272 research outputs found
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
Trusted Computing and Secure Virtualization in Cloud Computing
Large-scale deployment and use of cloud computing in industry
is accompanied and in the same time hampered by concerns regarding protection of
data handled by cloud computing providers. One of the consequences of moving
data processing and storage off company premises is that organizations have
less control over their infrastructure. As a result, cloud service (CS) clients
must trust that the CS provider is able to protect their data and
infrastructure from both external and internal attacks. Currently however, such
trust can only rely on organizational processes declared by the CS
provider and can not be remotely verified and validated by an external party.
Enabling the CS client to verify the integrity of the host where the
virtual machine instance will run, as well as to ensure that the virtual
machine image has not been tampered with, are some steps towards building
trust in the CS provider. Having the tools to perform such
verifications prior to the launch of the VM instance allows the CS
clients to decide in runtime whether certain data should be stored- or calculations
should be made on the VM instance offered by the CS provider.
This thesis combines three components -- trusted computing, virtualization technology
and cloud computing platforms -- to address issues of trust and
security in public cloud computing environments. Of the three components,
virtualization technology has had the longest evolution and is a cornerstone
for the realization of cloud computing. Trusted computing is a recent
industry initiative that aims to implement the root of trust in a hardware
component, the trusted platform module. The initiative has been formalized
in a set of specifications and is currently at version 1.2. Cloud computing
platforms pool virtualized computing, storage and network resources in
order to serve a large number of customers customers that use a multi-tenant
multiplexing model to offer on-demand self-service over broad network.
Open source cloud computing platforms are, similar to trusted computing, a
fairly recent technology in active development.
The issue of trust in public cloud environments is addressed
by examining the state of the art within cloud computing security and
subsequently addressing the issues of establishing trust in the launch of a
generic virtual machine in a public cloud environment. As a result, the thesis
proposes a trusted launch protocol that allows CS clients
to verify and ensure the integrity of the VM instance at launch time, as
well as the integrity of the host where the VM instance is launched. The protocol
relies on the use of Trusted Platform Module (TPM) for key generation and data protection.
The TPM also plays an essential part in the integrity attestation of the
VM instance host. Along with a theoretical, platform-agnostic protocol,
the thesis also describes a detailed implementation design of the protocol
using the OpenStack cloud computing platform.
In order the verify the implementability of the proposed protocol, a prototype
implementation has built using a distributed deployment of OpenStack.
While the protocol covers only the trusted launch procedure using generic
virtual machine images, it presents a step aimed to contribute towards
the creation of a secure and trusted public cloud computing environment
OS2: Oblivious similarity based searching for encrypted data outsourced to an untrusted domain
© 2017 Pervez et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Public cloud storage services are becoming prevalent and myriad data sharing, archiving and collaborative services have emerged which harness the pay-as-you-go business model of public cloud. To ensure privacy and confidentiality often encrypted data is outsourced to such services, which further complicates the process of accessing relevant data by using search queries. Search over encrypted data schemes solve this problem by exploiting cryptographic primitives and secure indexing to identify outsourced data that satisfy the search criteria. Almost all of these schemes rely on exact matching between the encrypted data and search criteria. A few schemes which extend the notion of exact matching to similarity based search, lack realism as those schemes rely on trusted third parties or due to increase storage and computational complexity. In this paper we propose Oblivious Similarity based Search (OS2) for encrypted data. It enables authorized users to model their own encrypted search queries which are resilient to typographical errors. Unlike conventional methodologies, OS2 ranks the search results by using similarity measure offering a better search experience than exact matching. It utilizes encrypted bloom filter and probabilistic homomorphic encryption to enable authorized users to access relevant data without revealing results of search query evaluation process to the untrusted cloud service provider. Encrypted bloom filter based search enables OS2 to reduce search space to potentially relevant encrypted data avoiding unnecessary computation on public cloud. The efficacy of OS2 is evaluated on Google App Engine for various bloom filter lengths on different cloud configurations
Survey on securing data storage in the cloud
Cloud Computing has become a well-known primitive nowadays; many researchers and companies are embracing this fascinating technology with feverish haste. In the meantime, security and privacy challenges are brought forward while the number of cloud storage user increases expeditiously. In this work, we conduct an in-depth survey on recent research activities of cloud storage security in association with cloud computing. After an overview of the cloud storage system and its security problem, we focus on the key security requirement triad, i.e., data integrity, data confidentiality, and availability. For each of the three security objectives, we discuss the new unique challenges faced by the cloud storage services, summarize key issues discussed in the current literature, examine, and compare the existing and emerging approaches proposed to meet those new challenges, and point out possible extensions and futuristic research opportunities. The goal of our paper is to provide a state-of-the-art knowledge to new researchers who would like to join this exciting new field
Cloud technology options towards Free Flow of Data
This whitepaper collects the technology solutions that the projects in the Data Protection, Security and Privacy Cluster propose to address the challenges raised by the working areas of the Free Flow of Data initiative. The document describes the technologies, methodologies, models, and tools researched and developed by the clustered projects mapped to the ten areas of work of the Free Flow of Data initiative. The aim is to facilitate the identification of the state-of-the-art of technology options towards solving the data security and privacy challenges posed by the Free Flow of Data initiative in Europe. The document gives reference to the Cluster, the individual projects and the technologies produced by them
Privacy-Preserving Secret Shared Computations using MapReduce
Data outsourcing allows data owners to keep their data at \emph{untrusted}
clouds that do not ensure the privacy of data and/or computations. One useful
framework for fault-tolerant data processing in a distributed fashion is
MapReduce, which was developed for \emph{trusted} private clouds. This paper
presents algorithms for data outsourcing based on Shamir's secret-sharing
scheme and for executing privacy-preserving SQL queries such as count,
selection including range selection, projection, and join while using MapReduce
as an underlying programming model. Our proposed algorithms prevent an
adversary from knowing the database or the query while also preventing
output-size and access-pattern attacks. Interestingly, our algorithms do not
involve the database owner, which only creates and distributes secret-shares
once, in answering any query, and hence, the database owner also cannot learn
the query. Logically and experimentally, we evaluate the efficiency of the
algorithms on the following parameters: (\textit{i}) the number of
communication rounds (between a user and a server), (\textit{ii}) the total
amount of bit flow (between a user and a server), and (\textit{iii}) the
computational load at the user and the server.\BComment: IEEE Transactions on Dependable and Secure Computing, Accepted 01
Aug. 201
TSKY: a dependable middleware solution for data privacy using public storage clouds
Dissertação para obtenção do Grau de Mestre em Engenharia InformáticaThis dissertation aims to take advantage of the virtues offered by data storage cloud based systems on the Internet, proposing a solution that avoids security issues by combining different providers’ solutions in a vision of a cloud-of-clouds storage and computing. The solution, TSKY System (or Trusted Sky), is implemented as a middleware system, featuring a set of components designed to establish and to enhance conditions for security, privacy, reliability and availability of data, with these conditions being secured and verifiable by the end-user, independently of each provider. These components, implement cryptographic tools, including threshold and homomorphic cryptographic schemes, combined with encryption, replication, and dynamic indexing mecha-nisms. The solution allows data management and distribution functions over data kept in different storage clouds, not necessarily trusted, improving and ensuring resilience and security guarantees against Byzantine faults and at-tacks. The generic approach of the TSKY system model and its implemented services are evaluated in the context of a Trusted Email Repository System (TSKY-TMS System). The TSKY-TMS system is a prototype that uses the base TSKY middleware services to store mailboxes and email Messages in a cloud-of-clouds
HardIDX: Practical and Secure Index with SGX
Software-based approaches for search over encrypted data are still either
challenged by lack of proper, low-leakage encryption or slow performance.
Existing hardware-based approaches do not scale well due to hardware
limitations and software designs that are not specifically tailored to the
hardware architecture, and are rarely well analyzed for their security (e.g.,
the impact of side channels). Additionally, existing hardware-based solutions
often have a large code footprint in the trusted environment susceptible to
software compromises. In this paper we present HardIDX: a hardware-based
approach, leveraging Intel's SGX, for search over encrypted data. It implements
only the security critical core, i.e., the search functionality, in the trusted
environment and resorts to untrusted software for the remainder. HardIDX is
deployable as a highly performant encrypted database index: it is logarithmic
in the size of the index and searches are performed within a few milliseconds
rather than seconds. We formally model and prove the security of our scheme
showing that its leakage is equivalent to the best known searchable encryption
schemes. Our implementation has a very small code and memory footprint yet
still scales to virtually unlimited search index sizes, i.e., size is limited
only by the general - non-secure - hardware resources
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