Extended Functionality in Verifiable Searchable
Encryption
James Alderman∗, Christian Janson, Keith M. Martin, and Sarah Louise Renwick†
Information Security Group, Royal Holloway, University of London Egham, Surrey, TW20 0EX, United Kingdom
{James.Alderman, Keith.Martin}@rhul.ac.uk
{Christian.Janson.2012, SarahLouise.Renwick.2012}@live.rhul.ac.uk
Abstract. When outsourcing the storage of sensitive data to an (un-trusted) remote server, a data owner may choose to encrypt the data beforehand to preserve confidentiality. However, it is then difficult to efficiently retrieve specific portions of the data as the server is unable to identify the relevant information. Searchable encryption has been well studied as a solution to this problem, allowing data owners and other au-thorised users to generate search queries which the server may execute over theencrypted data to identify relevant data portions.
However, many current schemes lack two important properties: verifia-bility of search results, and expressive queries. We introduce Extended Verifiable Searchable Encryption (eVSE) that permits a user to verify that search results are correct and complete. We also permit verifiable computational queries over keywords and specific data values, that go be-yond the standard keyword matching queries to allow functions such as averaging or counting operations. We formally define the notion of eVSE within relevant security models and give a provably secure instantiation.
1
Introduction
It is now common for data owners to outsource their data to public servers providing storage on a pay-as-you-go basis. This can reduce the costs of data storage compared with that of running a private data centre (e.g. hardware, construction, air conditioning and security costs), making this a cost effective solution. If the server is not fully trusted and the data is of a sensitive nature, the data owner may wish to encrypt it to ensure confidentiality. This, however, prevents the efficient retrieval of specific portions of the data as the server is unable to identify the relevant information.
Searchable Encryption (SE) [11, 16, 19, 22, 23, 25, 27, 34] addresses this issue by indexing the encrypted data in such a way as to allow a server to execute
∗
Supported by the European Commission under project H2020-644024 “CLARUS” and acknowledges support from BAE Systems Advanced Technology Centre.
†
a search query (formed by the data owner or an authorised data user) over the encrypted data and return the identifiers of any file that satisfies the search query.
To preserve confidentiality of the data, the server must not learn anything about the underlying data from the encrypted data and the data indexes; namely ciphertext indistinguishability andindex indistinguishability. In the presence of a search query the only information leaked to the server is the search results. Query indistinguishabilityis also a desirable property although, due to theoffline keyword guessing attack [12], this is not always easy to achieve in the public key setting (where indexes are generated using the data owner’s public key).
The majority of existing work on SE focusses on efficiently preserving confi-dentiality in the presence of anhonest-but-curious server. This means that the server is trusted to follow the search protocol honestly but may try to infer information about data or search queries that it is unauthorised to know.
Verifiable Searchable Encryption (VSE) [13, 26, 32, 37, 39] assumes a stronger semi-honest-but-curious adversarial model in which the server might execute only a fraction of the search, or return a fraction of the search results in order to preserve its resources. To ensure the completeness and correctness of search results in this scenario, it is required that the server is able to prove to the querier that the search was computed honestly.
The current approaches to VSE in the literature do not support a wide range of expressive search queries. We address this issue by extending the types of queries that can be executed and verified by a VSE scheme to include more expressive search queries, as well as some computations. Most VSE schemes in the literature also require that the verification of query results be performed by the entity that issued the query whereas eVSE is publicly and blindly verifiable.
1.1 Our Contributions
We adapt and apply new techniques from the area of Publicly Verifiable Out-sourced Computation to VSE in a novel way to enable a wider family of queries, and some types of computations, to be performed over outsourced encrypted data with verifiable query results. In summary, our contributions are:
– More expressive queries: Our scheme supports queries such as boolean formu-lae involving conjunctions, disjunctions and negations, threshold operations, polynomials, arbitrary CNF and DNF formulae, and fuzzy search1.
– Evaluation of computations: Our scheme supports the evaluation of some computations over the encrypted data, such as averaging and counting oper-ations. As well as assigning keywords to label data, we propose to also assign keywords representing certain data values that may be computed over (either in the form of single keywords or as a string of keywords encoding binary data, see Section 3.3).
1
– Blind public verifiability of query results: Any entity is able to verify the cor-rectness and completeness of query results without any knowledge of either the underlying query or the results themselves.
The remainder of this paper is organised as follows. Section 2 gives some background information on SE and verifiable computation. Section 3 formally defines eVSE and its security model, Section 4 gives an instantiation of eVSE and Section 5 concludes the paper, highlighting possible avenues of future research. The Appendix provides some background information and the security proofs.
2
Background
Searchable encryption (SE) allows data to be outsourced in encrypted form and for keyword search queries to be performed remotely. Methods based on oblivious RAM [20] provide a high level of security (hiding both the access and search patterns) at the expense of slow search times and high communication costs. Song et al. [30] achieve a scheme with fewer rounds of communication, but which leaks the access pattern and requires each word of a document to be en-crypted separately, so compression is not possible. Goh [19] introduced meta data (indexes) describing the content of each document, and enabled constant time searches using Bloom filters over the index only. Curtmola et al. [16] extended the system model to allow multiple users to query the data, using broadcast encryption to manage user access privileges. SE schemes that allow many users to upload data can be built using public key encryption, however the data can only be searched by the holder of the corresponding secret key (or a derivative thereof) [11]. Most SE schemes assume an honest-but-curious server model.
Verifiable searchable encryption (VSE) schemes assume a semi-honest-but-curious server model. The first VSE scheme was presented by Chai et al. [13], where they extend the paradigm of searchable symmetric encryption (SSE) [16] to create a verifiable SSE (VSSE) scheme that allows verification of search results from a single keyword equality query. Another approach by [26] extends a public key encryption with keyword search scheme [11] to support verification of search results from a single keyword equality query, where the indexes are created using a public key. Sun et al. [32] and Wang et al. [36] detail VSE schemes with enhanced functionality; verifiable multi-keyword ranked search and verifiable fuzzy keyword search, respectively.
query computations on data held by the server (or initially outsourced by a client) called Verifiable Delegable Computation (VDC). This can naturally be applied to problems like querying on remote data, as well as MapReduce. Data remains statically stored on the server and may be embedded in a server’s secret key, whilst the computation of many different functions can be requested by creating ciphertexts usingonly public information. Other notable approaches in the realm of querying remote data can be found in [3–5, 8–10, 15].
3
Extended Verifiable Searchable Encryption
3.1 System Model
We consider a system comprising adata owner, a remote storageserver, and a set of authoriseddata users. The data owner sets up the system to generate a master secret and holds a set of data D (e.g. a database) that they wish to encrypt and outsource to the remote server. The data owner controls which additional users are able to query their encrypted data. Queries may be formulated over these keywords (e.g. to identify records associated with a given set of keywords) as usual in SE, but we also allow computational queries of functions in the classN C1, which consists of Boolean functions computable by circuits of depth
O(logn) where each gate has a fan-in of two, over encoded data values.
For example consider workgroups within an organisation. The manager or system administrator acts as the data owner for the organisation and outsources a shared database to a remote server. Authorisation is granted by issuing a secret key to each user, which is required when creating a query tokenQTQ for
a particular query Q. The token is sent to the server who performs the query on the encoded index to generate a resultR. We allowany entity to verify the correctness and completeness of the result2, but we restrict the ability to read the value of the result to only authorised data users (holding a retrieval key).
Throughout this work, we assume a strict separation betweenqueriers (the data owner and users) and the remote server – the server may not issue queries itself, else it will trivially be able to learn the encoding of the index and queries (legitimate queriers must know this encoding to gain meaningful results).
3.2 Formal Definition
We now formally define a scheme for eVSE. We use the following notation. Data to be outsourced is denoted D and is considered to be a collection of n documents. Prior to outsourcing, the data owner specifies a pre-index for D, denoted δ(D), which assigns a set of descriptive labels to each document e.g. keywords contained in the document or specific data values that may be computed upon. The encoded form of the data, including the descriptive labels, is referred to as theindex ofD, denotedID, and is stored by the server. Queries
2
for functions in the class N C1 are denoted byQ and to make such a query, a data user creates a query tokenQTQforQ, a verification keyV KQwhich allows
any entity to blindly verify the result,R, of the query, and a retrieval key RKQ
which is issued to authorised data users to enable the query result to be learnt.
Definition 1. An Extended Verifiable Searchable Encryption (eVSE) scheme comprises the following algorithms:
– (MK,PP) ←$ Setup(1κ,U) : Run by the data owner and takes as input the
security parameter and a universe of attributes (keywords and data values). It outputs the data owner’s master secret key MK that is used for further administrative tasks and public parameters PP, both of which are provided to the remaining algorithms where required.
– (ID, sts, sto) $
←BuildIndex(δ(D), G,MK,PP) : Run by the data owner and takes as input the pre-index of the dataδ(D) and the set G of authorised users, and outputs a searchable indexIDfor the dataD, as well as a server
and data owner state.
– (SKID, sts) $
←AddUser(ID, G,MK,PP) : Run by the data owner to authorise a user ID to perform queries by issuing them a secret keySKID and outputs an updated server state.
– (QTQ, V KQ, RKQ) $
← Query(Q, sts, sto, SKID,PP) : Run by a data user
using its secret key and both states to generate a query token QTQ for a
queryQ, a verification keyV KQ and an output retrieval keyRKQ.
– R←$ Search(ID, QTQ, sts, SKS,PP) : Run by the server to execute a query
given in the query tokenQTQon the indexID. It generates a resultRwhich
can be returned to the querying user or published.
– r←Verify(R, V KQ, RTQ, RKQ,PP) : Verification consists of two steps:
1. RTQ←BVerif(R, V KQ,PP) : Run byanyparty to verify the correctness
and completeness of the resultR. It takes the verification keyV KQ and,
if the result is accepted, it outputs a retrieval token RTQ which can
be used to learn the result. Otherwise a distinguished failure symbol RTQ=⊥is returned.
2. r ← Retrieve(V KQ, RTQ, RKQ,PP) : Run by a data user to read the
value of the result. It takes as input the retrieval tokenRTQ, the retrieval
keyRKQand the user’s secret key. If the user holds a valid retrieval key
forQand the computation was performed correctly, then it returns the actual resultr=Q(ID), otherwise it returnsr=⊥.
– (sts, sto) $
← RevokeUser(ID, G,MK,PP) : Run by the data owner using its master secret key to revoke a user’s authorisation to make queries and read results. It does so by updating the server and data owner state.
3.3 Types of Query
We consider a broader range of verifiable queries than many prior schemes. In particular, we consider two main types:
– Keyword matching queries: Queries of this type have formed the basis of most prior work in SE. Suppose there exists a universe (dictionary) of keywords. Each encrypted data item is associated with anindex of one or more keywords to describe the contents. Queries are formed over the same universe of keywords. In this work, we permit Boolean formulae over sets of keywords (e.g. ((a∧b)∨c) where a,b,c are keywords). We return an identifier for each file whose associated keywords in the index satisfy this formula. Thus we can perform very expressive search queries over keywords.
– Computational queries: Queries of this type are similar to the operations commonly discussed in the context of outsourced computation. We allow statistical queries over keywords (e.g. counting the number of data items that satisfy a keyword matching query), as well as operations over selected data values that have been encoded using additional portions of the keyword universe. It is possible to encode the entire database in such a way as to en-able computations over all data fields, but it would usually be more efficient to select a (small) subset of fields that are most useful or most frequently queried. Clearly, keyword matching queries can be seen as a special case of computational queries where the function operator is equality testing.
– Mixed queries: Queries of this type combine both the functionalities of the aforementioned query types (e.g. finding the average of data values contained in all documents associated with a particular keyword).
All types of query are performed in a verifiable manner to ensure that results are correct and complete.
3.4 Security Model
We now formalise several notions of security as a series of cryptographic games. The adversary against each notion is modelled as a probabilistic polynomial time (PPT) algorithmArun by a challenger, with input parameters chosen to represent the knowledge of a real attacker as well as the security parameter κ. The adversary algorithm may maintain state and be multi-stage; we refer to each stage as A for ease of notation. The notation AO denotes the adversary being provided with oracle access to the following algorithms:BuildIndex(·,·,MK,PP),
AddUser(·,·,MK,PP),Query(·,·,·,·,PP) andSearch(·,·,·,·,PP). We assume that oracle queries are performed in a logical order such that all required information is generated from previous queries. For each game, we define theadvantage and security ofAas:
Definition 2. The advantageof a PPT adversaryAis defined as follows, where X∈ {PubVerif,IndPriv,QueryPriv}:
AdvX
A(eVSE,1κ) = Pr[Exp X
Game 1 ExpPubVerifA [eVSE,1κ]:
1: (Q, δ(D?))← A(1κ)
2: (PP,MK)←Setup(1κ,U)
3: G← ∅ 4: ID←$ Users
5: (SKID, sts)←AddUser(ID, G,MK,PP)
6: (ID?, sts, sto)←BuildIndex(δ(D?), G,MK,PP)
7: (QTQ, V KQ, RKQ)←Query(Q, sts, sto, SKID,PP)
8: R?← AO(QT
Q, V KQ, RKQ,ID?,PP) 9: RTQ←BVerif(R?, V KQ,PP)
10: r←Retrieve(V KQ, RTQ, RKQ,PP)
11: if(r6=⊥)and(r6=Q(ID?))then return1
12: else return0
An eVSE scheme is secure against Game X if for all PPT adversaries A, AdvXA(eVSE,1κ)≤negl(κ)where neglis a negligible function.
Public Verifiability. In Game 1, we capture the notion ofpublic verifiability such that a server may not cheat by returning an incorrect result without being detected. This is a selective notion of security where, at the beginning of the game, the adversary chooses the challenge query and pre-index. The challenger then initialises the system, runs AddUser for a randomly chosen ID from the userspace, runs BuildIndexfor the challenge pre-index to create the index, and finally runs Query. The adversary is given the resulting parameters, as well as access to the above specified oracle queries, and outputs R?, which it believes
to be an incorrect result that will, nevertheless, be accepted by the verifier. The challenger runs the verification steps on this output. The adversary wins if verification succeeds, yet the result is notQ(ID?).
Index Privacy and Query Privacy. In Appendix C, we provide notions of index indistinguishability against a selective chosen keyword attack and query privacy, which ensure that no information regarding the keywords is leaked from the index or query tokens respectively.
4
Construction
4.1 Overview
We consider the familyB of Boolean functions closed under complement – that is, if F ∈ B then F, where F(x) = F(x)⊕1, is also in B. A function F : {0,1}n → {0,1} is monotonic if x
6 y implies F(x) 6 F(y), where x = (x1, . . . , xn)≤y = (y1, . . . , yn) if and only if xi 6yi for all i. For a monotonic
functionF, the set AF ={x:F(x) = 1}defines a monotonic access structure.
A query Q is represented as a Boolean function of keywords and compu-tational data points. If a monotonic CP-ABE scheme is used then queries can be comprised of AND and OR gates (and negation can inefficiently be handled by including both a positively and negatively labelled attribute in the universe and requiring the presence of exactly one of them). A non-monotonic CP-ABE scheme enables queries formed fromAND,ORandNOTgates, which is a universal set of gates, and fuzzy CP-ABE enables fuzzy keyword search. We can achieve all functions in the classN C1, which includes common arithmetic and compar-ison operators useful in queries. Ann-bit result can be formed by performingn Boolean queries, each of which returns theithbit of the output.
The query token for a Boolean functionQ∈ Bcomprises two CP-ABE cipher-texts for access structures representing Q and Q ∈ B respectively. To perform the search, the server attempts to decrypt each ciphertext under the secret key (associated with the pre-index) and outputs the result. Each decryption succeeds if and only if the query evaluates to True on the index. Any entity may perform the blind verification operation using the verification key to learn only whether the operation was performed correctly or not. Only entities holding the retrieval token can read the value of the result.
4.2 Data Encoding
Defining the Index. Suppose the dataD to be outsourced comprisesn doc-uments. We now discuss how to form a pre-index δ(D), which represents the keywords and data fields that may be queried over.
Let D be a dictionary of keywords that describe the documents. D alone suffices for keyword matching queries but for computational queries, we also need to be able to encode data values such that they can be input to queries represented as access structures encoding Boolean functions.
For each data field xthat may be input to a computational query, let the maximum size of the data value bemx bits. We definemx additional attributes
Ax,1, Ax,2, . . . , Ax,mx, and define the universe C =
S x∈D∪
mx
i=1Ax,i to be the
union of these attributes over all data fields. Lety be a value stored in the data field x and let the binary representation of y be y1, . . . , ymx. We view y as a characteristic tuple of an attribute setAy⊆ C, whereAy={Ax,i:yi= 1} – we
include an attribute for positioniin the set if and only if theithbit of yis 1.
particular keyword or data value, and each copy relates to a different document in D - if we index each copy of an attributew ∈ {D ∪ C} as {wi}ni=1, thenwi
denotes the presence ofwin documenti. In practice, it may be desirable to use a ‘large universe’ CP-ABE scheme, wherein arbitrary textual strings are mapped to attributes (group elements), e.g. using a hash functionH. Thus, for a keyword or data valuewin document i, the attribute could be defined asH(w||i).3
The pre-index of the dataD is a set of attributesδ(D)⊆ U. The index that is outsourced will be a CP-ABE key generated over this attribute set.
Hiding the Index. In general, CP-ABE schemes do not hide the attributes within the decryption key. This is usually expected behaviour since CP-ABE is often used to cryptographically enforce access control policies and it is natural to assume that an entity is aware of their access rights.
However, in this setting we are using CP-ABE not to protect objects from unauthorised access, but instead to prove the outcome of a function evaluation. The keys in our setting are formed over attributes encoding the index of out-sourced data, as opposed to encoding access rights. Since the server should not learn any information about the data, including the index, we must implement a mechanism by which the decryption key hides the associated attributes.
In many CP-ABE schemes, the public parameters comprise an ordered set of group elements [38], each associated with an attribute from the universe; that is, ∀i ∈ U, chooseti
$
←Zp, then form the encoded attribute set {gti}i∈U. Thus, given a key (or ciphertext) that comprisesgti, it is possible, based on the ordering of this set, to determine the attribute i∈ U it relates to. In addition, the attributes may be listed in the clear, and attached to keys and ciphertexts to indicate which group elements should be applied at each point. Clearly, this is unsuitable for our requirement for a hidden index.
To this end, we first apply a random permutation toU such that the position of the group elements within the ordered set does not reveal the attribute string (unless the permutation is known). We then use a symmetric encryption scheme to encrypt each attributex∈ U under a keyk, and then instantiate the CP-ABE scheme on this universe ofencrypted attributes. Thus, without knowledge of the key k, the server should be unable to determine the attribute x that a given group element corresponds to. We assume that only the keywords or data items being computed over are considered sensitive, and not the logical makeup of the Boolean function (in terms of gates).
4.3 Formal Details
The data owner initialises the system and encodes the data as an index which is pushed to the server. Each (authorised) user will be issued with a personalised secret key enabling them to form queries. To make a queryQ, a user chooses a
3
random message from the message spaceMto act as a verification token, and encrypt this using the CP-ABE scheme under the access structure encodingQ. The server attempts to decrypt the ciphertext and recovers the chosen message if and only if Q(ID) = 1. By the indistinguishability security of the CP-ABE
scheme, the server learns nothing about the message if Q(ID) = 0 since this
corresponds to an access structure not being satisfied. Thus, if a server returns the correct message, the user is assured that the query evaluated to 1 on the data. If, however,Q(ID) = 0, then decryption will return⊥. This is insufficient
for verification purposes since the server can return ⊥ to convince a user of a false negative search result. Thus, the user must, in fact, produce two CP-ABE ciphertexts. As above, one corresponds to the functionQ, whilst the other cor-responds toQ, the complement query ofQ. Hence, the server’s key will decrypt exactly oneciphertext and the returned message will distinguish whetherQorQ was satisfied, and therefore the value ofQ(ID). A well-formed response (d0, d1) from a server, therefore, satisfies the following:
(d0, d1) =
(
(m0,⊥), ifQ(ID) = 1
(⊥, m1), ifQ(ID) = 0.
(1)
Public Verifiability is achieved by publishing a token comprising a one-way func-tiongapplied to both plaintexts. Any entity can applygto the server’s response and compare with this token to check correctness. To achieve blind verification, a random bitbpermutes the order of the ciphertexts. Thus, verifiers that do not knowb cannot determine whether a plaintext is associated withQor Q.
Our adversarial model allows the adversary (and hence servers in our system) to hold more than one key (for multiple datasets); we must ensure that a key can-not produce a valid looking response to a query on a different index. We achieve this by labelling each pre-index with a labell(δ(D)) and define an attribute for each label. Then, for a pre-index δ(D), the decryption key is formed over the attribute set (δ(D)∪l(δ(D))). Recall that encoded data stored on the server’s side is a collection ofndocuments, which we label D1, . . . , Dn. When making a
queryQ(ID), a sub-queryQi may be formed for each document (e.g. to check
if a given keyword is contained in each document). In this case, the encryption algorithm takes the access structure encoding of the conjunction (Di∧l(δ(D)))
fori∈[n]. A valid result can only be formed by applying the sub-query to the specified document, which is also labelled by Di ∈ D – decryption succeeds if
and only if the function is satisfiedand the labell(δ(D)) is matched in the key and ciphertext. Note that a key for a different pre-index will not include the correct label. Inputs to theQuery algorithm are assumed to be in this form.
Let CPABE = (ABE.Setup, ABE.KeyGen, ABE.Encrypt, ABE.Decrypt) de-fine a CP-ABE encryption scheme over the universe U. Let SE= (SE.KeyGen,
SE.Encrypt, SE.Decrypt) be an authenticated symmetric encryption scheme se-cure [6] in the sense ofIND-CPA. LetBE = (BE.KeyGen, BE.Encrypt,BE.Add,
letΠ andφbe pseudo-random permutations (PRPs) (which pad their inputs if required). Then Algorithms 1–8 define an eVSE scheme for a class of queriesQ. Alg. 1 (MK,PP)←Setup(1κ,U)
1: mk←BE.KeyGen(1κ)
2: k←SE.KeyGen(1κ)
3: fori∈ Udo
4: ui←SE.Encrypt(i, k)
5: U0← {u
i}i∈U
6: U ←˜ Π(U0)
7: (M SKABE, M P KABE)←ABE.Setup(1κ,U)˜ 8: PP←(M P KABE,U)˜
9: MK←(M SKABE, mk, k, Π)
Alg. 2 (ID, sts, sto)←BuildIndex(δ(D), G,MK,PP)
1: ID←ABE.KeyGen((δ(D)∪l(δ(D))), M SKABE, M P KABE)
2: j← {0$ ,1}κ
3: sts←BE.Encrypt(G, j, mk)
4: sto←j
Alg. 3 (SKID, sts)←AddUser(ID, G,MK,PP)
1: ukID←BE.Add(ID,mk)
2: ifID is a userthen SKID←(ukID, k, Π)
3: elseSKID←ukID
4: sts←BE.Encrypt(G∪ID,j,mk)
Alg. 4 (QTQ, V KQ, RKQ)←Query(Q={Qi}, sts, sto, SKu,PP)
1:ej←BE.Decrypt(sts, ukID)
2: if(ej6=sto)then return⊥
3: fori= 1to|Q|do
4: (m0i, m1i)
$
← M × M
5: bi $
← {0,1}
6: cbi←ABE.Encrypt(mbi, Qi, M P KABE)
7: c1−bi←ABE.Encrypt(m1−bi, Qi, M P KABE)
8: QTQi←(cbi, c1−bi) 9: γi←φj(cbikc1−bi) 10: V KQi←(g(m0i), g(m1i)) 11: RKQi←bi
12: QTQ← {γi},V KQ← {V KQi},RKQ← {RKQi} Alg. 5 R←Search(ID, QTQ={γi}, sts, SKS,PP)
1:ej←BE.Decrypt(sts, ukS)
2: if(ej6=sts)then return⊥
3: fori= 1to|Q|do
4: (cbikc1−bi)←φ −1
e j (γi)
5: dbi←ABE.Decrypt(cbi,ID, M P KABE)
6: d1−bi←ABE.Decrypt(c1−bi,ID, M P KABE)
Alg. 6 RTQ←BVerif(R={(di, di0)}, V KQ={(V Ki, V Ki0)},PP)
1: fori= 1to|Q|do
2: ifV Ki=g(di)thenRTQi=di 3: else ifV Ki0=g(d0i)thenRTQi=d
0
i
4: elseRTQi=⊥ 5: RTQ={RTQi}
Alg. 7 r←Retrieve(V KQ={(g(mbi), g(m1−bi))}, RTQ={RTQi}, RKQ={bi},PP) 1: fori= 1to|Q|do
2: ifg(RTQi) =g(m0)thenri= 1 3: else ifg(RTQi) =g(m1)thenri= 0 4: elseri=⊥
5: r={ri}
Alg. 8 (sts, sto)←RevokeUser(ID, G,MK,PP)
1: j0 $
← {0,1}κ
2: sts←BE.Encrypt(G\ID,j0,mk)
3: sto←j0
Theorem 1. Given a selective IND-CPAsecure CP-ABE scheme, an authen-ticated symmetric encryption scheme and a broadcast encryption scheme, both secure in the sense of IND-CPA, pseudo-random permutations Π and φ, and a one-way functiong. LeteVSE be the extended verifiable searchable encryption scheme defined in algorithms 1–8. Then eVSE is secure in the sense of Public Verifiability, Index Privacy and Query Privacy.
The proofs can be found in Appendix D and in Appendix E we discuss the trade-off between efficiency and functionality of our scheme. Note that we can add additional contextual access control following Alderman et al. [1] by replacingφwith akey assignment scheme.
5
Conclusion
With this work we have begun to consider the application of VC techniques in the setting of searchable encryption. On the searchable encryption side, this enables additional functionality in the form of computational queries (e.g. computing the average of outsourced data fields that are linked to a specific set of keywords), whilst on the VC side, this introduces additional privacy concerns regarding the outsourced data and computations. The choice of using VC techniques based on ABE stems from the natural correspondence between attributes and keywords in an index. However, future work should investigate other forms of VC to achieve different classes of functionality and (especially) improve efficiency.
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A
Background
A.1 Ciphertext-Policy Attribute-based Encryption
In Ciphertext-Policy Attribute-based Encryption (CP-ABE), attributes are as-signed to users and each ciphertext is associated with an access structure.
Definition 3. LetU be a universe of attributes. ACiphertext-Policy Attribute-based Encryption scheme[21] for U comprises four algorithms as follows:
– (PK,MK)←$ Setup(1κ): initialises the system using the security parameter to generate a public keyPK and master secret keyMK.
Game 2 ExpsIND-CPA
A [CPABE,1κ]: 1: A?← A(1κ)
2: (PK,MK)←Setup(1κ)
3: (m0, m1)← AO
KeyGen(·,MK,PK)
(PK) 4: b← {0$ ,1}
5: CT?←Encrypt(
A?, mb,PK)
6: b0← AOKeyGen(·,MK,PK)
(CT?,PK)
7: return (b0=b)
Oracle Query 1 OKeyGen(S,MK,PK):
1: ifS /∈A?then returnSKS←KeyGen(S,MK,PK)
2: else return⊥
– SKS $
←KeyGen(S,MK,PK): takes an attribute set S, the master secret key and the public key, and outputs a secret decryption keySKS.
– P T ←Decrypt(SKS, CTA,PK): takes a secret key, a ciphertext and the public key, and outputs the plaintextP T =mif and only if the attributesS satisfy the access structureA– that is,S∈A. Otherwise, P T =⊥.
Selective security for CP-ABE is defined in Game 2.
B
Additional Details for eVSE
B.1 Correctness Definition
Definition 4. A Extended Verifiable Searchable Encryption scheme is correct for a family of queriesQ if for all queriesQ∈ Q:
Pr[(MK,PP)←$ Setup(1κ,U),
(ID, sts, sto)
$
←BuildIndex(δ(D), G,MK,PP),
(SKID, sts)
$
←AddUser(ID, G,MK,PP),
(QTQ, V KQ, RKQ)
$
←Query(Q, sts, sto, SKID,PP),
R←$ Search(ID, QTQ, sts, SKS,PP), RTQ ←BVerif(R, V KQ,PP),
Q(ID)←Retrieve(V KQ, RTQ, RKQ,PP)]
= 1−negl(κ).
B.2 Example: Defining the Index
Here we provide a simple example that shows how we define the index. Suppose we have 3 documents with the following characteristics:
– Document 1:Keywords: Male, Vaccinated.Data: Age = 7 = 1112. – Document 2:Keywords: Female.Data: Age = 4 = 1002.
-Then,
D={Male,Female,Vaccinated},
C={AAge,1,AAge,2,AAge,3},
U ={MaleDoc1,MaleDoc2,MaleDoc3,
FemaleDoc1,FemaleDoc2,FemaleDoc3,
VaccinatedDoc1,VaccinatedDoc2,VaccinatedDoc3,
A(Age,1),Doc1,A(Age,1),Doc2,A(Age,1),Doc3,
A(Age,2),Doc1,A(Age,2),Doc2,A(Age,2),Doc3,
A(Age,3),Doc1,A(Age,3),Doc2,A(Age,3),Doc3},
δ(D) ={MaleDoc1,VaccinatedDoc1,A(Age,1),Doc1,A(Age,2),Doc1,A(Age,3),Doc1,
FemaleDoc2,A(Age,3),Doc2,
MaleDoc3,VaccinatedDoc3}.
C
Security Models
C.1 Index Privacy
In Game 3, we formalise the notion of index indistinguishability against a se-lective chosen keyword attack, which ensures no information regarding the key-words is leaked from the index. Firstly the adversary outputs two sets of at-tributes (D0, D1 ⊆ U) that they wish to be challenged on, with the restriction that |D0| = |D1| (this is required as the CP-ABE used to produce the index does not conceal the index length). The challenger runs Setup to produce the public and secret parameters. The challenger selects a bit b∈ {0,1} uniformly at random to select which set of attributes to encode into the index. Before the index is created, the challenger needs to create the pre-index from the set of attributesDb (line 4 of Game 2). This is done using anEncodemechanism that
takes the elements of Db as input and outputs the pre-index δ(Db). Encode is
not required in our instantiation as the pre-indexes can be chosen directly from ˜
U as the user knows the mapping from U to U0 and the permutation Π; the adversary however does not. The challenger then runs BuildIndex using δ(Db)
to produce the index IDb, which is given to A. The adversary is then given PP and oracle access, with the restriction that the query results are identi-cal for each index ID0,ID1, i.e. if R0 ← Search(ID0, QTQ, sts, SKS,PP) and
R1 ←Search(ID1, QTQ, sts, SKS,PP) then we needR0=R1. After this query
phase,Aoutputs a guess b0 and wins the game if the comparison operator == returns 1 which indicates thatb0 =b. HenceAwins the game if they can identify which attribute set (D0or D1) was encoded into the indexIDb.
C.2 Query Privacy
Game 3 ExpIndPrivA [eVSE,1κ]:
1: (D0, D1, Q)← A(1κ,U)
2: if(|D0| 6=|D1|)then return⊥
3: b← {0$ ,1}
4: (MK,PP)←Setup(1κ,U)
5: G← ∅ 6: ID←$ Users
7: (SKID, sts)←AddUser(ID, G,MK,PP)
8: δ(Db)←Encode(Db)
9: (IDb, sts, sto)←BuildIndex(δ(Db), G,MK,PP)
10: b0← AO(I
Db, sts,PP) 11: return (b0==b)
Game 4 ExpQueryPrivA [eVSE,1κ]: 1: (Q0, Q1)← A(1κ,U)
2: if(GQ06=GQ1)then return⊥
3: b← {0$ ,1}
4: (MK,PP)←Setup(1κ,U)
5: G← ∅ 6: ID←$ Users
7: (SKID, sts)←AddUser(ID, G,MK,PP)
8: δ(Db) $
←U˜
9: (ID, sts, sto)←BuildIndex(δ(D), G,MK,PP)
10: Q˜
b←Encode(Qb)
11: (QTQb, V KQb, RKQb)←Query( ˜Qb, sts, sto, SKID,PP) 12: b0← AO(QT
Qb, V KQb, RKQb,ID, sts,PP)
13: return (b0==b)
gates, but not the keywords themselves. This notion of query indistinguishability against a selective chosen query attack is formalised in Game 4. The game runs similarly to that of Game 3, subject to the following restrictions: the challenge queries (Q0, Q1) must use the same gates. We denote the gate structure of a queryQbyGQ, and hence require that GQ0 =GQ1.
D
Security Proofs
Lemma 1. eVSE as defined in algorithms 1–8 is secure against Public Verifia-bility (Game 1) under the same assumptions as in Theorem 1.
Proof. SupposeAeV SEis an adversary with non-negligible advantage against the
selective Public Verifiability game (Game 1) when instantiated with Algorithms 1–8. We begin by defining the following three games:
– Game A.This is the selective Public Verifiability game as defined in Game 1.
– Game B.This is the same asGame Awith the modification that inQuery, we no longer return an encryption ofm0 andm1.
Instead, we choose another random messagem06=m0, m1and, ifQ(ID) = 1,
ABE.Encrypt(Q, m0, M P KABE). In other words, we replace the ciphertext associated with the unsatisfied function with the encryption of a separate random message unrelated to the other system parameters, and in particular to the verification keys.
– Game C. This is the same as Game B with the exception that instead of choosing a random messagem0, we implicitly setm0 to be the challenge inputwin the one-way function game.
We show that an adversary with non-negligible advantage against the selective Public Verifiability game can be used to construct an adversary that may invert the one-way functiong.
Game A toGame B. We begin by showing that there is a negligible distin-guishing advantage betweenGame A andGame B. Suppose otherwise, that
AeV SE can distinguish the two games with non-negligible advantageδ. We then
construct an adversary AABE that uses AeV SE as a sub-routine to break the
selective IND-CPAsecurity of the CP-ABE scheme. We consider a challenger
C playing the IND-CPAgame withAABE, who in turn acts as a challenger in
the Verifiability game forAeV SE:
1. AeV SE is given the security parameter by the environment, and declares (to
AABE) its choice of pre-indexδ(D?) and the queryQ.
2. AABE uses oracle calls toCin order to obtain the encrypted-then-permuted
universe ˜U. C runs k ← SE.KeyGen(1κ) and uses the symmetric key k to
symmetrically encrypt each element ofU and therefore obtainsU0. ThenC applies the permutationΠ to the universeU0that results to a permuted uni-verse ˜U and returns it toAABE. FurthermoreC runsmk←BE.KeyGen(1κ)
for the broadcast encryption scheme. It sets the master key to be MK = (M SKABE, mk, k, Π) and keeps it private.
3. Cruns theABE.Setupalgorithm on the security parameter and ˜U to generate M P KABE andM SKABE. He givesM P KABE toAABE.
4. AABE now simulates runningSetupsuch that the outcome is consistent with
M P KABE. It sets PP = (M P KABE,U˜).
5. The set of authorised usersGis initialised and a random ID is chosen from the userspaceUserswhich will be used as input forAddUser.
6. AABE first creates the label l(δ(D?)) from δ(D?). Next AABE needs to
create the index. It does so by calling the challenger who runsABE.KeyGen
on (δ(D?)∪l(δ(D?))),M P K
ABE andM SKABE and obtainsSKδ(D?)that corresponds toID?. Furthermore,Ccreates the server and data owner state
respectively followingBuildIndexand returns the outputs toAABE.
7. AABE must send a challenge access structure to the challenger. It first
com-putesr=Q(ID?) – that is, the outcome of the challenge queryQapplied to
the challenge index. Ifr= 1,AABE sets A?=Q= (FD?∧l(δ(D?))). Else, r= 0,A?=Q= (F
8. To obtain a valid keyAABE uses oracle calls toCforAddUser. The challenger
runsukID←BE.Add(ID,mk). If ID is a user it sets the key to beSKID ← (ukID, k, Π), otherwiseSKID ←ukID, and keeps it private. Furthermore, it outputs an updated server state sts and implicitely updates the set G by
adding the newly added ID toG.
9. AABE sends sts to C who runsej ←BE.Decrypt(sts, uku) and returnsej to
AABE in theQuerystage. It checks whetherej=j. If so it proceeds with the
next step, otherwise the game aborts.
10. Each queryQcan comprise multiple subqueriesQi. Therefore the following
is done for alli∈[|Q|] ={1, . . . ,|Q|}:
– To generate the challenge input,AABE begins by choosing a random bit
bi, three random messagesm0i,m1i andm 0
ifrom the message space, and
another random bitti.
AABE sends the messages m0i andm1i to C as the challenge messages for the CP-ABE game. C chooses a random bit ci and returns CT? ←
Encrypt(mci,A
?, M P K
ABE).
• Ifr= 1, AABE generatescbi ←Encrypt(Qi, m 0
i, M P KABE) and sets c1−bi =CT
? (formed over
A? byC). It also setsV Kbi =g(m 0
i) and
V K1−bi=g(mti).
• Else r = 0, and AABE sets cbi = CT
? and computes c1
−bi ←
Encrypt(Qi, m0i, M P KABE). It sets V Kbi = g(mti) and V K1−bi = g(m0i).
AABE sets QTQi = (cbi, c1−bi), V KQi = (V Kbi, V K1−bi) and RKQi = bi. Finally, AABE computesγi←φj(cbikc1−bi) and sets for alli∈[|Q|] QTQ={γi},V KQ={V KQi}, andRKQ={RKQi}.
11. AABE sends the output from Query along with the public information to
AeV SE, who is also given oracle access to whichAABE responds as follows:
– BuildIndex(·,MK,PP): To generate the evaluation key for the queried pre-indexδ(D), AABE makes use of theKeyGenoracle in the CP-ABE
game. Then it sets x0 =δ(D)∪l(δ(D)) and makes an oracle query to
C forOKeyGen(x0,MK,PK) as in Oracle Query 1.C shall generate a CP-ABE decryption key SKx0 for δ(D) if and only ifx0 6∈A?. Now, since
each data label is unique, l(δ(D0)) =l(δ(D1)) if and only ifD0 =D1. By the definition ofA?,x0 will satisfyA? only if the data labelsl(δ(D)) and l(δ(D?)) match, hence only ifδ(D) = δ(D?). Now, if x=x?i, then additionally,δ(D) must satisfy eitherQorQas chosen inA? in Step 7. However, this was chosen specifically such that δ(D?) (and therefore δ(D)) does not satisfy the query expression, and thereforex0 6∈
A? and
C may generate the key, whichAABE will receive asSKδ(D).
– All other oracles are run according to their respective algorithms.
12. Eventually, AeV SE outputsR? which it believes is a valid forgery (i.e. that
13. AABE parses R? as {R?i} for all i ∈ [|Q|]. For each i ∈ [|Q|] AABE does
the following: AABE parses R?i as (dbi, d1−bi) and using the retrieval key RKQi =bi, findsd0i andd1i. One ofd0i andd1i will be⊥(by construction) and we denote the other value byYi.
Observe that, sinceAeV SE is assumed to be a successful adversary against
selective public verifiability, the non-⊥value,Yi, that it will return will be
the plaintext mci since the challenge access structure was always set to be unsatisfied on the challenge input.
Thus, ifg(Yi) =g(mti),AABE outputs a guessc 0
i=tiand otherwise guesses
c0i= (1−ti).
Ifti =ci (the challenge bit chosen byC), we observe that the above
corre-sponds toGame A(since the verification key comprisesg(m0i) wherem0i is the message a legitimate server could recover, andg(mci) wheremci is the other plaintext). Alternatively,ti= 1−ci and the distribution of the above
experiment is identical toGame B(since the verification key comprises the legitimate message and a random message m1−ci that is unrelated to the ciphertext).
Now, we consider the advantage of this constructed adversaryAABE playing
the sIND-CPAgame for CP-ABE. Recall that by assumption,AeV SEhas a
non-negligible advantageδ in distinguishing betweenGame Aand Game B– that is
|Pr(ExpAAeV SE[eVSE,1κ] = 1)−Pr(ExpBAeV SE[eVSE,1κ] = 1)|>δ
whereExpiAeV SE[eVSE,1κ] denotes the output of runningA
eV SE in Game
i. The probability ofAABE guessingci correctly is:
Pr(c0i=ci) = Pr(ti=ci) Pr(c0i=ci|ti=ci) + Pr(ti6=ci) Pr(ci0 =ci|ti 6=ci)
= 1
2Pr(g(Yi) =g(mti)|ti=ci) + 1
2Pr(g(Yi)6=g(mti)|ti6=ci)
= 1
2Pr(Exp
A
AeV SE[eVSE,1
κ] = 1) +1
2(1−Pr(g(Yi) =g(mti)|ti6=ci))
= 1
2Pr(Exp
A
AeV SE[eVSE,1
κ] = 1) +1
2
1−Pr(ExpBA
eV SE[eVSE,1
κ] = 1)
= 1 2
Pr(ExpAA
eV SE[eVSE,1
κ] = 1)−Pr(ExpB
AeV SE[eVSE,1
κ] = 1) + 1
> 12(δ+ 1)
Hence,
AdvAABE >
Pr(ci=c0i)−
1 2 > 1
2(δ+ 1)− 1 2
14. Overall the above is done for alli∈[|Q|] and therefore we haven·AdvAABE > n·δ
2.
Hence, ifAeV SE has advantage δat distinguishing these games thenAABE
can win the sIND-CPAgame for CP-ABE with non-negligible probability. Thus since we assumed the CP-ABE scheme to be secure, we conclude that AeV SE
cannot distinguishGame AfromGame Bwith non-negligible probability.
Game B toGame C. The transition from Game B to Game C is simply to set the value of m0i to no longer be random but instead to correspond to the challenge w in the one-way function inversion game. The game basically formailizes that it is infeasible for any probabilistic polynomial-time algorithm to invert the one-way function g, i.e. to find a pre-image of a given value z. We argue that the adversary has no distinguishing advantage between these games since the new value is independent of anything else in the system bar the verification keyg(w) and hence looks random to an adversary with no additional information (in particular, AeV SE does not see the challenge for the one-way
function as this is played betweenC andAABE).
Final Proof. We now show that using AeV SE in Game C, AABE can invert
the one-way functiong – that is, given a challenge z=g(w) we can recover w. (The following can be done analogous for alli∈[|Q|].) Specifically wlog, during
Query, we choose the messages as follows:
– ifQ(ID) = 1, we implicitly set m1−bi to be wand set the verification key componentV K1−bi =z. We choose mbi andV Kbi randomly as usual.
– if Q(ID) = 0, we implicitly set mbi to be w and set the verification key componentV Kbi =z. We choosem1−bi andV K1−bi randomly as usual. Now, sinceAeV SEis assumed to be successful, it will output a forgery comprising
the plaintext encrypted under the unsatisfied query (Qor Q). By construction, this will bew (and the adversary’s view is consistent since the verification key is simulated correctly using z).AABE can therefore forward this result toC in
order to invert the one-way function with the same non-negligible probability that AeV SE has against the public verifiability game.
We conclude that if the ABE scheme is sIND-CPAsecure and the one-way function is hard-to-invert, theneVSE as defined by Algorithms 1–8 is secure in
the sense of selective Public Verifiability. ut
Lemma 2. eVSE as defined in algorithms 1–8 is secure against Index Privacy (Game 3) under the same assumptions as in Theorem 1.
Proof. Suppose AeV SE is an adversary with non-negligible advantage against
the Index Privacy game (Game 3) when instantiated with Algorithms 1-8. We begin by defining the following two games:
– Game A: This is the selective Index Privacy game as defined in Game 3.
We show that an adversary with non-negligible advantage against the se-lective Index Privacy game can be used to construct an adversary AIN D-CP A
which may break the IND-CPA security of a symmetric key encryption scheme
SE= (SE.KeyGen,SE.Encrypt,SE.Decrypt).
Game A toGame B. The PRP-assumption [7] is formulated as follows. Let
D be a distinguisher algorithm that takes as input a permutation and outputs a bit. In the following, let Π be a random function, Π0 be a PRP and S, S0 are sets. We define the PRP-advantage ofDto be:
Pr[ ˜S←$ Π(S) :D( ˜S) = 1]−Pr[ ˜S0 ←Π0(S0) :D( ˜S0) = 1]
The PRP-assumption states that any efficient algorithm’s PRP-advantage is negligible.
Now, fix an adversaryAeV SE that is able to distinguish betweenGame A
and Game B with non-negligible advantage δ. That is, AeV SE’s probability
of success in one game is non-negligibly different to their probability of success in the other game (suppose the probability of success in Game A is higher than that ofGame B, without loss of generality). We can build a distinguisher
D that is able to distinguish whether a permutation is either truly random or pseudorandom with non-negligible probability, by usingAeV SE as a subroutine
(hence has non-negligible PRP-advantage). Given a permutationπ,D instanti-atesAeV SE in Game 3 usingπas input intoSetup(line 3 of Game 3). IfAeV SE
wins the game thenDoutputs 1, indicating that they believeπis truly random and 0 otherwise, indicating that they believeπis a PRP.Dwill be able to distin-guishπ with exactlyAeV SE’s advantage,δcontradicting the PRP-assumption.
Thus we conclude thatAeV SEcannot distinguishGame AfromGame Bwith
non-negligible probability. Hence we continue the proof usingGame B.
Reduction to IND-CPA. Now let AeV SE be an adversary with non-negligible
advantageδagainstGame B. We now show that usingAeV SE as a subroutine
in Game B, AIN D-CP A is able to break the IND-CPA security of SE. That is, given a challenge ciphertext c which is an encryption mb where b
$
← {0,1} AIN D-CP Acan distinguish whether cis an encryption ofm0 orm1.
Fix an adversary AeV SE that is able to break the index privacy of eVSE
with non-negligible advantage γ. Let C be the challenger for AIN D-CP A and
AIN D-CP Awill act as the challenger forAeV SE.
1. AeV SE chooses their challenge sets: D0 = (d0,1, d0,2, ..., d0,q) and D1 =
(d1,1, d1,2, ..., d1,q)⊆ Usuch that|D0|=|D1|. Note that a rational adversary
will always chooseD0 6= D1i.e. D0 and D1 differ by at least one element.
AeV SE submits these challenge sets toAIN D-CP A.
– AIN D-CP Aruns line 1 of Algorithm 1 to generate the secret key for the
broadcast encryption schemeBE= (BE.KeyGen,BE.Encrypt,BE.Add,BE.Decrypt):
mk←BE.KeyGen(1κ),
which is retained byAIN D-CP A and shared withC.
– Cruns line 2 of Algorithm 1 to generate the secret key for the symmetric encryption schemeSE= (SE.KeyGen,SE.Encrypt,SE.Decrypt):
k←SE.KeyGen(1κ),
which is retained byC.
– C provides AIN D-CP A with oracle access to the following functions:
SE.Encryptk(·) which takes as input a plaintext and returns its symmet-ric encryption underkandLR(·,·, b) which takes two plaintextsm0, m1 and a bitband outputs the symmetric encryption ofmb underk.
– For all d0,j 6=d1,j, AIN D-CP A submits the pair (d0,j, d1,j) (where such
pairs exist as the challenge sets are not equal) toLR(·,·, b) and receives challenge ciphertexts,cj, in return.
– These challenge ciphertexts are included in U0. To compute the rest of U0 (lines 3-5 of Algorithm 1), A
IN D-CP A submits every other pair
(d0,i, d1,i) ∈ {D0, D1} : d0,i = d1,i, to SE.Encryptk(·) and includes the
output in U0. To ensure U0 contains an encryption of each attribute in U, AIN D-CP A submits the remaining attributes of U: an ∈/ (D0∪
D1) to SE.Encryptk(·) and includes the output in U0. U0 now contains
an encryption of every element in U. To map elements from U to U0 (which is required to runEncode), every attribute inU needs to have a corresponding ciphertext inU0which is defined as follows: for each pair of attibutes that were submitted toLR(·,·, b) we let the output denote the corresponding element inU0 for the attribute on the left hand side of the submitted pair. For all attributes in U submitted to SE.Encryptk(·) the output is the corresponding element inU0for that attribute. This defines a bijective mapping of attributes inU to elements inU0 as required.
– AIN D-CP A defines the set ˜U ← Π(U0), where Π is a pseudorandom
function, and runs line 7 of algorithm 1:
(M SKABE, M P KABE)←ABE.Setup(1κ,U˜).
– AIN D-CP AretainsM SKABE and PP = (M P KABE,U˜) is made public.
4. AIN D-CP AinitializesGas the empty set, selects a randomIDfromUsersand
runsAddUser to produce SKID, which is shared withAeV SE. The values k
andΠ are omitted from this secret key as they are not required.AIN D-CP A
also runs AddUser on a server identity S to generate the secret key SKS
5. AIN D-CP A creates a pre-index δ(Db) to encode into the challenge index
forAeV SE (line 4 Algorithm 1). This is done usingEncode, which takes as
input the elements from the challenge set Db and maps them to elements
in U0 as defined in step 3. Due to the way the mapping is defined using LR(·,·, b), this will produce a preindex containing encryptions of elements from the challenge setDb. Ifb= 0 thenLR(·,·,0) would have been used for
encryption hence the attributes in D0 would have been encrypted and be included in the preindex, wheres ifb = 1 thenLR(·,·,1) would have been used for encryption hence the attributes inD1 would have been encrypted and be included in the preindex.
6. AIN D-CP A runs BuildIndex using the pre-index created in step 4 to create
the challenge indexIDbforAeV SE. Note that althoughBuildIndextakes MK as input, it does not requirekorΠ. The only part of MK that is required is M SKABEwhich is generated and retained byAIN D-CP Ain step 3.BuildIndex
also generatessts andsto. sts is shared withAeV SE andsto is retained by
AIN D-CP A.
7. AeV SE is given oracle access to BuildIndex, AddUser, Query and Search. To
queryBuildIndexAeV SEsubmits a set of attributes (with the restriction that
no attributes from either challenge set are used) toAIN D-CP A. AIN D-CP A
responds toBuildIndexqueries using Encodeto produce the pre-index from the set of attributes then runs ABE.KeyGen to produce the relevant index (line 1 Algorithm 2). We allowAeV SE to queryAddUserwith arbitrary user
IDs to generate secret keysSKID, AIN D-CP A responds to these queries by
calling C to run Algorithm 3 using the ID from AeV SE and mk, k which
it holds. To query Query AeV SE submits their query Q and their secret
keySKu to AIN D-CP A (with the restriction that the corresponding query
cannot be used to distinguish between the two challenge sets). AIN D-CP A
runs Algorithm 4 using these values along with sts (which was generated
in step 5) to produce the query (QTQ, V KQ, RKQ) which is returned to
AeV SE. To query Search submits their challenge index IDb and QTQ to
AIN D-CP Awhich runsSearchusing these values along withstsandSKS to
produce search resultsRwhich are returned toAeV SE. To allow verification
of search resultsAeV SEcan queryBVerif.AeV SE submits the resultRalong
with the verification tokenV KQ toAIN D-CP Awhich runs Algorithm 6 and
returnsRTQ toAeV SE.
8. AeV SE outputs their guess b0 for b. By our assumption that AeV SE is an
adversary with non-neglible advantageγin the Index Privacy game (Game 3) we have that Pr(b0 =b)>γ+12. Ifb0 = 0, this tellsAIN D-CP Athat AeV SE
believes that D0 was encoded into the index IDb and that LR(·,·,0) was used for encryption (respectively ifb0= 1 this tells AIN D-CP A that AeV SE
believes thatD1 was encoded into the index and that LR(·,·,0) was used for encryption).
9. Using this information AIN D-CP A outputs their guess for b as b0 also. As
b0 directly corresponds to the bitb chosen byC used to createAIN D-CP A’s
challenge ciphertext. Hence if AIN D-CP A uses the sameb0 as the response
to their challenge ciphertext then they will win their challenge with non-negligible probabilityγwhich contradicts our assumption thatSE is a secure symmetric encryption scheme.
10. From this we conclude that there cannot exist an adversary AeV SE with
non-negligible probability againstGame B, henceγis in fact negligible. We have shown that Game B can be distinguished from Game A (or
Game 3) with only a negligible probability. Therefore, an adversary against
Game Acan be run againstGame Binstead with at most a negligible loss in advantage. The advantage,γ, of an adversary against Game Bhas been shown to be negligible. Therefore, we conclude thatAdvIndP riv
AeV SE is also negligible. This proves the security with respect to Index Privacy of eVSE.
u t
Lemma 3. eVSE as defined in algorithms 1–8 is secure against Query Privacy (Game 4) under the same assumptions as in Theorem 1.
Proof. Suppose AeV SE is an adversary with non-negligible advantage against
the Query Privacy game (Game 4) when instantiated with algorithms 1-8. We begin by defining two games:
– Game A: This is the selective Query Privacy game as defined in Game 3.
– Game B: This is the same asGame Awith the modification that we use a pseudorandom permutation in Algorithm 1 to construct ˜U.
We show that an adversary with non-negligible advantage against the selec-tive Query Privacy game can be used to construct an adversary (AIN D-CP A)
which may break theIND-CPAsecurity of a symmetric key encryption scheme
SE= (SE.KeyGen,SE.Encrypt,SE.Decrypt).
Game A to Game B. See Game A to Game B in proof of Lemma 2 for details.
Reduction toIND-CPA.We now show that usingAeV SEinGame B,AIN D-CP A
can break the IND-CPA security of a symmetric key encryption scheme SE. That is, given a challenge ciphertext c which is an encryption mb where b
$
← {0,1},AIN D-CP Acan distinguish whetherc is an encryption ofm0 orm1.
This proof follows in the spirit of the proof of Lemma 2. LetC be the chal-lenger forAIN D-CP AandAIN D-CP Awill act as the challenger forAeV SE.
1. AeV SE chooses their challenge queries: Q0, Q1 with the restriction that all gates match in both queries (the gates are denoted byGQ0 forQ0andGQ1for
andQ1 respectively (note that if all the (binary) gates in each query match the two sets of attributes will be the same size).AeV SE submitsQ0 andQ1 toAIN D-CP A.
2. The challengerC chooses a bitb← {$ 0,1}. 3. eVSE.Setupis run betweenC andAIN D-CP A:
– AIN D-CP Aruns line 1 of Algorithm 1 to generate the secret key for the
broadcast encryption schemeBE= (BE.KeyGen,BE.Encrypt,BE.Add,BE.Decrypt):
mk←BE.KeyGen(1κ),
which is retained byAIN D-CP A and shared withC.
– Cruns line 2 of Algorithm 1 to generate the secret key for the symmetric encryption schemeSE:
k←SE.KeyGen(1κ),
which is retained byC.
– C provides AIN D-CP A with oracle access to the following functions:
SE.Encryptk(·) which takes as input a plaintext and returns its symmet-ric encryption underkandLR(·,·, b) which takes two plaintextsm0, m1 and a bitb and runsSE.Encryptk(·) using mb as input and outputs the
symmetric encryption ofmb under k.
– AIN D-CP Anow computes U0 (lines 3-5 of Algorithm 1). For every pair
(q0,i, q1,i) : q0,i 6= q1,i, AIN D-CP A submits the pairs (q0,i, q1,i) and
(q1,i, q0,i) toLR(·,·, b). For all other pairs (q0,t, q1,t) we have thatq0,t=
q1,t, hence AIN D-CP A submits q0,t to SE.Encryptk(·) and includes the
output in U0. To ensure U0 contains an encryption of each attribute in
U, AIN D-CP A submits the remaining attributes of U: an ∈/ (Q0∪Q1)
toSE.Encryptk(·) and includes the output inU0.U0 now contains an
en-cryption of every element inU. In order to map elements fromU to U0 (which is required to runEncode), every attribute inU needs to have a corresponding ciphertext inU0which is defined as follows: for each pair of attibutes that were submitted toLR(·,·, b) we let the output denote the corresponding element inU0 for the attribute on the left hand side of the submitted pair. For all attributes in U submitted to SE.Encryptk(·) the output is the corresponding element inU0for that attribute. This defines a bijective mapping of attributes inU to elements inU0 as required.
– AIN D-CP A defines the set ˜U ← Π(U0), where Π is a pseudorandom
function, and runs line 7 of algorithm 1:
(M SKABE, M P KABE)←ABE.Setup(1κ,U˜).
4. AIN D-CP AinitializesGas the empty set, selects a randomIDfromusersand
runsAddUser to produce SKID, which is shared withAeV SE. The values k
andΠ are omitted from this secret key as they are not required.AIN D-CP A
also runs AddUser on a server identity S to generate the secret key SKS
which is retained byAIN D-CP A.AIN D-CP AaddsID toG.
5. AIN D-CP Aruns BuildIndexusing a pre-indexδ(D) chosen randomly from ˜U
to create an indexID for AeV SE. Note that althoughBuildIndextakes MK
as input, it does not requirekorΠ. The only part of MK that is required is M SKABEwhich is generated and retained byAIN D-CP Ain step 3.BuildIndex
also generatessts andsto. sts is shared withAeV SE andsto is retained by
AIN D-CP A.
6. AIN D-CP A creates a pre-query ˜Qb to encode into the challenge query for
AeV SE. This is done using Encode, which takes as input the elements from
set of attributes corresponding to the challenge query Qb and maps them
to elements in U0 as defined in step 3. Due to the way the mapping is de-fined usingLR(·,·, b), this will produce a pre-query containing encryptions of attributes corresponding to the challenge query Qb. If b = 0 then then
LR(·,·,0) would have been used for encryption hence the attributes inQ0 would have been encrypted and be included in the pre-query, wheres ifb= 1 then LR(·,·,1) would have been used for encryption hence the attributes corresponding toQ1would have been encrypted and be included in the pre-query.
7. AIN D-CP A runs Query using the pre-query created in step 4 to create the
challenge query (QTQb, V KQb, RKQb) forAeV SE.
8. AeV SE is given oracle access to BuildIndex, AddUser, Query and Search. To
queryBuildIndexAeV SE submits a set of attributes toAIN D-CP A(with the
restriction that the search results produced when searching the correspond-ing index cannot be used to distcorrespond-inguish the two challenge sets).AIN D-CP A
responds toBuildIndexqueries usingEncodeto produce the pre-query from the set of attributes then runs ABE.KeyGen to produce the relevant index (line 1 Algorithm 2). We allowAeV SE to queryAddUserwith arbitrary user
IDs to generate secret keysSKID; AIN D-CP A responds to these queries by
querying C to run Algorithm 3 using the ID from AeV SE andmk, k which
it holds. To queryQuery AeV SE submits their queryQand their secret key
SKID toAIN D-CP A(with the restriction that the corresponding query
can-not be used to distinguish between the two challenge sets).AIN D-CP A runs
Algorithm 4 using these values along withsts(which was generated in step
5) to produce the query (QTQ, V KQ, RKQ) which is returned toAeV SE.
9. AeV SE outputs their guessb0 forb. By our assumption thatAeV SE is an
ad-versary with non-neglible advantageγin the Query Privacy game (Game 4) we have that Pr(b0 =b)>γ+12. Ifb0 = 0, this tellsAIN D-CP Athat AeV SE
