Privacy-aware searching with oblivious term matching for cloud storage

Pervez, Zeeshan; Awan, Ammar Ahmad; Khattak, Asad Masood; Lee, Sungyoung; Huh, Eui‐Nam

doi:10.1007/s11227-012-0829-z

Cited by 29 publications

(18 citation statements)

References 11 publications

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“…Concretely, AES [32], Private Matching [33] and Anonymization [34] have been chosen to support that. Besides existing standards, the indigenously proposed system of oblivious term matching [35] is considered to work over direct encryption. To generate high entropy a value matching protocol, Reflection [36], is used to further reinforce the privacy level.…”

Section: Mining Minds Implementationmentioning

confidence: 99%

Mining Minds: an innovative framework for personalized health and wellness support

Baños¹,

Amin²,

Khan³

et al. 2015

Proceedings of the 9th International Conference on Pervasive Computing Technologies for Healthcare

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Abstract-The world is witnessing a spectacular shift in the delivery of health and wellness care. The key ingredient of this transformation consists in the use of revolutionary digital technologies to empower people in their self-management as well as to enhance traditional care procedures. While substantial domain-specific contributions have been provided to that end in the recent years, there is a clear lack of platforms that may orchestrate, and intelligently leverage, all the data, information and knowledge generated through these technologies. This work presents Mining Minds, an innovative framework that builds on the core ideas of the digital health and wellness paradigms to enable the provision of personalized healthcare and wellness support. Mining Minds embraces some of the currently most prominent digital technologies, ranging from Big Data and Cloud Computing to Wearables and Internet of Things, and stateof-the-art concepts and methods, such as Context-Awareness, Knowledge Bases or Analytics, among others. This paper aims at thoroughly describing the efficient and rational combination and interoperation of these modern technologies and methods through Mining Minds, while meeting the essential requirements posed by a framework for personalized health and wellness support.

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Section: Mining Minds Implementationmentioning

confidence: 99%

Mining Minds: an innovative framework for personalized health and wellness support

Baños¹,

Amin²,

Khan³

et al. 2015

Proceedings of the 9th International Conference on Pervasive Computing Technologies for Healthcare

Self Cite

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“…Pervez et al assume that both files and inverted indices are stored in encrypted form at the cloud [20]. Authorized users submit encrypted search criteria to a third party, which homomorphically encrypts them before their transmission to the cloud server.…”

Section: Related Workmentioning

confidence: 99%

Lethe: Cluster-Based Indexing for Secure Multi-user Search

Micheli

Margaritis

Anastasiadis

2014

2014 IEEE International Congress on Big Data

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Secure keyword search in shared infrastructures prevents stored documents from leaking sensitive information to unauthorized users. A shared index provides confidentiality if it is exclusively used by users authorized to search all the indexed documents. We introduce the Lethe indexing workflow to improve query and update efficiency in secure keyword search. The Lethe workflow clusters together documents with similar sets of authorized users, and creates shared indices for configurable document subsets accessible by the same users. We examine different datasets based on the empirical statistics of a document sharing system and alternative theoretical distributions. We apply Lethe to generate indexing organizations of different tradeoffs between the search and update cost. With measurements over an open-source distributed search engine, we experimentally confirm the improved search and update performance of particular configurations that we introduce.

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“…In paper by [5] authors propose Oblivious Term Matching (OTM) which unlike existing systems, OTM enables authorized subscribers to define their own search queries comprising of arbitrary number of selection criterion. OTM ensures that cloud service provider obliviously evaluates encrypted search queries without learning any information about the outsourced data.…”

Section: Introductionmentioning

confidence: 99%

Service Models for Cloud Computing: Search as a Service (SaaS)

Dašić¹,

Dašić²,

Crvenković³

2016

IJET

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Abstract-Search as a Service (SaaS) is a cloud service model whose main focus is on enterprise search or site-specific web search. Modern companies require fast and accurate information from their internal databases, internal document stores, or through the content of a website. Having a reliable searching mechanism is essential for both internal company staff and for external customers. In this paper the overview of current state and technological advances of Search as a Service (SaaS) cloud service is given, as well as its security issues on current internet service platforms.

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Privacy-aware searching with oblivious term matching for cloud storage

Cited by 29 publications

References 11 publications

Mining Minds: an innovative framework for personalized health and wellness support

Mining Minds: an innovative framework for personalized health and wellness support

Lethe: Cluster-Based Indexing for Secure Multi-user Search

Service Models for Cloud Computing: Search as a Service (SaaS)

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