Search in social networks with access control

Bjørklund, Truls A.; Götz, Michaela; Gehrke, Johannes

doi:10.1145/1868366.1868370

Cited by 11 publications

(7 citation statements)

References 15 publications

(16 reference statements)

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“…Access control is enforced through intersection of the search result with the identifiers (author list) of documents authored by a particular set of users [4]. Alternative cost models are examined to optimally include specific friends in the author list of each user, and the HeapUnion operator is introduced to efficiently process multiple lists of document identifiers [5].…”

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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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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“…Existing indexing techniques for OSN content searching can be classified into two types: federated searching [4] and centralized index with access filtering [5].…”

Section: Related Workmentioning

confidence: 99%

“…A federated search engine maintains a local index for the content generated by each user [4], where an inverted index can be easily implemented atop popular OSN Key-Value stores following the widely used column family data model [6]. When a user issues a query, the search engine broadcasts the query messages to all his/her neighbors and performs a search in their local indices.…”

Section: Related Workmentioning

confidence: 99%

CBL

Chen

Zhang

Jin

2014

Proceedings of the 23rd International Symposium on High-Performance Parallel and Distributed Computing

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Retrieving relevant data for users in online social network (OSN) systems is a challenging problem. Cassandra, a storage system used by popular OSN systems, such as Facebook and Twitter, relies on a DHT-based scheme to randomly partition the personal data of users among servers across multiple data centers. Although DHT is highly scalable for hosting a large number of users (personal data), it leads to costly inter-server communications across data centers due to the complex interconnection and interaction among OSN users. In this paper, we explore how to retrieve the OSN content in a cost-effective way by retaining the simple and robust nature of OSNs. Our approach exploits a simple, yet powerful principle called Community-Based Locality (CBL), which posits that if a user has an one-hop neighbor within a particular community, it is very likely that the user has other one-hop neighbors inside the same community. We demonstrate the existence of community-based locality in diverse traces of popular OSN systems such as Facebook, Orkut, Flickr, Youtube, and Livejournal.Based on the observation, we design a CBL-based algorithm to build the content index in OSN systems. By partitioning and indexing the relevant data of users within a community on the same server in the data center, the CBL-based index avoids a significant amount of inter-server communications during searching, making retrieving relevant data for a user in large-scale OSNs efficient. In addition, by using CBL-based scheme we can provide much shorter query latency and balanced loads. We conduct comprehensive tracedriven simulations to evaluate the performance of the proposed scheme. Results show that our scheme significantly reduces the network traffic by 73% compared with existing schemes.

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“…In recent years, several models have been proposed, and some have gained serious attention. Among them are the rule based privilege computation model [23], privacy aware keyword search [37], and access control based on ontology [38], learning [39], evolution [40] and roles [41].…”

Section: Access Control As a Privacy Theorymentioning

confidence: 99%

Empowering Evolving Social Network Users with Privacy Rights

Jamil¹

2013

Preprint

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Considerable concerns exist over privacy on social networks, and huge debates persist about how to extend the artifacts users need to effectively protect their rights to privacy. While many interesting ideas have been proposed, no single approach appears to be comprehensive enough to be the front runner. In this paper, we propose a comprehensive and novel reference conceptual model for privacy in constantly evolving social networks and establish its novelty by briefly contrasting it with contemporary research. We also present the contours of a possible query language that we can develop with desirable features in light of the reference model, and refer to a new query language, PiQL, developed on the basis of this model that aims to support user driven privacy policy authoring and enforcement. The strength of our model is that such extensions are now possible by developing appropriate linguistic constructs as part of query languages such as SQL, as demonstrated in PiQL.

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Search in social networks with access control

Cited by 11 publications

References 15 publications

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

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

CBL

Empowering Evolving Social Network Users with Privacy Rights

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