer. In transaction tx2, A exercises this choice to consume the Counteroffer c2.

Since the messages from the sequencer synchronize all participants on the (virtual) global time, we may think of all participants performing the locking, unlocking, and archiving simultaneously.

In the first diagram, the sequencer sequences tx1 before tx2. Consequently, A and the Bank lock c1 when they receive the confirmation request, and so do A and P for c2. So when tx2 later arrives at A and P, the contract c2 is locked. Thus, A and P respond with a rejection and the mediator follows suit. In contrast, all stakeholders approve tx1; when the mediator’s approval arrives at the participants, each participant archives the appropriate contracts: A archives c1 and c2, the Bank archives c1, and P archives c2.

When two transactions conflict while they are in flight, the later transaction is always rejected.

The second diagram shows the scenario where A‘s retraction is sequenced before P‘s acceptance of the Counteroffer. So A and P lock c2 when they receive the confirmation request for tx2 from the sequencer and later approve it. For tx1, A and P notice that c2 is possibly archived and therefore reject tx1, whereas everything looks fine for the Bank. Consequently, the Bank and, for consistency, A lock c1 until the mediator sends the rejection for tx1.

Transaction tx2 is now submitted before tx1. The consumed contract c1 remains locked by the rejected transaction until the mediator sends the result message.

Note

In reality, participants approve each view individually rather than the transaction as a whole. So A sends two responses for tx1: An approval for c1‘s archival and a rejection for c2‘s archival. The diagrams omit this technicality.

The third diagram shows how locking and pessimistic rejections can lead to unnecessary rejections. Now, the painter’s acceptance of tx1 is sequenced before Alice’s retraction like in the first diagram, but the Iou between A and the Bank has already been archived earlier. The painter receives only the view for c2, since P is not a stakeholder of the Iou c1. Since everything looks fine, P locks c2 when the confirmation request for tx1 arrives. For consistency, A does the same, although A already knows that the transaction will fail because c1 is archived. Hence, both P and A reject tx2 because it tries to consume the locked contract c2. Later, when tx1‘s rejection arrives, c2 becomes active again, but the transaction tx2 remains rejected.

Even if the earlier transaction tx1 is rejected later, the later conflicting transaction tx2 remains rejected and the contract remains locked until the result message.

Time in Canton

The connection between time in Daml transactions and the time defined in Canton is explained in the respective ledger model section on time.

The respective section introduces ledger time and record time. The ledger time is the time the participant (or the application) chooses when computing the transaction prior to submission. We need the participant to choose this time as the transaction is pre-computed by the submitting participant and this transaction depends on the chosen time. The record time is assigned by the sequencer when registering the confirmation request (initial submission of the transaction).

There is only a bounded relationship between these times, ensuring that the ledger time must be in a pre-defined bound around the record time. The tolerance is defined on the domain as a domain parameter, known to all participants:

canton.domains.mydomain.parameters.ledger-time-record-time-tolerance

The bounds are symmetric in Canton, so the Canton domain parameter ledger-time-record-time-tolerance equals the skew_min and skew_max parameters from the ledger model.

Note

Canton does not support querying the time model parameters via the ledger API, as the time model is a per domain property and this cannot be properly exposed on the respective ledger API endpoint.

Checking that the record time is within the required bounds is done by the validating participants and is visible to everyone. The sequencer does not know the ledger time and therefore cannot perform this validation.

Therefore, a submitting participant cannot control the output of a transaction depending on record time, as the submitting participant does not know exactly the point in time when the transaction will be timestamped by the sequencer. But the participant can guarantee that a transaction will either be registered before a certain record time, or the transaction will fail.

Subtransaction privacy

Canton splits a Daml transaction into views, as described above under transaction processing. The submitting participant sends these views via the domain’s sequencer to all involved participants on a need-to-know basis. This section explains how the views are encrypted, distributed, and stored so that only the intended recipients learn the contents of the transaction.

In the above DvP example, Canton creates a view for each node, as indicated by the boxes with the different colors. Canton captures this hierarchical view structure in a Merkle-like tree. For example, the view for exercising the “xfer” choice conceptually looks as follows, where the hashes 0x... commit to the contents of the hidden nodes and subtrees without revealing the content. In particular, the second leg’s structure, contents, and recipients are completely hidden in the hash 0x1210....

Idealized Merkle tree for the view that exercises the “xfer” choice on Alice’s Iou.

The subview that creates the transferred Iou has a similar structure, except that the hash 0x738f... is now unblinded into the view content and the parent view’s Exercise action is represented by its hash 0x8912...

Idealized Merkle tree for the view that creates Bob’s new Iou.

Using the hashes, every recipient can correctly reconstruct their projection of the transaction from the views they receive.

As illustrated in the confirmation workflow, the submitting participant sends the views to the participants hosting an informee or witness of a view’s actions. This ensures subtransaction privacy as a participant receives only the data for the witnesses it hosts, not all of the transaction. Each Canton participant persists all messages it receives from the sequencer, including the views.

Moreover, Canton hides the transaction contents from the domain too. To that end, the submitting participant encrypts the views using the following hybrid encryption scheme:

1. It generates cryptographic randomness for the transaction, the transaction seed. From the transaction seed, a view seed is derived for each view following the hierarchical view structure, using a pseudo-random function. In the DvP example, a view seed seed₀ for the action at the top is derived from the transaction seed. The seed seed₁ for the view that exercises the “xfer” choice is derived from the parent view’s seed seed₀, and similarly the seed seed₂ for the view that creates Bob’s IOU is derived from seed₁.

2. For each view, it derives a symmetric encryption key from the view seed using a key derivation function. For example, the symmetric key for the view that creates Bob’s IOU is derived from seed₂. Since the transaction seed is fresh for every submission and all derivations are cryptographically secure, each such symmetric key is used only once.

3. It encrypts the serialization of each view’s Merkle tree with the symmetric key derived for this view. The view seed itself is encrypted with the public key of each participant hosting an informee of the view. The encrypted Merkle tree and the encryptions of the view seed form the data that is sent via the sequencer to the recipients.

   Note

   The view seed is encrypted only with the public key of the participants that host an informee, while the encrypted Merkle tree itself is also sent to participants hosting only witnesses. The latter participants can nevertheless decrypt the Merkle tree because they receive the view seed of a parent view and can derive the symmetric key of the witnessed view using the derivation functions.

Even though the sequencer persists the encrypted views for a limited period, the domain cannot access the symmetric keys unless it knows the secret key of one of the informee participants. Therefore, the transaction contents remain confidential with respect to the domain.

Domain Entities

A Canton domain consists of three entities:

• the sequencer
• the mediator
• and the topology manager, providing a PKI infrastructure, and party to participant mappings.

We call these the domain entities. The high-level communication channels between the domain entities are depicted below.

In general, every domain entity can run in a separate trust domain (i.e., can be operated by an independent organization). In practice, we assume that all domain entities are run by a single organization, and that the domain entities belong to a single trust domain.

Furthermore, each participant node runs in its own trust domain. Additionally, the participant may outsource a part of its identity management infrastructure, for example to a certificate authority. We assume that the participant trusts this infrastructure, that is, that the participant and its identity management belong to the same trust domain. Some participant nodes can be designated as VIP nodes, meaning that they are operated by trusted organizations. Such nodes are important for the VIP confirmation policy.

The generic term member will refer to either a domain entity or a participant node.

Sequencer

We now list the high-level requirements on the sequencer.

Ordering: The sequencer provides a global total-order multicast where envelopes are uniquely timestamped and the global ordering is derived from the timestamps. Instead of delivering a single envelope, the sequencer provides batching, that is, a list of individual envelopes are submitted. All of these envelopes get the timestamp of the batch they are contained in. Each envelope may have a different set of recipients; the envelopes in each recipient’s batch are in the same order as in the sent batch.

Evidence: The sequencer provides the recipients with a cryptographic proof of authenticity for every batch it delivers, including evidence on the order of envelopes.

Sender and Recipient Privacy: The recipients do not learn the identity of the submitting participant. A recipient only learns the identities of recipients on a particular envelope from a batch if it is itself a recipient of that envelope.

Note

In the implementation, the recipients of an envelope are not a set of members (as indicated above), but a forest of sets of members. A member receives an envelope if it appears somewhere in the recipient forest. A member sees the nodes of the forest that contain itself as a recipient (as well as all descendants of such nodes), but it does not see the ancestors of such nodes. This feature is used to support bcc-style addressing of envelopes.

Mediator

The mediator’s purpose is to compute the final result for a confirmation request and distribute it to the participants, ensuring that transactions are atomically committed across participants, while preserving the participants’ privacy, by not revealing their identities to each other. At a high level, the mediator:

• collects mediator responses from participants,
• validates them according to the Canton protocol,
• computes the mediator verdict (approve / reject / timed out) according to the confirmation policy, and
• sends the result message.

For auditability, the mediator also persists every finalized request together with its verdict in long-term storage and allows an auditor to retrieve messages from this storage.

Topology Manager

The topology manager allows participants to join and leave the Canton domain, and to register, revoke and rotate public keys. It knows the parties hosted by a given participant. It defines the trust level of each participant. The trust level is either ordinary or VIP. A VIP trust level indicates that the participant is trusted to act honestly. A canonical example is a participant run by a trusted market operator.

Participant-internal Canton Components

The following diagram shows the main components of a participant.

A ledger application uses the ledger API (at the top of the diagram) to send commands to a participant and to receive the corresponding events. The command submission service receives a command, parses it, and performs some basic validation. Next, the command is submitted to DAMLe (DAML engine), which translates it to a transaction; a command consists only of a root node whereas a transaction also recursively contains all consequences of all exercise actions. Then, the domain router chooses a domain that is suitable for executing the transaction.

The transaction processor translates the transaction to a confirmation request; in particular, it computes the view decomposition, embeds the transaction into a Merkle tree, and creates different envelopes tailored to the different members validating the request. It uses the sequencer client to send the confirmation request to the mediator and all participants involved in the transaction.

The transaction processor also uses the sequencer client to receive confirmation requests from the domain, to send mediator responses, and to receive the result messages from the mediator.

The multi-domain event log stores every committed request and every rollback. It also stores the order of events coming from the domains the participant is connected to. The parallel indexer subscription reads events from the multi-domain event log and stores them in a format that is optimized for fast read access. The command completion service allows ledger applications to read the completions corresponding to the commands it has previously submitted. The transaction service provides a stream of all transactions that have been committed to the virtual shared ledger and are visible to the participant.

Trust Assumptions

The different sets of rules that Canton domains specify affect the security and liveness properties in different ways. In this section, we summarize the system model that we assume, as well as the trust assumptions. As specified in the high-level requirements, the system provides guarantees only to honestly represented parties. Hence, every party must fully trust its participant (but no other participants) to execute the protocol correctly. In particular, signatures by participant nodes may be deemed as evidence of the party’s action in the transaction protocol.

General Trust Assumptions

These assumptions are relevant for all system properties, except for privacy.

• The sequencer is trusted to correctly provide a global total-order multicast service, with evidence and ensuring the sender and recipient privacy.
• The mediator is trusted to produce and distribute all results correctly.
• The domain topology manager (including the underlying public key infrastructure, if any) is operating correctly.

When a transaction is submitted with the VIP confirmation policy (in which case every action in the transaction must have at least one VIP informee), there exist an additional integrity assumption:

• All VIP stakeholders must be hosted by honest participants, i.e., participants that run the transaction protocol correctly.

We note that the assumptions can be weakened by replicating the trusted entities among multiple organization with a Byzantine fault tolerant replication protocol, if the assumptions are deemed too strong. Furthermore, we believe that with some extensions to the protocol we can make the violations of one of the above assumptions detectable by at least one participant in most cases, and often also provable to other participants or external entities. This would require direct communication between the participants, which we leave as future work.

Assumptions Relevant for Privacy

The following common assumptions are relevant for privacy:

• The private keys of honest participants are not compromised, and all certificate authorities that the honest participants use are trusted.
• The sequencer is privy to:
  1. the submitters and recipients of all messages
  2. the view structure of a transaction in a confirmation request, including informees and confirming parties
  3. the confirmation responses (approve / reject / ill-formed) of confirmers.
  4. encrypted transaction views
  5. timestamps of all messages
• The sequencer is trusted with not storing messages for longer than necessary for operational procedures (e.g., delivering messages to offline parties or for crash recovery).
• The mediator is privy to:
  1. the view structure of a transaction including informees and confirming parties, and the submitting party
  2. the confirmation responses (approve / reject / ill-formed) of confirmers
  3. timestamps of messages
• The informees of a view are trusted with not violating the privacy of the other stakeholders in that same part. In particular, the submitter is trusted with choosing strong randomness for transaction and contract IDs. Note that this assumption is not relevant for integrity, as Canton ensures the uniqueness of these IDs.

When a transaction is submitted with the VIP confirmation policy, every action in the transaction must have at least one VIP informee. Thus, the VIP informees of the root actions are automatically privy to the entire contents of the transaction, according to the ledger privacy model.

Assumptions Relevant for Liveness

In addition to the general trust assumptions, the following additional assumptions are relevant for liveness and bounded liveness functional requirements on the system: bounded decision time, and no unnecessary rejections:

• All the domain entities in Canton (the sequencer, the mediator, and the topology manager) are highly available.
• The sequencer is trusted to deliver the messages timely and fairly.
• Participants hosting confirming parties according to the confirmation policy are assumed to be highly available and responding correctly. For example in the VIP confirmation policy, only the VIP participant needs to be available whereas in the signatory policy, liveness depends on the availability of all participants that host signatories and actors.