Nowadays the e-healthrecord system has been very famous.The e-healthrecord system will make medical records to be computerized with the ability to prevent medical errors. The electronic healthrecord system help a patient to create his own health data in one hospital and manage or share the information with other in other hospitals. Many patient-centric EHR system have been implemented such as google health and Microsoft healthvault. The prospect to deploy the EHR system everywhere comes up with the privacy of the patient. The data collected at the healthcare data center contains private data and may be vulnerable to potential leakage and this data may be disclosed to individuals or companies who make profit from that data. Although the service provider can make the patient to believe that the information is secure ,the EHR could be exposed if the server is intruded or an inside staff misbehaves. The obstacle that stands in the way of wide adoption of the EHR system is the concern about privacy and security. The public key Encryption scheme with keywordsearch(PEKS) allows the user to search on encrypted data without decrypting it. Which is suitable to raise the security of EHR system.
In this setting, a user encrypts the data using symmetric/private key encryption schemes (e.g. AES) before outsourcing it to the cloudserver. This setting is appropriate when the user that searches over the data is also the one who generates it. The main advantage of this setting is the efficiency, but it lacks of functionality as it can only be used for a single user scenario. Moreover, most of the SSE schemes leaks the access patterns. The encryption is efficient because most SSE schemes are based on symmetric primitives like block-ciphers and pseudo-random functions and requires very less computational overhead. The SSE scheme was first proposed by Song et al.  which provides techniques for remote searching over encrypted data using symmetric key primitives. Later, security notions of SSE schemes were revisited and stronger security definitions were provided by Goh , Chang et al.  and Curtmola et al. .
Ensuring the cloud data security is a major concern for corporate cloud subscribers and in some cases for the private cloud users. Confidentiality of the stored data can be managed by encrypting the data at the client side before outsourcing it to the remote cloud storage server. However, once the data is encrypted, it will limit server’s capabil‑ ity for keywordsearch since the data is encrypted and server simply cannot make a plaintext keywordsearch on encrypted data. But again we need the keywordsearch functionality for efficient retrieval of data. To maintain user’s data confidentiality, the keywordsearch functionality should be able to perform over encrypted cloud data and additionally it should not leak any information about the searched keyword or the retrieved document. This is known as privacy preserving keywordsearch. This paper aims to study privacy preserving keywordsearch over encrypted cloud data. Also, we present our implementation of a privacy preserving data storage and retrieval system in cloud computing. For our implementation, we have chosen one of the symmetric key primitives due to its efficiency in mobile environments. The implemented scheme enables a user to store data securely in the cloud by encrypting it before outsourcing and also provides user capability to search over the encrypted data without revealing any information about the data or the query.
As a complementary approach, the first searchable encryption system using the public key system is proposed, by Boneh et al, 2004 , in which server contains encrypted files and keywords. User creates keyword trapdoor using its private key to search . The server checks with existing encrypted keywords and sends encrypted file that match it. In Bonh scheme, the trapdoor may be memorized and then it well reveal knowledge about the keyword . G.Duntao scheme  tried to solve the problem of memorized trapdoor. Based on Boneh's scheme, G.Duntao et al. proposed a temporary keywordsearch scheme over public key encryptio. G.Duntao scheme solves the problem of the memorized trapdoor. G.Duntao scheme divides the time into a few time slides, and generates a temporary trapdoor for corresponding time slides. The trapdoor of a keyword in some time doesn’t reveal anything about the trapdoor at time . To achieve more efficientsearch, Curtmola et al, 2006  proposed an index searching technique. In Curtmola scheme, it builds an index file. In the index file, each entry consists of a trapdoor of each keyword and the corresponding files identifiers contain the keyword. Secure and privacy preserving keyword searching (SPKS) was proposed in 2011 by Q.Liu et al. . In SPKS scheme cloud service provider (CSP) can determine files contain query keywords, and then make a partial decipherment of this files before returning the search results. Q.Liu scheme reduces the overhead in decryption for the user.
In recent years consumer centric cloud computing is a novel model for the enterprise-level IT organization that provides on- demand high quality applications and services from a shared group of computing resources. The Cloud Service Provider (CSP) has complete control over the outsourced data; it may possible that it can learn some additional information from that data therefore some problems like privacy of the data, arise in the circumstance. So, sensitive data have to encrypt before outsourcing to the cloudserver. However the encrypted data makes the existing plaintext search approaches useless. The simple and awkward method is downloading all data and decrypt it locally is apparently impractical, because the cloud consumers need to search only the interested data rather all the data. Therefore it is necessary to discover an efficient and effective search service over encrypted outsourced data .
In this proposed framework, surprisingly, we characterize and tackle the issue of Multi-keyword Ranked Search over Encrypted Cloud Data [MRSE] while safeguarding strict framework shrewd protection in the cloud computing worldview.We enhance the of ranked search mechanism, including supporting more search semantics, i.e., TF _IDF, and dynamic data operations. Also performs the provision of maintaining the integrity of rank order in search result and the cloudserver is untrusted.Beacouse of providing the integrity to rank order the quality of search is enhanced or improved .User save the time to get relevance document to their search query. In order to improve the document retrieval accuracy, the search result should be ranked by the cloudserver according to ranking in order to make the data on cloud more secure. To reduce the cost of communication data user can provide N number along with the trapdoor so that cloudserver return only top-N document which having are relevance to user query.
Searchable encryption is of increasing interest for protecting the data privacy in secure searchable cloud storage. In this paper, we investigate the security of a well-known cryptographic primitive, namely, public key encryption with keywordsearch (PEKS) which is very useful in many applications of cloud storage. Unfortunately, it has been shown that the traditional PEKS framework suffers from an inherent insecurity called inside keyword guessing attack (KGA) launched by the malicious server. To address this security vulnerability, we propose a new PEKS framework named dual-server PEKS (DS- PEKS). As another main contribution, we define a new variant of the smooth projective hash functions (SPHFs) referred to as linear and homomorphic SPHF (LH-SPHF). We then show a generic construction of secure DS- PEKS from LH-SPHF. To illustrate the feasibility of our new framework, we provide an efficient instantiation of the general framework from a Decision Diffie–Hellman- based LH-SPHF and show that it can achieve
In traditional way we use data encryption to avoid information leakage. However, it is a very challenging task to search on encrypted data as server-side data utilization is more. In order to address the above problem, a general solution with fully- homomorphic encryption has been designed. Searchable encryption schemes allow users to store data in encrypted form and perform search over cypher text domain. Till now numerous works have been proposed under various threat models to perform different search functionality. Among them, multi keyword ranked search has more practical applicability.
Abstract— Searchable encryption is of increasing interest for protecting the data privacy in secure searchable cloud storage. In this paper, we investigate the security of a well-known cryptographic primitive, namely, public key encryption with keywordsearch (PEKS) which is very useful in many applications of cloud storage. Unfortunately, it has been shown that the traditional PEKS framework suffers from an inherent insecurity called inside keyword guessing attack (KGA) launched by the malicious server. To address this security vulnerability, we propose a new PEKS framework named dual-server PEKS (DS- PEKS). As another main contribution, we define a new variant of the smooth projective hash functions (SPHFs) referred to as linear and homomorphic SPHF (LH- SPHF). We then show a generic construction of secure DS-PEKS from LH- SPHF. To illustrate the feasibility of our new framework, we provide an efficient instantiation of the general framework from a Decision Diffie–Hellman-based LH-SPHF
the data owners to share their private data with other authorized user. However, most of the available systems require the user to perform a large amount of complex bilinear pairing operations. These overwhelmed computations become a heavy burden for user’s terminal, which is especially serious for energy constrained devices. The outsourced decryption method allows user to recover the message with ultra lightweight decryption. However, the cloudserver might return wrong half-decrypted information as a result of malicious attack or system malfunction. Thus, it is an important issue to guarantee the correctness of outsourced decryption in public key encryption with keywordsearch (PEKS) system. The authorized entities may illegally leak their secret key to a third party for profits. Suppose that a patient someday suddenly finds out that a secret key corresponding his electronic medical data is sold on e-Bay. Such despicable behavior seriously threatens the patient’s data privacy. Even worse, if the private electronic health data that contain serious health disease is abused by the insurance company or the patient’s employment corporation, the patient would be declined to renew the medical insurance or labor contracts.
Abstract. As cloud computing becomes prevalent, more and more sensi- tive data is being centralized into the cloud by users. To maintain the confi- dentiality of sensitive user data against untrusted servers, the data should be encrypted before they are uploaded. However, this raises a new chal- lenge for performing search over the encrypted data efficiently. Although the existing searchable encryption schemes allow a user to search the encrypted data with confidentiality, these solutions cannot support the verifiability of searching result. We argue that a cloudserver may be selfish in order to save its computation ability or bandwidth. For exam- ple, it may execute only a fraction of the search and returns part of the searching result. In this paper, we propose a new verifiable fuzzy key- word search scheme based on the symbol-tree which not only supports the fuzzy keywordsearch, but also enjoys the verifiability of the search- ing result. Through rigorous security and efficiency analysis, we show that our proposed scheme is secure under the proposed model, while correctly and efficiently realizing the verifiable fuzzy keywordsearch. The extensive experimental results demonstrate the efficiency of the proposed scheme.
We define and solve the challenging problem of privacy-preserving multi-keyword ranked ontology keyword mapping and search over encrypted cloud data (EARM), and establish a set of strict privacy requirements for such a secure cloud data utilization system to become a reality. Among various multi-keyword semantics, we choose the efficient principle of “coordinate matching”. It has been proposed the problem of Secured Multikeyword search (SMS) over encrypted cloud data (ECD), and construct a group of privacy policies for such a secure cloud data utilization system. From number of multi-keyword semantics, we select the highly efficient rule of coordinate matching, i.e., as many matches as possible, to identify the similarity between search query and data, and for further matching we use inner data correspondence to quantitatively
Abstract: The advancement in cloud computing has motivated the data owners to outsource their data management systems from local sites to commercial public cloud for great flexibility and economic savings .For real privacy, user identity should remain hidden from CSP (Cloud service provider) and to protect privacy of data, data which is sensitive is to be encrypted before outsourcing. By considering the large number of data users, documents in the cloud, it is important for the search service to allow multi keyword query and provide result similarity ranking to meet the effective need of data retrieval search and not often differentiate the search results. In this system, we define and solve the challenging problem of confidentiality retention in keyword list ranked search over encrypted cloud data, and establish a set of strict privacy requirements for such a secure cloud data utilization system to be implemented in real. We first propose a basic idea for the Keyword list Ranked Search over Encrypted cloud data based on secure inner product computation and efficient similarity measure of coordinate matching, i.e., as many matches as possible, in order to capture the relevance of data documents to the search query, then we give two significantly improved Ranked search schemes to achieve various stringent privacy requirements in two different threat models. Assignment of anonymous ID to the user to provide more security to the data on cloudserver is done. To improve the search experience of the data search service, further extension of the two schemes to support more search semantics is done.
On the other hand, to collect the efficient data retrieval requirement, the huge amount of documents orders the cloudserver to reach result relevance ranking, as an alternative of returning undifferentiated results. Such ranked search system permit data users to find the most suitable information quickly, rather than some sorting during every match in the content group. Ranked search can also gracefully remove unwanted network traffic by transferring the most relevant data, which is highly attractive in the “pay-as-you-use” cloud concept. For privacy protection, such ranking operation on the other hand, should not release any keyword to related information. To get better the search result accuracy as well as to improve the user searching experience, it is also required for such ranking system to support multiple keywords search, as single keywordsearch usually give up far too common results. As a regular practice specifies by today’s web search engines i,e Google search, data users may slant to offer a set of keywords as an alternative of only one as the indicator of their search interest to retrieve the most applicable data. And each keyword in the search demand is able to help the limited search result further.
Wide range of studies has been done for efficient multi keywordsearch scheme over mobile cloud. One of the well-known algorithms for efficient multi keywordsearch is RSA, which is widely used cryptosystem in the world. In the paper, Dawn Xiao dong Song  described some cryptographic schemes for the problem of searching on encrypted data and provided proofs of security for the resulting crypto systems. These techniques have a number of crucial advantages. They are provably secure, they provide provable secrecy for encryption, meaning that the untrusted server cannot learn anything more about the plaintext than the search result; they provide controlled searching, so that the untrusted server cannot search for an arbitrary word without the user’s authorization.Dan Boneh  performed for the problem of searching on data that is encrypted using a public key system. Consider user Bob who sends email to user Alice encrypted under Alice's public key. An email gateway wants to test whether the email contains the keyword \urgent" so that it could route the email accordingly. Alice, on the other hand does not wish to give the gateway the ability to decrypt all her messages. This construct a mechanism that enables Alice to provide a key to the gateway that enables the gateway to test whether the word \urgent" is a keyword in the email without learning anything else about the email. It refers to this mechanism as Public Key Encryption with keywordSearch. Using this mechanism Alice can send the mail server a key that will enable the server to identify all messages containing some special keyword, but learn nothing else.
As the popularity of cloud increases, a large number of data owners were motivated for outsourcing the information to the cloud servers which will be convenient for users and also reduction in cost for managing the data. But confidential information has to be encrypted in prior to outsource the data to provide privacy and security that can be used for data retrieval through keyword based scheme. The paper provides a multiple keyword rank search technique on data encrypted that can be used to support dynamic operations such as insertion and deletion of data in document. Widely used models are vector space and TF-IDF were commonly used in combination with the query generation and construction of index. An index structure is constructed on the basis of tree and an algorithm is proposed which is depth-first search tree, a greedy algorithm that helps to provide efficiency in multiple keyword rank search. A secure algorithm called KNN is used for encrypting the query vectors and also the index. The usage of KNN algorithm also provides accurate score computation among the query vectors and indexes which are encrypted. To protect from statistical attacks, apparition words were included in the index to bind with the search result. As a special tree-based indexing structure was implemented, the proposed method will achieve more efficiency in time for search and also provides flexibility for performing insertion and deletion operations in a document. Substantial procedures were used for the demonstration of the proposed scheme for achieving greater efficiency.
Searchable encryption is increasing interest for protecting the data privacy in secure searchable cloud storage. The security of a well-known cryptographic primitive, namely, public key encryption with keywordsearch (PEKS) which is very useful in many applications of cloud storage. Unfortunately, it has been shown that the traditional PEKS framework suffers from an inherent insecurity called inside keyword guessing attack (KGA) launched by the malicious server. To address this security vulnerability, a new PEKS framework named dual-server PEKS (DS-PEKS). As another main contribution, a new variant of the smooth projective hash functions (SPHFs) referred to as linear and homomorphic SPHF (LH-SPHF). To show a generic construction of secure DS-PEKS from LH-SPHF. To illustrate the feasibility of new framework, provide an efficient instantiation of the general framework from a Decision Diffie– Hellman-based LH-SPHF and show that it can achieve the strong security against inside the KGA.
With the Emergence of cloud computing, it has become increasingly admire for data owners to outsource their data to public cloud servers while allowing data users to retrieve this data. For privacy concerns, authenticated secure searches over encrypted cloud data have motivated several research works under the single owner model. Although, most of the cloud servers in real time practice do not just serve one data owner instead, they support multiple data owners to share the application and benefits brought by cloud computing. This paper presents different schemes to deal with Privacy preserving Ranked Multi-keywordSearch in a Multi-owner model (PRMSM). To permit authorization to cloud servers to perform secure search without knowing the actual data of keywords and trapdoors, unauthorized user we systematically construct a novel secure search protocol. To provide the count of generate number of rank to search results and preserve the privacy of relevance scores between keywords and files, we propose a novel Additive Order and Privacy Preserving Function family. To intercept the unauthorized attackers from eavesdropping secret keys and pretending to be legal data users submitting searches, we propose a novel dynamic secret key generation protocol and a new data user authentication protocol. Furthermore, PRMSM supports efficient data user revocation. The real world extensive experiments on datasets confirm the efficacy and efficiency of PRMSM.
The system works as follows. KDC is a fully trusted third party by all entities in the system. KDC firstly gen- erates system global parameters and distribute attribute related private keys to users. DS is responsible to gener- ate encrypted files and extract keyword to create secure index, which are outsourced to CSC. Distinct access pol- icy will be sent for different document before uploading. The outsourced health records can be shared with autho- rized users. CSC is deemed as semi-trusted, who is not only honest follow the operations specified by the scheme, but also strive to filch as much as possible information from encrypted EHR content and data retrieval request. DU could execute keyword query on encrypted EHR files. If the DU has attributes that satisfies the access policy defined by the data sender for encrypted documents, DU is capable to operate the data retrieval of those files. DU is able to generate trapdoor for keywordsearch and decrypt EHR files. KDC also has the authority to add or revoke the access right of participants. A revocation list of user will be provided to cloud center.
5.Cong Wang, Ning Cao, Jin Li, Kui Ren , and Wenjing Lou in 2010, To deﬁne and solve the problem of effective yet secure ranked keywordsearch over encrypted cloud data. Ranked search greatly enhances system usability by returning the matching ﬁles in a ranked order regarding to certain relevance criteria. we motivate and solve the problem of supporting efﬁcient ranked keywordsearch for achieving effective utilization of remotely stored encrypted data in Cloud Computing. This approach suffers from two main drawbacks when directly applied in the context of Cloud Computing. On the one hand, users, who do not necessarily have pre- knowledge of the encrypted cloud data, have to postprocess every retrieved ﬁle in order to ﬁnd ones most matching their interest; On the other hand, invariably retrieving all ﬁles containing the queried keyword further incurs unnecessary network trafﬁc,which is absolutely undesirable in today’s pay-as-you-use cloud paradigm.