In this abstract, we propose a shared authority based privacy preserving authentication protocol (SAPA) for the cloud data storage, which realizes authentication and authorization without compromising a user’s private information. The main contributions are as follows. 1) Identify a new privacy challenge in cloud storage, and address a subtle privacy issue during a user challenging […]
STOCHASTIC POWER REDUCTION SCHEME BASED POWER COST REDUCTION IN DISTRIBUTED DATA CENTERS
Geographically distributed data centers are contains a huge number of servers. Our goal then is to minimize power cost by deciding, how to distribute the workload from the front-end servers to the back-end clusters, how many servers to activate at each back-end cluster at any given time; and how to set the service rates (or […]
BROKER-LESS PUBLISH/SUBSCRIBE SYSTEMS WITH IDENTITY-BASED ENCRYPTION
In publish/subscribe (pub/sub) communication, Publishers inject information into the pub/sub system, and subscribers specify the events of interest by means of subscriptions. Published events are routed to their relevant subscribers, without the publishers knowing the relevant set of subscribers, or vice versa. This abstract presents a novel approach to provide confidentiality and authentication in a […]
STOCHASTIC POWER REDUCTION SCHEME BASED POWER COST REDUCTION IN DISTRIBUTED DATA CENTERS
Geographically distributed data centers are contains a huge number of servers. Our goal then is to minimize power cost by deciding, how to distribute the workload from the front-end servers to the back-end clusters, how many servers to activate at each back-end cluster at any given time; and how to set the service rates (or […]
REDUCING POWER COST USING SAVE ALGORITHM IN DISTRIBUTED DATA CENTERS
In this abstract propose a two-time-scale control algorithm aimed at reducing power cost and facilitating a power cost versus delay trade-off in geographically distributed data centers. By extending the traditional Lyapunov optimization approach, which operates on a single time scale, to two different time scales, we derive analytical bounds on the time average power cost […]
CLOUD BACKUP SERVICES OF PERSONAL STORAGE USING APPLICATION-AWARE LOCAL-GLOBAL SOURCE DEDUPLICATION
Data deduplication, an effective data compression approach that exploits data redundancy, partitions large data objects into smaller parts, called chunks, represents these chunks by their fingerprints (i.e., generally a crypto-graphic hash of the chunk data), replaces the duplicate chunks with their fingerprints after chunk fingerprint index lookup, and only transfers or stores the unique chunks […]
ALG-DEDUPE FOR CLOUD BACKUP SERVICES OF PERSONAL STORAGE
In this abstract, we propose ALG-Dedupe, an Application-aware Local-Global source deduplication scheme that not only exploits application awareness, but also combines local and global duplication detection, to achieve high deduplication efficiency by reducing the deduplication latency to as low as the application-aware loc al de-duplication while saving as much cloud storage cost as the application-aware […]
MRSE SCHEME OVER ENCRYPTED CLOUD DATA FOR PRIVACY PRESERVING
To protect data privacy and combat unsolicited accesses in the cloud and beyond, sensitive data, e.g., emails, personal health records, photo albums, tax documents, financial transactions, etc., may have to be encrypted by data owners before outsourcing to the commercial public cloud; this, however, obsoletes the traditional data utilization service based on plaintext keyword search. […]
SPARSE REPRESENTATION BASED FINGERPRINT COMPRESSION
Large volumes of fingerprint are collected and stored every day in a wide range of applications, including forensics and access control. Due to the large number and size of fingerprint images, data compression has to be applied to reduce the storage and communication bandwidth requirements of those images. Obtaining an over complete dictionary from a […]
AN EFFICIENT MULTI-KEYWORD RANKED SEARCH SCHEME OVER ENCRYPTED CLOUD DATA
In this abstract, for the first time, we define and solve the problem of multi-keyword ranked search over encrypted cloud data (MRSE) while preserving strict system-wise privacy in the cloud computing paradigm. Among various multi-keyword semantics, we choose the efficient similarity measure of “coordinate matching”, i.e., as many matches as possible, to capture the relevance […]
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