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To provide a secure and efficient retrieval of data, one needs to ensure that the user can perform a search over the encrypted data without revealing the contents and the searched keyword to the server. The cryptographic primitive that provides this feature is widely known as searchable encryption (SE). This research aims to study the searchable encryption schemes in detail and implements a solution that enables privacy preserving data storage and retrieval system in cloud computing (aka PrivCloud). For our implementation, we have chosen an existing searchable symmetric key encryption algorithm. To enable the privacy preserving keyword search, this scheme will generate an encrypted keyword index which will be outsourced to the cloud server along with the encrypted data set. The encrypted keyword index lists out the encrypted keyword and pointer to the corresponding document containing that keyword. To search a keyword, client can simply encrypt the keyword to generate the search token and send it to the remote cloud server. The server can retrieve pointer to the corresponding document by matching the search token with the encrypted keyword index table. For our proposed solution, we have chosen to index all the words from the document instead of a specific keyword set. This will allow the client to search for any word in the document rather than any specific keyword. Also, indexing all the words of the document make sure that the user does not need to maintain a keyword index table at the client side since it can search for any words. However, indexing all the words will come with the trade-off of a slightly larger index size. One of the limitations of the proposed solution is that it does not support the addition of new files since the index update is static.
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Searchable encryption (SE) enables the users to generate a search token from the searched keyword in such way that given a token, the cloud server can retrieve the encrypted contents containing the searched keyword. Basically, the search token represents an encrypted query over the encrypted data and can be generated only by users with the appropriate secret key. Figure 1 shows the basic architecture and working principle of a searchable encryption scheme. The architecture comprises mainly four entities: data owner, data user, cloud service provider and key generator. A brief description of the entities and their operations are given below.
Search query: Server should not learn anything about the keyword being searched for. Given a token, the server can retrieve nothing other than pointers to the encrypted content that contains the keyword.
Searchable encryption scheme can be built using either a non-keyword based approach or an index/keyword based approach. In the non-keyword based approach, the scheme scans the entire document word by word to find out the word W of interest. This provides the functionality to search any words in the document. However, it takes a long search time for a large number of document set. On the other hand, index/keyword based solution builds up an index [10], for each word W of interest and lists out the corresponding documents that contain W. This provides a faster search operation when the document set is large. However, storing and updating the index can be an overhead.
In this section, we present a brief summary of related works dealing with the searchable encryption schemes. Searchable encryption scheme can be designed based on either public key or symmetric key algorithm. The first searchable encryption scheme based on public key algorithm was proposed by Boneh et al. [11]. This is known as the PEKS scheme which uses the public key of a user to encrypt and store the data in the server, and allows an authorized user with the private key to search and decrypt the corresponding content. This is a keyword based scheme ensuring faster search functionality; however, limiting the search capability. Also, the scheme is computationally expensive and it reveals the user access pattern. An extension of the PEKS scheme was proposed by Liu et al. [14]. This also uses the public key primitive to support the keyword searching on encrypted data. This scheme allows the cloud service provider to participate in the partial decipherment and claims to have reduced computational overhead on the client due to this partial decipherment. Another variant of the PEKS scheme called iPEKS was proposed by Tseng et al. [15]. This scheme aims to accelerate the search time by looking into the previously searched keywords. For this, the cloud service provider caches the previously searched keywords to avoid the search on all the stored ciphertexts. However, this comes with the tradeoff of large storage overhead. The first searchable encryption scheme based on symmetric key primitive was proposed by Song et al. [17]. This provides a non-keyword based solution. However, this scheme can search for only fixed length words and also the search time is linear in document size, since the it needs to scan the whole document to complete the search. The scheme is too slow when searching for a large number of documents. Goh [10] addresses some of the issues of the above scheme by introducing the concept of a secure index. This scheme generates a search index which can be used to locate the encrypted content. Later, the security notions of searchable symmetric encryption were revisited and stronger security definitions were provided by Curtmola et al. [19]. This is a very simple scheme based on keyword indexing approach.
This research aims to design and develop a privacy preserving data storage and retrieval system in cloud computing. The scopes involve the use of searchable encryption algorithms to search for specific keywords within an encrypted content, i.e., without requiring the user to download the database and decrypt its contents before searching can be performed. The proposed solution delegates searching on encrypted data to CSP but with privacy preserved. For the searchable encryption algorithm, we have chosen to implement the adaptively secure Searchable Symmetric encryption (referred as SSE-2 scheme in the original paper) scheme proposed by Curtmola et al. [19]. For the rest of the paper, we will use the term SSE-2 scheme or adaptively secure SSE scheme to refer to the proposed method by Curtmola et al. The SSE-2 scheme provides a simple but efficient method to enable searching over encrypted data while preserving the data privacy. The reason behind selecting a private/symmetric key primitive for our implementation mainly lies in the fact that it results in significantly lesser computational overhead when compared to its public/asymmetric key counterpart and therefore will be more suitable for mobile devices.
In this section, we describe the adaptively secure SSE algorithm proposed by Curtmola et al. [19]. As the name suggests, the scheme is based on the symmetric key encryption setting and therefore mostly suitable for a single reader/single writer scenario. It uses the index based approach [10], where user has to pre-process the contents to generate a keyword index to provide for the search capability. Figure 2 shows the construction of the adaptively secure searchable symmetric encryption scheme.
As shown in Figure 2, a user U encrypts a set of data \(D = \left\{ D_{1}, D_{2},\cdots , D_{n}\right\}\) and creates an encrypted index file I which contains a set of m encrypted keywords extracted from the data set D. In order to conduct a search over the encrypted data, user U outsources the index I and the encrypted data set D to the cloud server. During a search, U creates an encrypted query and sends it to the server. Cloud server takes this encrypted query as input and then uses the encrypted index located at the server to retrieve pointers to the document(s) containing the searched keyword. Once the search result is obtained, the encrypted document(s) containing the searched keyword is returned to the client.
Document re-processing: This block provides the necessary function to pre-process a set of documents and initialize the encryption procedure. Before encrypting the set of documents, the user needs to pre-process the document set to pull out the keyword and build an index. Let D defines a set of document to be encrypted and uploaded in the cloud server. The user has to list out all the keywords from each document in D and build an index table listing the documents and the corresponding keywords. The scheme will also assign a content ID for each of the documents in the set. For example, consider a set of 5 documents \(D = \left\{ D_{1}, D_{2}, D_{3}, D_{4}, D_{5}\right\}\) to be uploaded in the cloud. At the pre-processing step, the user will pre-process these set of documents to build an index table as shown in Table 1. Here, \(w_{i}\) \((i = 1, 2, 3, \cdots , m )\) represents the keyword and m is the total number (\(m = 10\) for this example) of keywords. The content IDs are assigned sequentially starting from 1.
Encryption: This block provides the functionality to encrypt the index and document set. The encryption is performed using the encryption keys generated at the key generation step. Basically, it consists of index encryption and document encryptions and performs as described below: Index encryption This encrypts the keyword set generated at the pre-processing step and creates an encrypted index/lookup table. The keyword encryption is computed as \(ENC_{K_{1}}\left( w_{i} || n_{i}\right)\), where \(ENC_{K_{1}}\) represents encryption with key \(K_{1}\), \(w_{i}\) is the keyword i and \(n_{i}\) is the corresponding document ID containing keyword \(w_{i}\). For each of the encrypted keywords, the encrypted index table lists out the corresponding document ID. For our example document set, the encrypted index table is shown in Table 3. 589ccfa754
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