A Practical Framework for Storing and Searching Encrypted Data on Cloud Storage

Security has become a significant concern with the increased popularity of cloud storage services. It comes with the vulnerability of being accessed by third parties. Security is one of the major hurdles in the cloud server for the user when the user data that reside in local storage is outsourced to the cloud. It has given rise to security concerns involved in data confidentiality even after the deletion of data from cloud storage. Though, it raises a serious problem when the encrypted data needs to be shared with more people than the data owner initially designated. However, searching on encrypted data is a fundamental issue in cloud storage. The method of searching over encrypted data represents a significant challenge in the cloud. Searchable encryption allows a cloud server to conduct a search over encrypted data on behalf of the data users without learning the underlying plaintexts. While many academic SE schemes show provable security, they usually expose some query information, making them less practical, weak in usability, and challenging to deploy. Also, sharing encrypted data with other authorized users must provide each document's secret key. However, this way has many limitations due to the difficulty of key management and distribution. We have designed the system using the existing cryptographic approaches, ensuring the search on encrypted data over the cloud. The primary focus of our proposed model is to ensure user privacy and security through a less computationally intensive, user-friendly system with a trusted third party entity. To demonstrate our proposed model, we have implemented a web application called CryptoSearch as an overlay system on top of a well-known cloud storage domain. It exhibits secure search on encrypted data with no compromise to the user-friendliness and the scheme's functional performance in real-world applications.Comment: 146 Pages, Master's Thesis, 6 Chapters, 96 Figures, 11 Table

A practical and secure multi-keyword search method over encrypted cloud data

Cloud computing technologies become more and more popular every year, as many organizations tend to outsource their data utilizing robust and fast services of clouds while lowering the cost of hardware ownership. Although its benefits are welcomed, privacy is still a remaining concern that needs to be addressed. We propose an efficient privacy-preserving search method over encrypted cloud data that utilizes minhash functions. Most of the work in literature can only support a single feature search in queries which reduces the effectiveness. One of the main advantages of our proposed method is the capability of multi-keyword search in a single query. The proposed method is proved to satisfy adaptive semantic security definition. We also combine an effective ranking capability that is based on term frequency-inverse document frequency (tf-idf) values of keyword document pairs. Our analysis demonstrates that the proposed scheme is proved to be privacy-preserving, efficient and effective

Split keyword fuzzy and synonym search over encrypted cloud data

A substitute solution for various organizations of data owners to store their data in the cloud using storage as a service(SaaS). The outsourced sensitive data is encrypted before uploading into the cloud to achieve data privacy. The encrypted data is search based on keywords and retrieve interested files by data user using a lot of traditional Search scheme. Existing search schemes supports exact keyword match or fuzzy keyword search, but synonym based multi-keyword search are not supported. In the real world scenario, cloud users may not know the exact keyword for searching and they might give synonym of the keyword as the input for search instead of exact or fuzzy keyword due to lack of appropriate knowledge of data. In this paper, we describe an efficient search approach for encrypted data called as Split Keyword Fuzzy and Synonym Search (SKFS). Multi-keyword ranked search with accurate keyword and Fuzzy search supports synonym queries are a major contribution of SKFS. The wildcard Technique is used to store the keywords securely within the index tree. Index tree helps to search faster, accurate and low storage cost. Extensive experimental results on real-time data sets shows, the proposed solution is effective and efficient for multi-keyword ranked search and synonym queries Fuzzy based search over encrypted cloud data. © 2017 Springer Science+Business Media, LL

Fuzzy keywords enabled ranked searchable encryption scheme for a public Cloud environment

Searchable Encryption allows a user or organization to outsource their encrypted documents to a Cloud-based storage service, while maintaining the ability to perform keyword searches over the encrypted text. However, most of the existing search schemes do not take the almost certain presence of typographical errors in the documents under consideration, when trying to obtain meaningful and accurate results. This paper presents a novel ranked searchable encryption scheme that addresses this issue by supporting fuzzy keywords. The proposed construction is based on probabilistic trapdoors that help resist distinguishability attacks. This paper for the first time proposes Searchable Encryption as a Service (SEaaS). The proposed construction is deployed on the British Telecommunication’s public Cloud architecture and evaluated over a real-life speech corpus. Our security analysis yields that the construction satisfies strong security guarantees and is also quiet lightweight, by analyzing its performance over the speech corpus

A New Secure and Lightweight Searchable Encryption Scheme over Encrypted Cloud Data

Searchable Encryption is an emerging cryptographic technique that enables searching capabilities over the encrypted data on the cloud. In this paper, a novel searchable encryption scheme for the client-server architecture has been presented. The scheme exploits the properties of modular inverse to generate a probabilistic trapdoor which facilitates the searching over the secure inverted index table. We propose indistinguishability that is achieved by using the property of a probabilistic trapdoor. We design and implement a proof of concept prototype and test our scheme onto a real dataset of files. We analyze the performance of our scheme against our claim of the scheme being light weight. The security analysis yields that our scheme assures higher level of security as compared to other existing schemes

A Survey and Security Analysis on One-To-Many Order Preserving Technique on Cloud Data

The data on cloud computing is encrypted due to security concern or the factor of third party digging into it. As the consequence to this, the search over encrypted data becomes a complex task. The traditional approaches like searching in plain text cannot be apply over encrypted data. So the searchable encryption techniques are being used. In searchable encryption techniques the order of relevance must be consider as the concern because when it is large amount of data it becomes complex as relevant documents are more in number. We have discussed the probabilistic OPE technique known as one-to-many OPE. The expected result is to be that cloud server cannot penetrate in actual user data and provide the search on encrypted data will be performed and results will appear in order of relevance score. Even though with good security of one-to-many OPE the cloud can get the information of the plain text if differential attack occurred on the cipher text by calculating the differences between the cipher text