An Information-Flow Control Model for Online Social Networks Based on User-Attribute Credibility and Connection-Strength Factors

Gudes, Ehud; Voloch, Nadav

doi:10.1007/978-3-319-94147-9_5

Cited by 12 publications

(7 citation statements)

References 13 publications

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“…This paper presents a new privacy model for access control in an OSN, in which the decisions of permission granting combines both pre-defined roles and trust-based factors derived from user-attributes, such as total number of friends, age of user account, and resemblance attributes between the two users. Similar attributes have appeared in a previous work ( [2]), which deals with information-flow control, and creates a model for adversary detection. However, in this paper we present specific parametric values for these attributes, which are experimentally based.…”

Section: Introductionmentioning

confidence: 86%

A Role and Trust Access Control Model for Preserving Privacy and Image Anonymization in Social Networks

Voloch

Nissim

Elmakies

et al. 2019

IFIP Advances in Information and Communication Technology

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Over the last decade Online Social Networks (OSN) privacy has been thoroughly studied in many aspects. Some of these privacy related aspects are trust and credibility involving the OSN user-data conveyed by different relationships in the network. One of OSN major problems is that users expose their information in a manner thought to be relatively private, or even partially public, to unknown and possibly unwanted entities, such as adversaries, social bots, fake users, spammers or data-harvesters. Preventing this information leakage is the target of many OSN privacy models, such as Access Control, Relationship based models, Trust based models and many others. In this paper we suggest a new Role and Trust based Access Control model, denoted here as RTBAC, in which roles, that manifest different permissions, are assigned to the users connected to the Ego-node (the user sharing the information), and in addition, every user is evaluated trust wise by several criteria, such as total number of friends, age of user account, and friendship duration. An interesting extension of the model of image anonymization is also given, where a user that has a certain role with a proper permission can access a partial instance of the data, if a sufficient trust level is not achieved. These role and trust assessments provide more precise and viable information sharing decisions and enable better privacy control in the social network.

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Section: Introductionmentioning

confidence: 86%

A Role and Trust Access Control Model for Preserving Privacy and Image Anonymization in Social Networks

Voloch

Nissim

Elmakies

et al. 2019

IFIP Advances in Information and Communication Technology

Self Cite

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“…An Ego node along with its adjacent nodes are denoted Ego network. The model we have presented in previous work ( [5], [6], [7], [5]) is composed of three main phases addressing three of its major aspects: trust, role-based access control and information flow. In the first phase, the Trust phase, we assign trust values on the edges connecting direct friends to the Ego node in their different roles, e.g., Family, Colleagues etc.…”

Section: Context Independent Trust-based Modelmentioning

confidence: 99%

“…Moreover, users may wish to share a piece of sensitive information in one subject with people they trust in the context of this subject but avoid sharing with the same people sensitive information in other subjects. The GDPR [7] was initiated by the EU for data protection and privacy, and affects most of the commercial companies, government institutions, and other sectors that process personal data of their customers or audiences. This regulation applies by virtue of public international law to organizations located within all EU member states that process personal data.…”

Section: Introductionmentioning

confidence: 99%

A Privacy Providing Context-based Trust Model for OSN and its Relation to GDPR

Voloch,

Gal-Oz,

Gudes

2023

Preprint

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Users’ privacy has become a key objective inthe operation of Online Social Networks (OSN), whichinvolves major concerns regarding personal data exposure and processing. It became a demand with the raiseof legislative initiatives such as the General Data Protection Regulation (GDPR) in the EU that affects mostof the commercial companies, government institutions,and other sectors that process personal data. While thesubject of ensuring privacy in OSN is widely addressedin current research, we focus on challenges related toseveral principles concerning the right to the protectionof personal data, as defined by the GDPR. In previousresearch we have devised a comprehensive Trust-basedModel for Social Networks, that uses Trust, Access Control and Flow Control, to enhance users’ control overtheir data. Users of social networks share data of various contexts, and for a specific user, some contexts aremore sensitive than others. In this paper we use contextdependent trust to build a refined model for controllingpersonal content that aligns with the users’ preferences.We propose a context-based trust model that involvesuser actions, OSN features and OSN activities. It provides a means for revealing the sources of sensitive datadissemination and prevents them from happening. Wevalidate this model by analyzing trust using sentimentanalysis of posts in a real network. The context-basedmodel we present in this paper, addresses the need toestablish an infrastructure for the enforcement of dataprotection rules, concerning users’ privacy in OSN, suchas data minimization and the right-to-be-forgotten. Wealso propose a solution for Digital Rights Management(DRM) to control and manage access to copyrightedmaterial.

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“…similarity indexes, user interactions such as comments, private messages and so on (i.e. see works by Misra et al (2016) or Gudes and Voloch (2018)). For online SSN data, there may be potential to adapt trust-based methods to geoprivacy protection in spatial data sharing.…”

Section: Spatial Cloakingmentioning

confidence: 99%

Decentralized geoprivacy: leveraging social trust on the distributed web

Hojati

Farmer²,

Feick

et al. 2021

International Journal of Geographical Information Science

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Despite several high-profile data breaches and business models that commercialize user data, participation in social media networks continues to require users to trust corporations to safeguard their personal data. Since these data increasingly contain geographic references that allude to individuals' locations and movements, the need for new approaches to geoprivacy and data sovereignty has grown. We develop a geoprivacy framework that couples two emerging technologies -decentralized data storage and discrete global grid systems -to facilitate fine-grained user control over the ownership of, access to and map-based representation of their data. The framework is illustrated with a dynamic k-anonymity model that links the geographic precision of shared data to social trust within in a social network. In this framework, users' spatio-temporal data are shared through a decentralized system and are represented on a discrete global grid data model at spatial resolutions that correspond to varying degrees of trust between individuals who are exchanging information. Our framework has several advantages over centralized geoprivacy approaches, namely trust in a third-party entity is not required and geoprivacy is dynamic and context-dependent with users maintaining autonomy. As the distributed web begins to emerge, so too can the next generation of geographic information sharing tools.

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An Information-Flow Control Model for Online Social Networks Based on User-Attribute Credibility and Connection-Strength Factors

Cited by 12 publications

References 13 publications

A Role and Trust Access Control Model for Preserving Privacy and Image Anonymization in Social Networks

A Role and Trust Access Control Model for Preserving Privacy and Image Anonymization in Social Networks

A Privacy Providing Context-based Trust Model for OSN and its Relation to GDPR

Decentralized geoprivacy: leveraging social trust on the distributed web

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