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Varunya Attasena

dblp:138/1342 · DBLP profile ↗
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2ranked-venue papers
2as first author
0since 2021 · last 2017
0000-0002-3652-9032ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 2 · 2 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Network and information security
1 paper
Cryptographic protocols and secure computation · 100%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Cloud and datacenter computing · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Cryptographic protocols and secure computation
secret sharing
0.312017
Secret sharing for cloud data security: a survey · VLDB J. 2017
Cloud and datacenter computing › cloud security
cloud data security
0.112017
Secret sharing for cloud data security: a survey · VLDB J. 2017
YearPublicationVenuePosition
2017 Secret sharing for cloud data security: a survey
Varunya Attasena, Jérôme Darmont, Nouria Harbi
VLDB J.1
2014 fVSS: A New Secure and Cost-Efficient Scheme for Cloud Data Warehouses
abstract
Cloud business intelligence is an increasingly popular choice to deliver decision support capabilities via elastic, pay-per-use resources. However, data security issues are one of the top concerns when dealing with sensitive data. In this paper, we propose a novel approach for securing cloud data warehouses by flexible verifiable secret sharing, fVSS. Secret sharing encrypts and distributes data over several cloud service providers, thus enforcing data privacy and availability. fVSS addresses four shortcomings in existing secret sharing-based approaches. First, it allows refreshing the data warehouse when some service providers fail. Second, it allows on-line analysis processing. Third, it enforces data integrity with the help of both inner and outer signatures. Fourth, it helps users control the cost of cloud warehousing by balancing the load among service providers with respect to their pricing policies. To illustrate fVSS' efficiency, we thoroughly compare it with existing secret sharing-based approaches with respect to security features, querying power and data storage and computing costs.
Varunya Attasena, Nouria Harbi, Jérôme Darmont
DOLAP1