Key Transparency Protocol

Introduction End-to-end encrypted communication services rely on the secure exchange of public keys to ensure that messages remain confidential. It is typically assumed that service providers correctly manage the public keys associated with each user's account. However, this is not always true. A service provider that is compromised or malicious can change the public keys associated with a user's account without their knowledge, thereby allowing the provider to eavesdrop on and impersonate that user. This document describes a protocol that enables a group of users to ensure that they all have the same view of the public keys associated with each other's accounts. Ensuring a consistent view allows users to detect when unauthorized public keys have been associated with their account, indicating a potential compromise. More detailed information about the protocol participants and the ways the protocol can be deployed can be found in .

Conventions and Definitions The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", "SHOULD", "SHOULD NOT", "RECOMMENDED", "NOT RECOMMENDED", "MAY", and "OPTIONAL" in this document are to be interpreted as described in BCP 14 when, and only when, they appear in all capitals, as shown here. This document uses the TLS presentation language to describe the structure of protocol messages, but does not require the use of a specific transport protocol. As such, implementations do not necessarily need to transmit messages according to the TLS format and can chose whichever encoding method best suits their application. However, cryptographic computations MUST be done with the TLS presentation language format to ensure the protocol's security properties are maintained.

Tree Construction A Transparency Log is a verifiable data structure that maps label-version pairs to cryptographic keys or other structured data. Labels correspond to user identifiers, and a new version of a label is created each time the label's associated value changes. Transparency Logs have an epoch counter which is incremented every time a new set of label-version pairs are added.

An example log history. At epoch n the user with label X submits their first key k. As it is their first key, it is associated with version 0. At epoch n+1, user Y updates their key to l. k { ..., X:0 } * n+1 Y:3 -> l { ..., X:0, Y:3 } * n+2 Z:2 -> m { ..., X:0, Y:3, Z:2 } * n+3 X:1 -> n { ..., X:0, Y:3, Z:2, X:1 } ]]> KT uses a prefix tree to commit to a mapping between each label-version pair and a commitment to the label's value at that version. Every time the prefix tree changes, its new root hash is stored in a log tree. The benefit of the prefix tree is that it is easily searchable, and the benefit of the log tree is that it can easily be verified to be append-only. The data structure powering KT combines a log tree and a prefix tree, and is called the combined tree structure. This section describes the operation of both prefix and log trees at a high level and the way that they're combined. More precise algorithms for computing the intermediate and root values of the trees are given in .

Terminology Trees consist of nodes which have a byte string as their hash value. A node is either a leaf if it has no children, or a parent if it has either a left child or a right child. A node is the root of a tree if it has no parents, and an intermediate if it has both children and parents. Nodes are siblings if they share the same parent. The descendants of a node are that node, its children, and the descendants of its children. A subtree of a tree is the tree given by the descendants of a particular node, called the head of the subtree. The direct path of a root node is the empty list, and of any other node is the concatenation of that node's parent along with the parent's direct path. The copath of a node is the node's sibling concatenated with the list of siblings of all the nodes in its direct path, excluding the root.

Log Tree Log trees are used for storing information in the chronological order that it was added and are constructed as left-balanced binary trees. A binary tree is balanced if its size is a power of two and for any parent node in the tree, its left and right subtrees have the same size. A binary tree is left-balanced if for every parent, either the parent is balanced, or the left subtree of that parent is the largest balanced subtree that could be constructed from the leaves present in the parent's own subtree. Given a list of n items, there is a unique left-balanced binary tree structure with these elements as leaves. Note also that every parent always has both a left and right child.

A log tree containing five leaves. Log trees initially consist of a single leaf node. New leaves are added to the right-most edge of the tree along with a single parent node, to construct the left-balanced binary tree with n+1 leaves.

Example of inserting a new leaf with index 5 into the previously depicted log tree. Observe that only the nodes on the path from the new root to the new leaf change. While leaves contain arbitrary data, the value of a parent node is always the hash of the combined values of its left and right children. Log trees are powerful in that they can provide both inclusion proofs, which demonstrate that a leaf is included in a log, and consistency proofs, which demonstrate that a new version of a log is an extension of a past version of the log. An inclusion proof is given by providing the copath values of a leaf. The proof is verified by hashing together the leaf with the copath values and checking that the result equals the root hash value of the log. Consistency proofs are a more general version of the same idea. With a consistency proof, the prover provides the minimum set of intermediate node values from the current tree that allows the verifier to compute both the old root value and the current root value. An algorithm for this is given in section 2.1.2 of .

Illustration of a proof of inclusion. To verify that leaf 2 is included in the tree, the server provides the client with the hashes of the nodes on its copath, i.e., all hashes that are required for the client to compute the root hash itself. In the figure, the copath consists of the nodes marked by (X).

Illustration of a consistency proof. The server proves to the client that it correctly extended the tree by giving it the hashes of marked nodes ([X] / (X)). The client can verify that it can construct the old root hash from the hashes of nodes marked by (X), and that it can construct the new root hash when also considering the hash of the node [X].

Prefix Tree Prefix trees are used for storing key-value pairs, in a way that provides the ability to efficiently prove that a search key's value was looked up correctly. Each leaf node in a prefix tree represents a specific key-value pair, while each parent node represents some prefix which all search keys in the subtree headed by that node have in common. The subtree headed by a parent's left child contains all search keys that share its prefix followed by an additional 0 bit, while the subtree headed by a parent's right child contains all search keys that share its prefix followed by an additional 1 bit. The root node, in particular, represents the empty string as a prefix. The root's left child contains all search keys that begin with a 0 bit, while the right child contains all search keys that begin with a 1 bit. A prefix tree can be searched by starting at the root node, and moving to the left child if the first bit of a search key is 0, or the right child if the first bit is 1. This is then repeated for the second bit, third bit, and so on until the search either terminates at a leaf node (which may or may not be for the desired value), or a parent node that lacks the desired child.

A prefix tree containing five entries. New key-value pairs are added to the tree by searching it according to the same process. If the search terminates at a parent without a left or right child, a new leaf is simply added as the parent's missing child. If the search terminates at a leaf for the wrong search key, one or more intermediate nodes are added until the new leaf and the existing leaf would no longer reside in the same place. That is, until we reach the first bit that differs between the new search key and the existing search key.

The previous prefix tree after adding the key-value pair: 01101 -> F. The value of a leaf node is the encoded key-value pair, while the value of a parent node is the hash of the combined values of its left and right children (or a stand-in value when one of the children doesn't exist). A proof of membership is given by providing the leaf hash value, along with the hash value of each copath entry along the search path. A proof of non-membership is given by providing an abridged proof of membership that follows the path for the intended search key, but ends either at a stand-in node or a leaf for a different search key. In either case, the proof is verified by hashing together the leaf with the copath hash values and checking that the result equals the root hash value of the tree.

Combined Tree Log trees are desirable because they can provide efficient consistency proofs to assure verifiers that nothing has been removed from a log that was present in a previous version. However, log trees can't be efficiently searched without downloading the entire log. Prefix trees are efficient to search and can provide inclusion proofs to convince verifiers that the returned search results are correct. However, it's not possible to efficiently prove that a new version of a prefix tree contains the same data as a previous version with only new values added. In the combined tree structure, which is based on , a prefix tree contains a mapping where each label-version pair is a search key, and its associated value is a cryptographic commitment to the label's new contents. A log tree contains a record of each version of the prefix tree that's created. With some caveats, this combined structure supports both efficient consistency proofs and can be efficiently searched. Note that, although the Transparency Log maintains a single logical prefix tree, each modification of this tree results in a new root hash, which is then stored in the log tree. Therefore, when instructions refer to "looking up a label-version pair in the prefix tree at a given log entry," this actually means searching in the specific version of the prefix tree that corresponds to the root hash stored at that log entry (where a "log entry" refers to a leaf of the log tree).

An example evolution of the combined tree structure, following the example from the beginning of the section. At every epoch, a new leaf is added to a log tree, containing a change to a label's value and the updated prefix tree (PT). k; h(PT_n)] [X:0->k; h(PT_n)] [Y:3->l; h(PT_n+1)] ]]>

Searching the Tree When searching the combined tree structure described in , the proof provided by the Transparency Log may either be full or abridged. A full proof must be provided if the deployment mode of the Transparency Log is Contact Monitoring, or if the user has specifically requested it. Otherwise, proofs are provided abridged. A full proof follows the path of a binary search for the first log entry where the prefix tree contains the desired label-version pair. This ensures that all users will check the same or similar entries when searching for the same label, allowing for efficient client-side auditing of the Transparency Log. The binary search uses an implicit binary search tree constructed over the leaves of the log tree (distinct from the structure of the log tree itself), which allows the search to have a complexity logarithmic in the number of the log's leaves. An abridged proof skips this binary search, and simply looks at the most recent version of the prefix tree to determine the commitment to the update that the user is looking for. Abridged proofs rely on a third-party auditor or manager that can be trusted not to collude with the Transparency Log, and who checks that every version of the prefix tree is constructed correctly. This is described in more detail in .

Implicit Binary Search Tree Intuitively, the leaves of the log tree can be considered a flat array representation of a binary tree. This structure is similar to the log tree, but distinguished by the fact that not all parent nodes have two children. In this representation, "leaf" nodes are stored in even-numbered indices, while "intermediate" nodes are stored in odd-numbered indices:

A binary tree constructed from 14 entries in a log Following the structure of this binary tree when executing searches makes auditing the Transparency Log much more efficient because users can easily reason about which nodes will be accessed when conducting a search. As such, only nodes along a specific search path need to be checked for correctness. The following Python code demonstrates the computations used for following this tree structure: > k) > 0: k += 1 return k-1 # The level of a node in the tree. Leaves are level 0, their parents # are level 1, etc. If a node's children are at different levels, # then its level is the max level of its children plus one. def level(x): if x & 0x01 == 0: return 0 k = 0 while ((x >> k) & 0x01) == 1: k += 1 return k # The root index of a search if the log has `n` entries. def root(n): return (1 << log2(n)) - 1 # The left child of an intermediate node. def left(x): k = level(x) if k == 0: raise Exception('leaf node has no children') return x ^ (0x01 << (k - 1)) # The right child of an intermediate node. def right(x, n): k = level(x) if k == 0: raise Exception('leaf node has no children') x = x ^ (0x03 << (k - 1)) while x >= n: x = left(x) return x ]]> The root function returns the index in the log at which a search should start. The left and right functions determine the subsequent index to be accessed, depending on whether the search moves left or right. For example, in a search where the log has 50 entries, instead of starting the search at the typical "middle" entry of 50/2 = 25, users would start at entry root(50) = 31. If the next step in the search is to move right, the next index to access would be right(31, 50) = 47. As more entries are added to the log, users will consistently revisit entries 31 and 47, while they may never revisit entry 25 after even a single new entry is added to the log.

Binary Ladder When executing searches on a Transparency Log, the implicit tree described in is navigated according to a binary search. At each individual log entry, the binary search needs to determine whether it should move left or right. That is, it needs to determine, out of the set of label-version pairs stored in the prefix tree, whether the highest version of a label that's present at a given log entry is greater than, equal to, or less than a target version. A binary ladder is a series of lookups in a single log entry's prefix tree, which is used to establish whether the target version of a label is present or not. It consists of the following lookups, stopping after the first lookup that produces a proof of non-inclusion:

First, version x of the label is looked up, where x is consecutively higher powers of two minus one (0, 1, 3, 7, ...). This is repeated until x is the largest such value less than or equal to the target version.
Second, the largest x that was looked up is retained, and consecutively smaller powers of two are added to it until it equals the target version. Each time a power of two is added, this version of the label is looked up.

As an example, if the target version of a label to lookup is 20, a binary ladder would consist of the following versions: 0, 1, 3, 7, 15, 19, 20. If all of the lookups succeed (i.e., result in proofs of inclusion), this indicates that the target version of the label exists in the log. If the ladder stops early because a proof of non-inclusion was produced, this indicates that the target version of the label did not exist, as of the given log entry. When executing a search in a Transparency Log for a specific version of a label, a binary ladder is provided for each node on the search path, verifiably guiding the search toward the log entry where the desired label-version pair was first inserted (and therefore, the log entry with the desired update). Requiring proof that this series of versions are present in the prefix tree, instead of requesting proof of just version 20, ensures that all users are able to agree on which version of the label is most recent, which is discussed further in the next section.

Most Recent Version Often, users wish to search for the "most recent" version of a label. That is, the label with the highest version possible. To determine this, users request a full binary ladder for each node on the frontier of the log. The frontier consists of the root node of a search, followed by the entries produced by repeatedly calling right until reaching the last entry of the log. Using the same example of a search where the log has 50 entries, the frontier would be entries: 31, 47, 49. A full binary ladder is similar to the binary ladder discussed in the previous section, except that it identifies the exact highest version of a label that exists, as of a particular log entry, rather than stopping at a target version. It consists of the following lookups:

First, version x of the label is looked up, where x is a consecutively higher power of two minus one (0, 1, 3, 7, ...). This is repeated until the first proof of non-inclusion is produced.
Once the first proof of non-inclusion is produced, a binary search is conducted between the highest version that was proved to be included, and the version that was proved to not be included. Each step of the binary search produces either a proof of inclusion or non-inclusion, which guides the search left or right, until it terminates.

For the purpose of finding the highest version possible, requesting a full binary ladder for each entry along the frontier is functionally the same as doing so for only the last log entry. However, inspecting the entire frontier allows the user to verify that the search path leading to the last log entry represents a monotonic series of version increases, which minimizes opportunities for log misbehavior. Once the user has verified that the frontier lookups are monotonic and determined the highest version, the user then continues a binary search for this specific version.

Putting it Together As noted at the beginning of the section, a search in the tree will either require producing a full proof, or an abridged proof may be accepted if the user can trust a third-party to audit and not collude with the Transparency Log. The steps for producing a full or abridged search proof are summarized as follows:

Full proof:
- If searching for the most recent version of a label, a full binary ladder is obtained for each node on the frontier of the log. This determines the highest version of the label available, which allows the search to proceed for this specific version.
- If searching for a specific version, the proof follows a binary search for the first entry in the log where this version of the label exists. For each step in the binary search, the proof contains a (non-full) binary ladder for the targeted version, which proves whether the targeted version of the label existed yet or not by this point in the log. This indicates whether the binary search should move forwards or backwards in the log.
Abridged proof:
- If searching for the most recent version of a label, a full binary ladder is obtained only from the last (most recent) entry of the log. The prefix tree entry for the most recent version of the label will contain the commitment to the update, ending the search.
- If searching for a specific version, a (non-full) binary ladder for this version is obtained only from the last entry of the log. Similar to the previous case, the prefix tree entry for the targeted version will contain the commitment to the update.

Monitoring the Tree As new entries are added to the log tree, the search path that's traversed to find a specific version of a label may change. New intermediate nodes may become established in between the search root and the leaf, or a new search root may be created. The goal of monitoring a label is to efficiently ensure that, when these new parent nodes are created, they're created correctly so that searches for the same versions continue converging to the same entries in the log. To monitor a given label, users maintain a small amount of state: a map from a position in the log to a version counter. The version counter is the highest version of the label that's been proven to exist at that log position. Users initially populate this map by setting the position of an entry they've looked up, to map to the version of the label stored in that entry. A map may track several different versions of a label simultaneously, if a user has been shown different versions of the same label. To update this map, users receive the most recent tree head from the server and follow these steps, for each entry in the map:

Compute the entry's direct path (in terms of the Implicit Binary Search Tree) based on the current tree size.
If there are no entries in the direct path that are to the right of the current entry, then skip updating this entry (there's no new information to update it with).
For each entry in the direct path that's to the right of the current entry, from low to high:
1. Receive and verify a binary ladder from that log entry, for the version currently in the map. This proves that, at the indicated log entry, the highest version present is greater than or equal to the previously-observed version.
2. If the above check was successful, remove the current position-version pair from the map and replace it with a position-version pair corresponding to the entry in the log that was just checked.

This algorithm progressively moves up the tree as new intermediate/root nodes are established and verifies that they're constructed correctly. Note that users can often execute this process with the output of Search or Update operations for a label, without waiting to make explicit Monitor queries. It is also worth noting that the work required to monitor several versions of the same label scales sublinearly, due to the fact that the direct paths of the different versions will often intersect. Intersections reduce the total number of entries in the map and therefore the amount of work that will be needed to monitor the label from then on. Finally, unlike searching, there is no abridged version of monitoring.

Ciphersuites Each Transparency Log uses a single fixed ciphersuite, chosen when the log is initially created, that specifies the following primitives to be used for cryptographic computations:

A hash algorithm
A signature algorithm
A Verifiable Random Function (VRF) algorithm

The hash algorithm is used for computing the intermediate and root values of hash trees. The signature algorithm is used for signatures from both the service operator and the third party, if one is present. The VRF is used for preserving the privacy of labels. One of the VRF algorithms from must be used. Ciphersuites are represented with the CipherSuite type. The ciphersuites are defined in .

Cryptographic Computations

Verifiable Random Function Each label-version pair created in a log will have a unique representation in the prefix tree. This is computed by providing the combined label and version as inputs to the VRF: ; uint32 version; } VrfInput; ]]> The VRF's output evaluated on VrfInput is the concrete value inserted into the prefix tree.

Commitment As discussed in , commitments are stored in the leaves of the log tree and correspond to updates. Commitments are computed with HMAC , using the hash function specified by the ciphersuite. To produce a new commitment, the application generates a random 16 byte value called opening and computes: where fixedKey is the 16 byte hex-decoded value: and CommitmentValue is specified as: ; opaque label<0..2^8-1>; UpdateValue update; } CommitmentValue; ]]> This fixed key allows the HMAC function, and thereby the commitment scheme, to be modeled as a random oracle. The label field of CommitmentValue contains the label being updated and the update field contains the new value for the label. The output value commitment may be published, while opening should be kept private until the commitment is meant to be revealed.

Prefix Tree The leaf nodes of a prefix tree are serialized as: ; uint64 update_index; } PrefixLeaf; ]]> where vrf_output is the VRF output for the label-version pair, VRF.Nh is the output size of the ciphersuite VRF in bytes, and update_index is the index of the log tree's leaf committing to the respective value, i.e., the log tree's tree_size just after the respective label-version pair was inserted minus one. The parent nodes of a prefix tree are serialized as: ; } PrefixParent; ]]> where Hash.Nh is the output length of the ciphersuite hash function. The value of a parent node is computed by hashing together the values of its left and right children: where Hash denotes the ciphersuite hash function.

Log Tree The leaf and parent nodes of a log tree are serialized as: ; opaque prefix_tree; } LogLeaf; struct { opaque value; } LogParent; ]]> The commitment field contains the output of evaluating HMAC on CommitmentValue, as described in . The prefix_tree field contains the root hash of the prefix tree, after inserting a new label-version pair for the label in CommitmentValue. The value of a parent node is computed by hashing together the values of its left and right children:

Tree Head Signature The head of a Transparency Log, which represents the log's most recent state, is represented as: ; } TreeHead; ]]> where tree_size counts the number of entries in the log tree. If the Transparency Log is deployed with Third-party Management then the public key used to verify the signature belongs to the third-party manager; otherwise the public key used belongs to the service operator. The signature itself is computed over a TreeHeadTBS structure, which incorporates the log's current state as well as long-term log configuration: ; opaque vrf_public_key<0..2^16-1>; select (Configuration.mode) { case contactMonitoring: case thirdPartyManagement: opaque leaf_public_key<0..2^16-1>; case thirdPartyAuditing: opaque auditor_public_key<0..2^16-1>; }; } Configuration; struct { Configuration config; uint64 tree_size; opaque root; } TreeHeadTBS; ]]>

Tree Proofs

Log Tree An inclusion proof for a single leaf in a log tree is given by providing the copath values of a leaf. Similarly, a bulk inclusion proof for any number of leaves is given by providing the fewest node values that can be hashed together with the specified leaves to produce the root value. Such a proof is encoded as: ; struct { NodeValue elements<0..2^16-1>; } InclusionProof; ]]> Each NodeValue is a uniform size, computed by passing the relevant LogLeaf or LogParent structures through the nodeValue function in . The contents of the elements array is kept in left-to-right order: if a node is present in the root's left subtree, its value must be listed before any values provided from nodes that are in the root's right subtree, and so on recursively. Consistency proofs are encoded similarly: ; } ConsistencyProof; ]]> Again, each NodeValue is computed by passing the relevant LogLeaf or LogParent structure through the nodeValue function. The nodes chosen correspond to those output by the algorithm in Section 2.1.2 of .

Prefix Tree A proof from a prefix tree authenticates that a set of values are either members of, or are not members of, the total set of values represented by the prefix tree. Such a proof is encoded as: ; NodeValue elements<0..2^16-1>; } PrefixProof; ]]> The results field contains the search result for each individual value. It is sorted lexicographically by corresponding value. The result_type field of each PrefixSearchResult struct indicates what the terminal node of the search for that value was:

inclusion for a leaf node matching the requested value.
nonInclusionLeaf for a leaf node not matching the requested value. In this case, the terminal node's value is provided given that it can not be inferred.
nonInclusionParent for a parent node that lacks the desired child.

The depth field indicates the depth of the terminal node of the search, and is provided to assist proof verification. The elements array consists of the fewest node values that can be hashed together with the provided leaves to produce the root. The contents of the elements array is kept in left-to-right order: if a node is present in the root's left subtree, its value must be listed before any values provided from nodes that are in the root's right subtree, and so on recursively. In the event that a node is not present, an all-zero byte string of length Hash.Nh is listed instead. The proof is verified by hashing together the provided elements, in the left/right arrangement dictated by the tree structure, and checking that the result equals the root value of the prefix tree.

Combined Tree

Proofs for Contact Monitoring A proof from a combined log and prefix tree follows the execution of a binary search through the leaves of the log tree, as described in . It is serialized as follows: ; } VRFProof; struct { PrefixProof prefix_proof; opaque commitment; } ProofStep; struct { optional version; VRFProof vrf_proofs<0..2^8-1>; ProofStep steps<0..2^8-1>; InclusionProof inclusion; } SearchProof; ]]> If searching for the most recent version of a label, the most recent version is provided in version. If searching for a specific version, this field is omitted. Each element of vrf_proofs contains the output of evaluating the VRF on a different version of the label. The versions chosen correspond either to the binary ladder described in (when searching for a specific version of a label), or to the full binary ladder described in (when searching for the most recent version of a label). The proofs are sorted from lowest version to highest version. Each ProofStep structure in steps is one log entry that was inspected as part of the binary search. The first step corresponds to the "middle" leaf of the log tree (calculated with the root function in ). From there, each subsequent step moves left or right in the tree, according to the procedure discussed in and . The prefix_proof field of a ProofStep is the output of executing a binary ladder, excluding any ladder steps for which a proof of inclusion is expected, and a proof of inclusion was already provided in a previous ProofStep for a log entry to the left of the current one. The commitment field of a ProofStep contains the commitment to the update at that leaf. The inclusion field of SearchProof contains a batch inclusion proof for all of the leaves accessed by the binary search. The proof can be verified by checking that:

The elements of steps represent a monotonic series over the leaves of the log, and
The steps array has the expected number of entries (no more or less than are necessary to execute the binary search).

Once the validity of the search steps has been established, the verifier can compute the root of each prefix tree represented by a prefix_proof and combine it with the corresponding commitment to obtain the value of each leaf. These leaf values can then be combined with the proof in inclusion to check that the output matches the root of the log tree.

Proofs for Third-Party Auditing In third-party auditing, clients can rely on the assumption that the prefix tree is monitored to be append-only. Therefore, they need not execute the binary ladder but the proof can directly jump to the index identified by the prefix tree leaf. version; VRFProof vrf_proofs<0..2^8-1>; PrefixProof prefix_proof; InclusionProof inclusion; } SearchProofCompact; ]]> The semantics of the version field do not change. Similarly to SearchProof, vrf_proofs contains the output of evaluating the VRF on a different version of the label. Either one version will be included (when requesting a specific version) or the versions to verify the full binary ladder (when requesting the latest version). prefix_proof contains the proof to either verify the inclusion of the label-version pair (when requesting a specific version) or to verify the full binary ladder (when requesting the latest version). Both types of proofs are for the most recent prefix tree. inclusion contains a batch inclusion of the most recent leaf and the leaf that commits to respective value for the request label-version pair. The most recent leaf is needed to obtain the prefix tree's root hash, and the leaf committing to the requested value will be at the index identified in the most recent prefix tree.

Update Format The updates committed to by a combined tree structure contain the new value of a label, along with additional information depending on the deployment mode of the Transparency Log. They are serialized as follows: ; }; } UpdatePrefix; struct { UpdatePrefix prefix; opaque value<0..2^32-1>; } UpdateValue; ]]> The value field contains the new value associated with the label. In the event that third-party management is used, the prefix field contains a signature from the service operator, using the public key from Configuration.leaf_public_key, over the following structure: ; uint32 version; opaque value<0..2^32-1>; } UpdateTBS; ]]> The label field contains the label being updated, version contains the new version, and value contains the same contents as UpdateValue.value. Clients MUST successfully verify this signature before consuming UpdateValue.value.

User Operations The basic user operations are organized as a request-response protocol between a user and the Transparency Log operator. Users MUST retain the most recent TreeHead they've successfully verified as part of any query response, and populate the last field of any query request with the tree_size from this TreeHead. This ensures that all operations performed by the user return consistent results. consistency; select (Configuration.mode) { case thirdPartyAuditing: AuditorTreeHead auditor_tree_head; }; } FullTreeHead; ]]> If last is present, then the Transparency Log MUST provide a consistency proof between the current tree and the tree when it was this size, in the consistency field of FullTreeHead.

Search Users initiate a Search operation by submitting a SearchRequest to the Transparency Log containing the label that they're interested in. Users can optionally specify a version of the label that they'd like to receive, if not the most recent one. last; opaque label<0..2^8-1>; optional version; } SearchRequest; ]]> In turn, the Transparency Log responds with a SearchResponse structure: ; UpdateValue value; } SearchResponse; ]]> Users verify a search response by following these steps:

Evaluate the search proof in search according to the steps in . This will produce a verdict as to whether the search was executed correctly and also a candidate root value for the tree. If it's determined that the search was executed incorrectly, abort with an error.
With the candidate root value for the tree, verify the given FullTreeHead.
Verify that the commitment in the terminal search step opens to SearchResponse.value with opening SearchResponse.opening.

Depending on the deployment mode of the Transparency Log, the value field may or may not require additional verification, specified in , before its contents may be consumed.

Update Users initiate an Update operation by submitting an UpdateRequest to the Transparency Log containing the new label and value to store. last; opaque label<0..2^8-1>; opaque value<0..2^32-1>; } UpdateRequest; ]]> If the request passes application-layer policy checks, the Transparency Log adds a new label-version pair to the prefix tree, followed by adding a new entry to the log tree with the associated value and updated prefix tree root. It returns an UpdateResponse structure: ; UpdatePrefix prefix; } UpdateResponse; ]]> Users verify the UpdateResponse as if it were a SearchResponse for the most recent version of label. To aid verification, the update response provides the UpdatePrefix structure necessary to reconstruct the UpdateValue.

Monitor Users initiate a Monitor operation by submitting a MonitorRequest to the Transparency Log containing information about the labels they wish to monitor. ; uint32 highest_version; uint64 entries<0..2^8-1>; } MonitorLabel; struct { optional last; MonitorLabel owned_labels<0..2^8-1>; MonitorLabel contact_labels<0..2^8-1>; } MonitorRequest; ]]> Users include each of the labels that they own in owned_labels. If the Transparency Log is deployed with Contact Monitoring (or simply if the user wants a higher degree of confidence in the log), they also include any labels they've looked up in contact_labels. Each MonitorLabel structure contains the label being monitored in label, the highest version of the label that the user has observed in highest_version, and a list of entries in the log tree corresponding to the keys of the map described in . The Transparency Log verifies the MonitorRequest by following these steps, for each MonitorLabel structure:

Verify that the requested labels in owned_labels and contact_labels are all distinct.
Verify that the user owns every label in owned_labels, and is allowed (or was previously allowed) to lookup every label in contact_labels, based on the application's policy.
Verify that the highest_version for each label is less than or equal to the most recent version of each label.
Verify that each entries array is sorted in ascending order, and that all entries are within the bounds of the log.
Verify each entry lies on the direct path of different versions of the label.

If the request is valid, the Transparency Log responds with a MonitorResponse structure: ; ProofStep steps<0..2^8-1>; } MonitorProof; struct { FullTreeHead full_tree_head; MonitorProof owned_proofs<0..2^8-1>; MonitorProof contact_proofs<0..2^8-1>; InclusionProof inclusion; } MonitorResponse; ]]> The elements of owned_proofs and contact_proofs correspond one-to-one with the elements of owned_labels and contact_labels. Each MonitorProof in contact_proofs is meant to convince the user that the label they looked up is still properly included in the log and has not been surreptitiously concealed. Each MonitorProof in owned_proofs conveys the same guarantee that no past lookups have been concealed, and also proves that MonitorProof.version is the most recent version of the label. The version field of a MonitorProof contains the version that was used for computing the binary ladder, and therefore the highest version of the label that will be proven to exist. The vrf_proofs field contains VRF proofs for different versions of the label, starting at the first version that's different between the binary ladders for MonitorLabel.highest_version and MonitorProof.version. The steps field of a MonitorProof contains the proofs required to update the user's monitoring data following the algorithm in . That is, each ProofStep of a MonitorProof contains a binary ladder for the version MonitorProof.version. The steps are provided in the order that they're consumed by the monitoring algorithm. If same proof is consumed by the monitoring algorithm multiple times, it is provided in the MonitorProof structure only the first time. For MonitorProof structures in owned_labels, it is also important to prove that MonitorProof.version is the highest version of the label available. This means that such a MonitorProof must contains full binary ladders for MonitorProof.version along the frontier of the log. As such, any ProofStep under the owned_labels field that's along the frontier of the log includes a full binary ladder for MonitorProof.version instead of a regular binary ladder. For additional entries on the frontier of the log that are to the right of the leftmost frontier entry already provided, an additional ProofStep is added to MonitorProof. This additional ProofStep contains only the proofs of non-inclusion from a full binary ladder. Users verify a MonitorResponse by following these steps:

Verify that the lengths of owned_proofs and contact_proofs are the same as the lengths of owned_labels and contact_labels.
For each MonitorProof structure, verify that MonitorProof.version is greater than or equal to the highest version of the label that's been previously observed.
For each MonitorProof structure, evalute the monitoring algorithm in . Abort with an error if the monitoring algorithm detects that the tree is constructed incorrectly, or if there are fewer or more steps provided than would be expected (keeping in mind that extra steps may be provided along the frontier of the log, if a MonitorProof is a member of owned_labels).
Construct a candidate root value for the tree by combining the PrefixProof and commitment of ProofStep, with the provided inclusion proof.
With the candidate root value, verify the provided FullTreeHead.

Some information is omitted from MonitorResponse in the interest of efficiency, due to the fact that the user would have already seen and verified it as part of conducting other queries. In particular, VRF proofs for different versions of each label are not provided, given that these can be cached from the original Search or Update query.

Security Considerations

IANA Considerations This document requests the creation of the following new IANA registries:

KT Ciphersuites ()

All of these registries should be under a heading of "Key Transparency", and assignments are made via the Specification Required policy . See for additional information about the KT Designated Experts (DEs). RFC EDITOR: Please replace XXXX throughout with the RFC number assigned to this document

KT Ciphersuites

KT Designated Expert Pool