124,482 research outputs found
Towards A Well-Secured Electronic Health Record in the Health Cloud
The major concerns for most cloud implementers particularly in the health care industry have remained data security
and privacy. A prominent and major threat that constitutes a hurdle for practitioners within the health industry from exploiting and
benefiting from the gains of cloud computing is the fear of theft of patients health data in the cloud. Investigations and surveys
have revealed that most practitioners in the health care industry are concerned about the risk of health data mix-up amongst the
various cloud providers, hacking to comprise the cloud platform and theft of vital patients’ health data.An overview of the
diverse issues relating to health data privacy and overall security in the cloud are presented in this technical report. Based on
identifed secure access requirements, an encryption-based eHR security model for securing and enforcing authorised access to
electronic health data (records), eHR is also presented. It highlights three core functionalities for managing issues relating to
health data privacy and security of eHR in health care cloud
My Private Cloud Overview: A Trust, Privacy and Security Infrastructure for the Cloud
Based on the assumption that cloud providers can be trusted (to a certain extent) we define a trust, security and privacy preserving infrastructure that relies on trusted cloud providers to operate properly. Working in tandem with legal agreements, our open source software supports: trust and reputation management, sticky policies with fine grained access controls, privacy preserving delegation of authority, federated identity management, different levels of assurance and configurable audit trails. Armed with these tools, cloud service providers are then able to offer a reliable privacy preserving infrastructure-as-a-service to their clients
AnonyControl: Control Cloud Data Anonymously with Multi-Authority Attribute-Based Encryption
Cloud computing is a revolutionary computing paradigm which enables flexible,
on-demand and low-cost usage of computing resources. However, those advantages,
ironically, are the causes of security and privacy problems, which emerge
because the data owned by different users are stored in some cloud servers
instead of under their own control. To deal with security problems, various
schemes based on the Attribute- Based Encryption (ABE) have been proposed
recently. However, the privacy problem of cloud computing is yet to be solved.
This paper presents an anonymous privilege control scheme AnonyControl to
address the user and data privacy problem in a cloud. By using multiple
authorities in cloud computing system, our proposed scheme achieves anonymous
cloud data access, finegrained privilege control, and more importantly,
tolerance to up to (N -2) authority compromise. Our security and performance
analysis show that AnonyControl is both secure and efficient for cloud
computing environment.Comment: 9 pages, 6 figures, 3 tables, conference, IEEE INFOCOM 201
"If You Can't Beat them, Join them": A Usability Approach to Interdependent Privacy in Cloud Apps
Cloud storage services, like Dropbox and Google Drive, have growing
ecosystems of 3rd party apps that are designed to work with users' cloud files.
Such apps often request full access to users' files, including files shared
with collaborators. Hence, whenever a user grants access to a new vendor, she
is inflicting a privacy loss on herself and on her collaborators too. Based on
analyzing a real dataset of 183 Google Drive users and 131 third party apps, we
discover that collaborators inflict a privacy loss which is at least 39% higher
than what users themselves cause. We take a step toward minimizing this loss by
introducing the concept of History-based decisions. Simply put, users are
informed at decision time about the vendors which have been previously granted
access to their data. Thus, they can reduce their privacy loss by not
installing apps from new vendors whenever possible. Next, we realize this
concept by introducing a new privacy indicator, which can be integrated within
the cloud apps' authorization interface. Via a web experiment with 141
participants recruited from CrowdFlower, we show that our privacy indicator can
significantly increase the user's likelihood of choosing the app that minimizes
her privacy loss. Finally, we explore the network effect of History-based
decisions via a simulation on top of large collaboration networks. We
demonstrate that adopting such a decision-making process is capable of reducing
the growth of users' privacy loss by 70% in a Google Drive-based network and by
40% in an author collaboration network. This is despite the fact that we
neither assume that users cooperate nor that they exhibit altruistic behavior.
To our knowledge, our work is the first to provide quantifiable evidence of the
privacy risk that collaborators pose in cloud apps. We are also the first to
mitigate this problem via a usable privacy approach.Comment: Authors' extended version of the paper published at CODASPY 201
Flexible Yet Secure De-Duplication Service for Enterprise Data on Cloud Storage
The cloud storage services bring forth infinite storage capacity and flexible access capability to store and share
large-scale content. The convenience brought forth has attracted both individual and enterprise users to outsource data service to a cloud provider. As the survey shows 56% of the usages of cloud storage applications are for data back up and up to 68% of data backup are user assets. Enterprise tenants would need to protect their data privacy before uploading them to the cloud and expect a reasonable performance while they try to reduce the operation cost in terms of cloud storage, capacity and I/Os matter as well
as systems’ performance, bandwidth and data protection. Thus, enterprise tenants demand secure and economic data storage yet flexible access on their cloud data.
In this paper, we propose a secure de-duplication solution
for enterprise tenants to leverage the benefits of cloud storage while reducing operation cost and protecting privacy. First, the solution uses a proxy to do flexible group access control which supports secure de-duplication within a group; Second, the solution supports scalable clustering of proxies to support large-scale data access; Third, the solution can be integrated with cloud storage seamlessly. We implemented and tested our solution by integrating it with Dropbox. Secure de-duplication in a group is performed at low data transfer latency and small
storage overhead as compared to de-duplication on plaintext
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Privacy Preserving Attribute Based Encryption for Multiple Cloud Collaborative Environment
In a Multiple Cloud Collaborative Environment (MCCE), cloud users and cloud providers interact with each other via a brokering service to request and provision cloud services. The brokering service considers several pieces of data to broker the best deal between users and providers which can subsequently risks the privacy and security of MCCE. In this paper, we propose a Privacy Preserving Attribute-Based Encryption(PPABE) scheme which protects MCCE from a compromised broker. The proposed encryption scheme preserves the privacy by employing data access policy over sets of attributes. The identifying attributes are anonymoized using pseudonyms. The data access policy is further anonymized so as it remain unknown to unauthorized parties. The PP-ABE achieves unlinkability between different data items which flows through the collaborative cloud environment and preserves the privacy of cloud users and cloud providers
A JSON Token-Based Authentication and Access Management Schema for Cloud SaaS Applications
Cloud computing is significantly reshaping the computing industry built
around core concepts such as virtualization, processing power, connectivity and
elasticity to store and share IT resources via a broad network. It has emerged
as the key technology that unleashes the potency of Big Data, Internet of
Things, Mobile and Web Applications, and other related technologies, but it
also comes with its challenges - such as governance, security, and privacy.
This paper is focused on the security and privacy challenges of cloud computing
with specific reference to user authentication and access management for cloud
SaaS applications. The suggested model uses a framework that harnesses the
stateless and secure nature of JWT for client authentication and session
management. Furthermore, authorized access to protected cloud SaaS resources
have been efficiently managed. Accordingly, a Policy Match Gate (PMG) component
and a Policy Activity Monitor (PAM) component have been introduced. In
addition, other subcomponents such as a Policy Validation Unit (PVU) and a
Policy Proxy DB (PPDB) have also been established for optimized service
delivery. A theoretical analysis of the proposed model portrays a system that
is secure, lightweight and highly scalable for improved cloud resource security
and management.Comment: 6 Page
The Curious Case of the PDF Converter that Likes Mozart: Dissecting and Mitigating the Privacy Risk of Personal Cloud Apps
Third party apps that work on top of personal cloud services such as Google
Drive and Dropbox, require access to the user's data in order to provide some
functionality. Through detailed analysis of a hundred popular Google Drive apps
from Google's Chrome store, we discover that the existing permission model is
quite often misused: around two thirds of analyzed apps are over-privileged,
i.e., they access more data than is needed for them to function. In this work,
we analyze three different permission models that aim to discourage users from
installing over-privileged apps. In experiments with 210 real users, we
discover that the most successful permission model is our novel ensemble method
that we call Far-reaching Insights. Far-reaching Insights inform the users
about the data-driven insights that apps can make about them (e.g., their
topics of interest, collaboration and activity patterns etc.) Thus, they seek
to bridge the gap between what third parties can actually know about users and
users perception of their privacy leakage. The efficacy of Far-reaching
Insights in bridging this gap is demonstrated by our results, as Far-reaching
Insights prove to be, on average, twice as effective as the current model in
discouraging users from installing over-privileged apps. In an effort for
promoting general privacy awareness, we deploy a publicly available privacy
oriented app store that uses Far-reaching Insights. Based on the knowledge
extracted from data of the store's users (over 115 gigabytes of Google Drive
data from 1440 users with 662 installed apps), we also delineate the ecosystem
for third-party cloud apps from the standpoint of developers and cloud
providers. Finally, we present several general recommendations that can guide
other future works in the area of privacy for the cloud
Multi - owner Secure Data Sharing in Cloud Computing Environment
Data sharing in the cloud is a technique that allows users to conveniently access data over the cloud. The data owner outsources their data in the cloud due to cost reduction and the great conveniences provided by cloud services. Data owner is not able to control over their data, because cloud service provider is a third party provider. The main crisis with data sharing in the cloud is the privacy and security issues. Various techniques are available to support user privacy and secure data sharing. This paper focus on various schemes to deal with secure data sharing such as Data sharing with forward security, secure data sharing for dynamic groups, Attribute based data sharing, encrypted data sharing and Shared Authority Based Privacy-Preserving Authentication Protocol for access control of outsourced data
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