1,702 research outputs found
Prochlo: Strong Privacy for Analytics in the Crowd
The large-scale monitoring of computer users' software activities has become
commonplace, e.g., for application telemetry, error reporting, or demographic
profiling. This paper describes a principled systems architecture---Encode,
Shuffle, Analyze (ESA)---for performing such monitoring with high utility while
also protecting user privacy. The ESA design, and its Prochlo implementation,
are informed by our practical experiences with an existing, large deployment of
privacy-preserving software monitoring.
(cont.; see the paper
A Cloud-based RFID Authentication Protocol with Insecure Communication Channels
© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Radio Frequency Identification (RFID) has becomea widespread technology to automatically identify objects and withthe development of cloud computing, cloud-based RFID systemsattract more research these days. Several cloud-based RFIDauthentication protocols have been proposed to address privacyand security properties in the environment where the cloudprovider is untrusted therefore the tag’s data are encrypted andanonymously stored in the cloud database. However, most of thecloud-based RFID authentication protocols assume securecommunication channels between the reader and the cloud server.To protect data transmission between the reader and the cloudserver without any help from a third party, this paper proposes acloud-based RFID authentication protocol with insecurecommunication channels (cloud-RAPIC) between the reader and the cloud server. The cloud-RAPIC protocol preserves tag privacyeven when the tag does not update its identification. The cloudRAPIC protocol has been analyzed using the UPriv model andAVISPA verification tool which have proved that the protocolpreserves tag privacy and protects data secrecy
An Effective Private Data storage and Retrieval System using Secret sharing scheme based on Secure Multi-party Computation
Privacy of the outsourced data is one of the major challenge.Insecurity of
the network environment and untrustworthiness of the service providers are
obstacles of making the database as a service.Collection and storage of
personally identifiable information is a major privacy concern.On-line public
databases and resources pose a significant risk to user privacy, since a
malicious database owner may monitor user queries and infer useful information
about the customer.The challenge in data privacy is to share data with
third-party and at the same time securing the valuable information from
unauthorized access and use by third party.A Private Information Retrieval(PIR)
scheme allows a user to query database while hiding the identity of the data
retrieved.The naive solution for confidentiality is to encrypt data before
outsourcing.Query execution,key management and statistical inference are major
challenges in this case.The proposed system suggests a mechanism for secure
storage and retrieval of private data using the secret sharing technique.The
idea is to develop a mechanism to store private information with a highly
available storage provider which could be accessed from anywhere using queries
while hiding the actual data values from the storage provider.The private
information retrieval system is implemented using Secure Multi-party
Computation(SMC) technique which is based on secret sharing. Multi-party
Computation enable parties to compute some joint function over their private
inputs.The query results are obtained by performing a secure computation on the
shares owned by the different servers.Comment: Data Science & Engineering (ICDSE), 2014 International Conference,
CUSA
Systematizing Decentralization and Privacy: Lessons from 15 Years of Research and Deployments
Decentralized systems are a subset of distributed systems where multiple
authorities control different components and no authority is fully trusted by
all. This implies that any component in a decentralized system is potentially
adversarial. We revise fifteen years of research on decentralization and
privacy, and provide an overview of key systems, as well as key insights for
designers of future systems. We show that decentralized designs can enhance
privacy, integrity, and availability but also require careful trade-offs in
terms of system complexity, properties provided, and degree of
decentralization. These trade-offs need to be understood and navigated by
designers. We argue that a combination of insights from cryptography,
distributed systems, and mechanism design, aligned with the development of
adequate incentives, are necessary to build scalable and successful
privacy-preserving decentralized systems
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