New Paradigm of Inference Control with Trusted Computing

Yang, Yanjiang; Li, Yingjiu; Deng, Robert H.

doi:10.1007/978-3-540-73538-0_18

Cited by 8 publications

(4 citation statements)

References 45 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As noted by [18], this has been a major bottleneck preventing dynamic auditing algorithms from being deployed in practice, since there may be hundreds or thousands of users querying the database simultaneously. The most computationally expensive part of our algorithm by far is the model finding, and that can be farmed out to the client (user) side.…”

Section: Discussionmentioning

confidence: 98%

A model-theoretic approach to data anonymity and inference control

Arkoudas¹,

Vashist²

2012

Proceedings of the Second ACM Conference on Data and Application Security and Privacy

View full text Add to dashboard Cite

In secure data management the inference problem occurs when data classified at a high security level becomes inferrible from data classified at lower levels. We present a model-theoretic approach to this problem that captures the epistemic state of the database user as a set of possible worlds or models. Privacy is enforced by requiring the existence of k > 1 models assigning distinct values to sensitive attributes, and implemented via model counting. We provide an algorithm mechanizing this process and show that it is sound and complete for a large class of queries.

show abstract

Section: Discussionmentioning

confidence: 98%

A model-theoretic approach to data anonymity and inference control

Arkoudas¹,

Vashist²

2012

Proceedings of the Second ACM Conference on Data and Application Security and Privacy

View full text Add to dashboard Cite

show abstract

“…Some works have been elaborated to overcome these problems especially for run time approaches. Example in Yang et al (2007) a new paradigm of inference control with trusted computing was developed to push the inference control from server side to client side in order to mitigate the bottleneck on the database server. Furthermore, in Staddon (2003) the authors have developed a run time inference control techniques while retaining fast query processing.…”

Section: Inference Attacks and Prevention Methodsmentioning

confidence: 99%

Secure data outsourcing in presence of the inference problem: issues and directions

Jebali

Sassi

Jemai

2020

Journal of Information and Telecommunication

View full text Add to dashboard Cite

With the emergence of cloud computing paradigms, secure data outsourcing has become one of the crucial challenges which strongly imposes itself. Data owners place their data among cloud service providers in order to increase flexibility, optimize storage, enhance data manipulation and decrease processing time. Nevertheless, from a security point of view, access control is a major challenge in this situation seeing that the security policy of the data owner must be preserved when data is moved to the cloud. Nonetheless, the lack of a comprehensive and systematic review motivated us to construct this reviewing paper on this research problem. Here, we discuss current and emerging research on privacy and confidentiality concerns in data outsourcing and pinpoint potential issues that are still unresolved.

show abstract

“…Reference [13] proposes to respond to the needs of database audits with an inference control whose architecture requires the database server to consider tradition-al access control and the user platforms to apply inference control. Each user man-ages his inference control in a decentralized way.…”

Section: Inference Control In Traditional Databasesmentioning

confidence: 99%

A Mechanism for Detecting Partial Inferences in Data Warehouses

Edwige¹,

Joel²,

Oumtanaga³

2021

IJAR

View full text Add to dashboard Cite

Data warehouses are widely used in the fields of Big Data and Business Intelligence for statistics on business activity. Their use through multidimensional queries allows to have aggregated results of the data. The confidential nature of certain data leads malicious people to use means of deduction of this information. Among these means are data inference methods. To solve these security problems, the researchers have proposed several solutions based on the architecture of the warehouses, the design phase, the cuboids of a data cube and the materialized views of multidimensional queries. In this work, we propose a mechanism for detecting inference in data warehouses. The objective of this approach is to highlight partial inferences during the execution of a multidimensional OLAP (Online Analytical Processing) SUM-type multidimensional query. The goal is to prevent a data warehouse user from inferring sensitive information for which he or she has no access rights according to the access control policy in force. Our study improves the model proposed by a previous study carried out by Triki, which proposes an approach based on average deviations. The aim is to propose an optimal threshold to better detect inferences. The results we obtain are better compared to the previous study.

show abstract

New Paradigm of Inference Control with Trusted Computing

Cited by 8 publications

References 45 publications

A model-theoretic approach to data anonymity and inference control

A model-theoretic approach to data anonymity and inference control

Secure data outsourcing in presence of the inference problem: issues and directions

A Mechanism for Detecting Partial Inferences in Data Warehouses

Contact Info

Product

Resources

About