2,804 research outputs found
Achieving Secure and Efficient Cloud Search Services: Cross-Lingual Multi-Keyword Rank Search over Encrypted Cloud Data
Multi-user multi-keyword ranked search scheme in arbitrary language is a
novel multi-keyword rank searchable encryption (MRSE) framework based on
Paillier Cryptosystem with Threshold Decryption (PCTD). Compared to previous
MRSE schemes constructed based on the k-nearest neighbor searcha-ble encryption
(KNN-SE) algorithm, it can mitigate some draw-backs and achieve better
performance in terms of functionality and efficiency. Additionally, it does not
require a predefined keyword set and support keywords in arbitrary languages.
However, due to the pattern of exact matching of keywords in the new MRSE
scheme, multilingual search is limited to each language and cannot be searched
across languages. In this pa-per, we propose a cross-lingual multi-keyword rank
search (CLRSE) scheme which eliminates the barrier of languages and achieves
semantic extension with using the Open Multilingual Wordnet. Our CLRSE scheme
also realizes intelligent and per-sonalized search through flexible keyword and
language prefer-ence settings. We evaluate the performance of our scheme in
terms of security, functionality, precision and efficiency, via extensive
experiments
Privacy-preserving targeted advertising scheme for IPTV using the cloud
In this paper, we present a privacy-preserving scheme for targeted advertising via the Internet Protocol TV (IPTV). The scheme uses a communication model involving a collection of viewers/subscribers, a content provider (IPTV), an advertiser, and a cloud server. To provide high quality directed advertising service, the advertiser can utilize not only demographic information of subscribers, but also their watching habits. The latter includes watching history, preferences for IPTV content and watching rate, which are published on the cloud server periodically (e.g. weekly) along with anonymized demographics. Since the published data may leak sensitive information about subscribers, it is safeguarded using cryptographic techniques in addition to the anonymization of demographics. The techniques used by the advertiser, which can be manifested in its queries to the cloud, are considered (trade) secrets and therefore are protected as well. The cloud is oblivious to the published data, the queries of the advertiser as well as its own responses to these queries. Only a legitimate advertiser, endorsed with a so-called {\em trapdoor} by the IPTV, can query the cloud and utilize the query results. The performance of the proposed scheme is evaluated with experiments, which show that the scheme is suitable for practical usage
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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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
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