321 research outputs found
GraphSE: An Encrypted Graph Database for Privacy-Preserving Social Search
In this paper, we propose GraphSE, an encrypted graph database for online
social network services to address massive data breaches. GraphSE preserves
the functionality of social search, a key enabler for quality social network
services, where social search queries are conducted on a large-scale social
graph and meanwhile perform set and computational operations on user-generated
contents. To enable efficient privacy-preserving social search, GraphSE
provides an encrypted structural data model to facilitate parallel and
encrypted graph data access. It is also designed to decompose complex social
search queries into atomic operations and realise them via interchangeable
protocols in a fast and scalable manner. We build GraphSE with various
queries supported in the Facebook graph search engine and implement a
full-fledged prototype. Extensive evaluations on Azure Cloud demonstrate that
GraphSE is practical for querying a social graph with a million of users.Comment: This is the full version of our AsiaCCS paper "GraphSE: An
Encrypted Graph Database for Privacy-Preserving Social Search". It includes
the security proof of the proposed scheme. If you want to cite our work,
please cite the conference version of i
Novel Proposed Work for Empirical Word Searching in Cloud Environment
People's lives have become much more convenient as a result of the development of cloud storage. The third-party server has received a lot of data from many people and businesses for storage. Therefore, it is necessary to ensure that the user's data is protected from prying eyes. In the cloud environment, searchable encryption technology is used to protect user information when retrieving data. The versatility of the scheme is, however, constrained by the fact that the majority of them only offer single-keyword searches and do not permit file changes.A novel empirical multi-keyword search in the cloud environment technique is offered as a solution to these issues. Additionally, it prevents the involvement of a third party in the transaction between data holder and user and guarantees integrity. Our system achieves authenticity at the data storage stage by numbering the files, verifying that the user receives a complete ciphertext. Our technique outperforms previous analogous schemes in terms of security and performance and is resistant to inside keyword guessing attacks.The server cannot detect if the same set of keywords is being looked for by several queries because our system generates randomized search queries. Both the number of keywords in a search query and the number of keywords in an encrypted document can be hidden. Our searchable encryption method is effective and protected from the adaptive chosen keywords threat at the same time
Secured Uploading and Retrieval of Data Using Visual Cryptography Scheme
Cloud storage provides a convenient, massive, and scalable storage at low cost, but data security is a major issue that prevents users from storing ?les on the cloud. This paper focuses on security for the documents that are uploaded and stored on the cloud. However, it poses risks to end users unless the data is encrypted for security. This study addresses these issues by proposing Visual Cryptography Scheme (VCS) for securing the files. In order to prevent issues like breaches and malware attacks on cloud, this innovative scheme helps in high level security to safeguard the files that are stored on the clou
Privacy-preserving efficient searchable encryption
Data storage and computation outsourcing to third-party managed data centers,
in environments such as Cloud Computing, is increasingly being adopted
by individuals, organizations, and governments. However, as cloud-based outsourcing
models expand to society-critical data and services, the lack of effective
and independent control over security and privacy conditions in such settings
presents significant challenges.
An interesting solution to these issues is to perform computations on encrypted
data, directly in the outsourcing servers. Such an approach benefits
from not requiring major data transfers and decryptions, increasing performance
and scalability of operations. Searching operations, an important application
case when cloud-backed repositories increase in number and size, are good examples
where security, efficiency, and precision are relevant requisites. Yet existing
proposals for searching encrypted data are still limited from multiple perspectives,
including usability, query expressiveness, and client-side performance and
scalability.
This thesis focuses on the design and evaluation of mechanisms for searching
encrypted data with improved efficiency, scalability, and usability. There are
two particular concerns addressed in the thesis: on one hand, the thesis aims at
supporting multiple media formats, especially text, images, and multimodal data
(i.e. data with multiple media formats simultaneously); on the other hand the
thesis addresses client-side overhead, and how it can be minimized in order to
support client applications executing in both high-performance desktop devices
and resource-constrained mobile devices.
From the research performed to address these issues, three core contributions
were developed and are presented in the thesis: (i) CloudCryptoSearch, a middleware
system for storing and searching text documents with privacy guarantees,
while supporting multiple modes of deployment (user device, local proxy, or computational cloud) and exploring different tradeoffs between security, usability, and performance; (ii) a novel framework for efficiently searching encrypted images
based on IES-CBIR, an Image Encryption Scheme with Content-Based Image
Retrieval properties that we also propose and evaluate; (iii) MIE, a Multimodal
Indexable Encryption distributed middleware that allows storing, sharing, and
searching encrypted multimodal data while minimizing client-side overhead and
supporting both desktop and mobile devices
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