IJERT-Fetching Encrypted Cloud Data Using Searchable Index Scheme (original) (raw)
Related papers
MULTI KEYWORD RANKED SEARCH OVER ENCRYPTED CLOUD DATA
International Journal of Advanced Research in Computer Engineering & Technology (IJARCET), 2018
Cloud computing environment provides on-demand access to shared resources that can be managed with minimal interaction of cloud service provider and validated service to the user. Cloud storage can be either public or private. Data in the public storage can be viewed by all cloud users. The private data can be viewed by the authorized user only. This paper enhance the security of the cloud data using Advanced Encryption Standard (AES) encryption algorithm. Data owners are motivated to outsource their data in cloud servers for great convenience. Private data should be encrypted before outsourcing by using keys. Encryption is an important concept in cloud computing to maintain the database. Existing system maintained the database by providing password for files and documents. The proposed system provides keys to access the file and keys are maintained as private and keys are provided by the data owner. The paper focused ostrovsky scheme (private information retrieval) that allows a user to retrieve file without any information leakage. Experimental result are presented to test the security of AES algorithm and information leakage.
Cloud computing has emerging as a promising pattern for data outsourcing and high-quality data services. However, concerns of sensitive information on cloud potentially causes privacy problems. Data encryption protects data security to some extent, but at the cost of compromised efficiency. Searchable symmetric encryption (SSE) allows retrieval of encrypted data over cloud. In this paper, we focus on addressing data privacy issues using searchable symmetric encryption (SSE). For the first time, we formulate the privacy issue from the aspect of similarity relevance and scheme robustness. We observe that server-side ranking based on order-preserving encryption (OPE) inevitably leaks data privacy. To eliminate the leakage, we propose a two-round searchable encryption (TRSE) scheme that supports top-k multi-keyword retrieval. In TRSE, we employ a vector space model and homomorphic encryption. The vector space model helps to provide sufficient search accuracy, and the homomorphic encryption enables users to involve in the ranking while the majority of computing work is done on the server side by operations only on ciphertext. As a result, information leakage can be eliminated and data security is ensured. Thorough security and performance analysis show that the proposed scheme guarantees high security and practical efficiency.
Efficient Multi-User and Multi-Keyword Ranked Search Scheme for Encrypted Cloud Data
International Journal of Advanced Trends in Computer Science and Engineering, 2020
With the improvement of cloud storage, greater data users are willing to outsource their data to cloud offerings. For privacy issues, sensitive data must be encrypted before outsourcing. There are numerous searchable encryption schemes to ensure statistics availability. However, the present search schemes pay little attention to the performance of facts users' queries, specifically for the multiuser situation. To allow the cloud servers to perform a search without understanding any statistics, to assemble a novel search and efficient technique based totally on the encrypted cloud statistics the usage of the "ECC cryptography scheme". To obtain an efficient search, for every statistics person, a tree-based totally index encrypted with an additive order and secure characteristic is constructed. In order to rank the search outcomes, the proposed method utilize and model the relevance ratings of facts documents and advise a ``Iterative Deepening Depth-First Search'' (ID-DFS) set of rules to attain the ranked results. To perform a keyword-primarily based query, the complete records set needs to be decrypted despite the fact that the matching end result set may be very small. It poses insufferable query latency and incurs unacceptable computational overhead. Finally, the proposed approach confirms the security and performance of the proposed scheme through complete theoretical evaluation and big experiments with real dataset.
Secure Access of Encrypted Cloud Data Based on Top-K Multikeywords with User Side Ranking
International journal of engineering research and technology, 2018
Cloud computing has become popular due to the huge storage and flexible access from around the world. The data owners are motivated to outsource their data from local servers to the commercial public cloud for great flexibility and cost savings. But the data owner cannot trust the cloud server provider due to the confidential data. So to protect data privacy, sensitive data have to be encrypted before outsourcing to the public cloud, due to which traditional data based on plaintext keyword search is not possible. So there is a requirement for cloud data search on encrypted data. As the number of users are large and huge number of documents in the cloud, it is important to allow multiple keywords in the search request and return the resultant documents in the order of their relevance to these keywords. Existing works on searchable encryption focus on single keyword search or Boolean keyword search, and rarely sort the search results. In this paper, for the first time, we define and s...
Towards Secure Multi-Keyword Top-k Retrieval over Encrypted Cloud Data
Cloud computing has emerging as a promising pattern for data outsourcing and high-quality data services. However, concerns of sensitive information on cloud potentially causes privacy problems. Data encryption protects data security to some extent, but at the cost of compromised efficiency. Searchable symmetric encryption (SSE) allows retrieval of encrypted data over cloud. In this paper, we focus on addressing data privacy issues using searchable symmetric encryption (SSE). For the first time, we formulate the privacy issue from the aspect of similarity relevance and scheme robustness. We observe that server-side ranking based on order-preserving encryption (OPE) inevitably leaks data privacy. To eliminate the leakage, we propose a two-round searchable encryption (TRSE) scheme that supports top-k multi-keyword retrieval. In TRSE, we employ a vector space model and homomorphic encryption. The vector space model helps to provide sufficient search accuracy, and the homomorphic encryption enables users to involve in the ranking while the majority of computing work is done on the server side by operations only on ciphertext. As a result, information leakage can be eliminated and data security is ensured. Thorough security and performance analysis show that the proposed scheme guarantees high security and practical efficiency.
An Optimized and Secured Ranking Approach for Retrieving Cloud Data Using Keyword Search
Cloud computing is a versatile technology that emerged as a solution to reduce costs in organizations by providing on-demand high quality applications and services from a centralized pool of configurable computing resources. With the advantage of storage as a service data owners are motivated to outsource their valuable and sensitive data from local sites to commercial public cloud since it costs less, easily scalable and can be accessed from anywhere anytime. Sensitive data that moves into and across cloud infrastructures increases the risk of data loss or compliance violations. However to protect data privacy, sensitive cloud data have to be encrypted before outsourcing. Data encryption makes effective data utilization a very challenging task. In this paper we define an optimized and secured semantic based ranked keyword search over encrypted cloud data. Existing search schemes are not much efficient as they entirely depend on the submitted query keyword and did not consider the keyword semantics. Ranking approach in the proposed scheme not only consider the keyword semantics but also deals with examining the different forms of a queried keyword for retrieving the most matching files relevant to the user request. This type of ranked search enhances system usability by computing relevance score and ensures security guarantee by using an order preserving symmetric encryption technique to protect those sensitive score information. Here user can retrieve more files from cloud server with less communication overhead.
An Encrypted and Dynamic Multi-Keyword Ranked Search in Cloud Storage
Recently, advancement of private and semi-private information has grown up rapidly on information mastermind; instruments to interest such information have bombarded in security protecting. The security sparing looking for is expecting basic part in the field of information frameworks to perform diverse data mining activities on encoded data set away in various storing systems. It is furthermore fundamental and testing undertaking to secure the mystery of private data shared among master communities and data proprietors. Existing system gives one possible course of action that is security protecting requesting (PPI). In this structure, chronicles are secured fit as a fiddle on private server that is security is exchanged off. So to enhance this system to influence it more to secure and viable, first we store the records on server fit as a fiddle and after that usage Key Distribution Center (KDC) for allowing deciphering of data gotten from private server, at client side. We moreover complete TF-IDF, which gives the compelling situating of results, to improve the customer look inclusion. Finally we coordinate the wide tests on dataset, to survey the execution of our proposed structure. Exploratory results will show that the proposed system is better than anything existing one, to the extent, insurance protecting, capable and secure request on mixed appropriated files.
55 A protected and active Multi-keyword Ranked Search intend over Encrypted Cloud Records
With the advent of cloud computing, data owners are motivated to outsource their complex data management systems from local sites to the commercial public cloud for great flexibility and economic savings. But for protecting data privacy, sensitive data has to be encrypted before outsourcing, which obsoletes traditional data utilization based on plaintext keyword search. Thus, enabling an encrypted cloud data search service is of paramount importance. Considering the large number of data users and documents in the cloud, it is necessary to allow multiple keywords in the search request and return documents in the order of their relevance to these keywords. Related works on searchable encryption focus on single keyword search or Boolean keyword search, and rarely sort the search results. In this paper, for the first time, we define and solve the challenging problem of privacy-preserving multi-keyword ranked search over encrypted cloud data (MRSE). We establish a set of strict privacy requirements for such a secure cloud data utilization system. Among various multi-keyword semantics, we choose the efficient similarity measure of " coordinate matching " , i.e., as many matches as possible, to capture the relevance of data documents to the search query. We further use " inner product similarity " to quantitatively evaluate such similarity measure. We first propose a basic idea for the MRSE based on secure inner product computation, and then give two significantly improved MRSE schemes to achieve various stringent privacy requirements in two different threat models. Thorough analysis investigating privacy and efficiency guarantees of proposed schemes is given. Experiments on the real-world dataset further show proposed schemes indeed introduce low overhead on computation and communication.
Information Security and Secure Search Over Encrypted Data in Cloud Storage Services
2016
Cloud computing is most widely used as the next generation architecture of IT enterprises, that provide convenient remote access to data storage and application services. This cloud storage can potentially bring great economical savings for data owners and users, but due to wide concerns of data owners that their private data may be exposed or handled by cloud providers. Hence end-to-end encryption techniques and fuzzy fingerprint technique have been used as solutions for secure cloud data storage. In this project we use searchable encryption techniques, which allows encrypted data to be searched by users without leaking information about the data itself and user's queries. We build a secure searchable index, and develop a one to many order preserving mapping technique to protect those sensitive score information. The resulting design is able to facilitate efficient server side ranking without losing keyword privacy. Hence to avoid loose and loss of data, we use privacy preserving data-leak detection (DLD) solution to solve the issue where sensitive data digests is used in detection. The advantage of this method is that it enables the data owner to safely delegate the detection operation to a semi honest provider without revealing the sensitive data to the provider.In this project, we identify the challenges towards achieving privacy in searchable outsourced cloud data services and we use the DLD solution which helps to detect the leak data. This technique helps us to save securely our sensitive data in cloud storage and retrieve this data while we required without leaking our private data through Information Security and Secure Search over Encrypted Data in Cloud Storage Services.
Secure Ranked Keyword Search over Encrypted Cloud Data
2010 IEEE 30th International Conference on Distributed Computing Systems, 2010
As Cloud Computing becomes prevalent, sensitive information are being increasingly centralized into the cloud. For the protection of data privacy, sensitive data has to be encrypted before outsourcing, which makes effective data utilization a very challenging task. Although traditional searchable encryption schemes allow users to securely search over encrypted data through keywords, these techniques support only boolean search, without capturing any relevance of data files. 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. In this paper, for the first time we define and solve the problem of effective yet secure ranked keyword search over encrypted cloud data. Ranked search greatly enhances system usability by returning the matching files in a ranked order regarding to certain relevance criteria (e.g., keyword frequency), thus making one step closer towards practical deployment of privacy-preserving data hosting services in Cloud Computing. We first give a straightforward yet ideal construction of ranked keyword search under the state-of-the-art searchable symmetric encryption (SSE) security definition, and demonstrate its inefficiency. To achieve more practical performance, we then propose a definition for ranked searchable symmetric encryption, and give an efficient design by properly utilizing the existing cryptographic primitive, order-preserving symmetric encryption (OPSE). Thorough analysis shows that our proposed solution enjoys "as-strong-aspossible" security guarantee compared to previous SSE schemes, while correctly realizing the goal of ranked keyword search. Extensive experimental results demonstrate the efficiency of the proposed solution.