Privacy-Preserving Genetic Relatedness Test

An increasing number of individuals are turning to Direct-To-Consumer (DTC) genetic testing to learn about their predisposition to diseases, traits, and/or ancestry. DTC companies like 23andme and Ancestry.com have started to offer popular and affordable ancestry and genealogy tests, with services allowing users to find unknown relatives and long-distant cousins. Naturally, access and possible dissemination of genetic data prompts serious privacy concerns, thus motivating the need to design efficient primitives supporting private genetic tests. In this paper, we present an effective protocol for privacy-preserving genetic relatedness test (PPGRT), enabling a cloud server to run relatedness tests on input an encrypted genetic database and a test facility's encrypted genetic sample. We reduce the test to a data matching problem and perform it, privately, using searchable encryption. Finally, a performance evaluation of hamming distance based PP-GRT attests to the practicality of our proposals.Comment: A preliminary version of this paper appears in the Proceedings of the 3rd International Workshop on Genome Privacy and Security (GenoPri'16

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

Efficient Strong Privacy-Preserving Conjunctive Keyword Search Over Encrypted Cloud Data

Searchable symmetric encryption (SSE) supports keyword search over outsourced symmetrically encrypted data. Dynamic searchable symmetric encryption (DSSE), a variant of SSE, further enables data updating. Most DSSE works with conjunctive keyword search primarily consider forward and backward privacy. Ideally, the server should only learn the result sets involving all keywords in the conjunction. However, existing schemes suffer from keyword pair result pattern (KPRP) leakage, revealing the partial result sets containing two of query keywords. We propose the first DSSE scheme to address aforementioned concerns that achieves strong privacy-preserving conjunctive keyword search. Specifically, our scheme can maintain forward and backward privacy and eliminate KPRP leakage, offering a higher level of security. The search complexity scales with the number of documents stored in the database in several existing schemes. However, the complexity of our scheme scales with the update frequency of the least frequent keyword in the conjunction, which is much smaller than the size of the entire database. Besides, we devise a least frequent keyword acquisition protocol to reduce frequent interactions between clients. Finally, we analyze the security of our scheme and evaluate its performance theoretically and experimentally. The results show that our scheme has strong privacy preservation and efficiency

Practical Architectures for Deployment of Searchable Encryption in a Cloud Environment

Public cloud service providers provide an infrastructure that gives businesses and individuals access to computing power and storage space on a pay-as-you-go basis. This allows these entities to bypass the usual costs associated with having their own data centre such as: hardware, construction, air conditioning and security costs, for example, making this a cost-effective solution for data storage. If the data being stored is of a sensitive nature, encrypting it prior to outsourcing it to a public cloud is a good method of ensuring the confidentiality of the data. With the data being encrypted, however, searching over it becomes unfeasible. In this paper, we examine different architectures for supporting search over encrypted data and discuss some of the challenges that need to be overcome if these techniques are to be engineered into practical systems

Secure and Efficient Utilization of Encrypted Cloud Data using Multi-Keyword Ranked Search

Cloud Computing is a technology that provides services to users such as software as a service, platform as a service and storage as a service. These services are provided based on Pay-per-Use basis so these services are cost effective and flexible. Due to this advantage of cloud computing, the individuals as well as the enterprises are getting motivated to shift their local sensitive and huge data management system to cloud storage. But the sensitive data has to be encrypted before outsourcing in order to provide security to the data. After the data has outsourced it has to be utilized efficiently without losing the originality as it was stored. In this paper we provide a mechanism called ”Multi-keyword Ranked Search over Encrypted cloud data” that gives better and efficient searched result over the encrypted data taking multiple keywords as query, which obsoletes the tradition searching scheme based on plain text search. And we use a “Coordinate Matching” technique to find as many matches as possible and use “inner product similarity” to retrieve relevance search results. So if user wants to retrieve the data stored on cloud, he can specify the multiple keywords and rank for relevance retrieval of results. Finally results the user with top ranked files. DOI: 10.17762/ijritcc2321-8169.160415

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

FSPVDsse: A Forward Secure Publicly Verifiable Dynamic SSE scheme

A symmetric searchable encryption (SSE) scheme allows a client (data owner) to search on encrypted data outsourced to an untrusted cloud server. The search may either be a single keyword search or a complex query search like conjunctive or Boolean keyword search. Information leakage is quite high for dynamic SSE, where data might be updated. It has been proven that to avoid this information leakage an SSE scheme with dynamic data must be forward private. A dynamic SSE scheme is said to be forward private, if adding a keyword-document pair does not reveal any information about the previous search result with that keyword. In SSE setting, the data owner has very low computation and storage power. In this setting, though some schemes achieve forward privacy with honest-but-curious cloud, it becomes difficult to achieve forward privacy when the server is malicious, meaning that it can alter the data. Verifiable dynamic SSE requires the server to give a proof of the result of the search query. The data owner can verify this proof efficiently. In this paper, we have proposed a generic publicly verifiable dynamic SSE (DSSE) scheme that makes any forward private DSSE scheme verifiable without losing forward privacy. The proposed scheme does not require any extra storage at owner-side and requires minimal computational cost as well for the owner. Moreover, we have compared our scheme with the existing results and show that our scheme is practical.Comment: 17 pages, Published in ProvSec 201

An In-Depth Analysis on Efficiency and Vulnerabilities on a Cloud-Based Searchable Symmetric Encryption Solution

Searchable Symmetric Encryption (SSE) has come to be as an integral cryptographic approach in a world where digital privacy is essential. The capacity to search through encrypted data whilst maintaining its integrity meets the most important demand for security and confidentiality in a society that is increasingly dependent on cloud-based services and data storage. SSE offers efficient processing of queries over encrypted datasets, allowing entities to comply with data privacy rules while preserving database usability. Our research goes into this need, concentrating on the development and thorough testing of an SSE system based on Curtmola’s architecture and employing Advanced Encryption Standard (AES) in Cypher Block Chaining (CBC) mode. A primary goal of the research is to conduct a thorough evaluation of the security and performance of the system. In order to assess search performance, a variety of database settings were extensively tested, and the system's security was tested by simulating intricate threat scenarios such as count attacks and leakage abuse. The efficiency of operation and cryptographic robustness of the SSE system are critically examined by these reviews