Dynamic Disclosure Monitor (D 2 Mon): An Improved Query Processing Solution

Toland, Tyrone S.; Farkas, Csilla; Eastman, Caroline M.

doi:10.1007/11552338_9

Cited by 10 publications

(6 citation statements)

References 20 publications

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“…Further, since data update can affect data inference, [FTE01] proposed a mechanism that propagates update to the user history files to ensure no query is rejected based on the outdated information. To reduce the time in examining the entire history log in computing inference, [TFE05] proposed to use a prior knowledge of data dependency to reduce the search space of a relation and thus reduce the processing time for inference.…”

Section: Related Workmentioning

confidence: 99%

Protection of Database Security via Collaborative Inference Detection

Chen

Chu

2008

IEEE Trans. Knowl. Data Eng.

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Malicious users can exploit the correlation among data to infer sensitive information from a series of seemingly innocuous data accesses. Thus, we develop an inference violation detection system to protect sensitive data content. Based on data dependency, database schema and semantic knowledge, we constructed a semantic inference model (SIM) that represents the possible inference channels from any attribute to the pre-assigned sensitive attributes. The SIM is then instantiated to a semantic inference graph (SIG) for query-time inference violation detection. For a single user case, when a user poses a query, the detection system will examine his/her past query log and calculate the probability of inferring sensitive information. The query request will be denied if the inference probability exceeds the pre-specified threshold. For multi-user cases, the users may share their query answers to increase the inference probability. Therefore, we develop a model to evaluate collaborative inference based on the query sequences of collaborators and their task-sensitive collaboration levels. Experimental studies reveal that information authoritativeness, communication fidelity and honesty in collaboration are three key factors that affect the level of achievable collaboration. An example is given to illustrate the use of the proposed technique to prevent multiple collaborative users from deriving sensitive information via inference.

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Section: Related Workmentioning

confidence: 99%

Protection of Database Security via Collaborative Inference Detection

Chen

Chu

2008

IEEE Trans. Knowl. Data Eng.

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“…The DiIE is the component that responsible for generating all information that can be disclosed based on a user's previous queries results (stored in history file), the current query result and database constraints. Another approach is D2Mon [12,14] which extends the capabilities of DMon to work with dynamic databases. Some work was on providing access control to semantically related XML documents and provide a general control mechanism for access made to a collection of related documents rather than individual document.…”

Section: Related Workmentioning

confidence: 99%

Disclosure prevention in XML

Mohy

El-Sharkawi

2008

2008 First International Conference on the Applications of Digital Information and Web Technologies (ICADIWT)

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Information security is considered the most serious requirement which must be carefully considered. Traditional security mechanism protects data at physical level such as encryption and access control, but today's organizations need to protect data on both levels physical and logical level. Since the organization's data may be published and shared by many users. Disclosure is a result of weakness of these security mechanisms. In this paper we discuss the problem of protecting XML data at logical level specifically solve the disclosure problem. The objective is to prevent an unauthorized user to infer sensitive information through the data they authorized to access (result of previous queries), integrity constraints, and using inferences. In most existing access control approaches the XML elements specified by access policies are either accessible or inaccessible according to their sensitivity. However, in some cases, the original XML elements are sensitive and inaccessible, but after being processed in some appropriate ways, the results become insensitive and thus accessible [6]. We propose a security mechanism called Disclosure Prevention Algorithm (DPA) that enhances both the security (by preventing disclosure) and availability (by considering suspected users only) of data represented in XML format.

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“…For example, the consideration of dynamic disclosure concerns-on the basis of a picture of use being built up via history databases or audits has been addressed in a number of articles, including [2], [27], [28], and [40]. Typically, though, such effort requires significant additional computational steps [29].…”

Section: Tracker Attack Preventionmentioning

confidence: 99%

On tracker attacks in health grids

Simpson¹,

Power²,

Slaymaker³

2006

Proceedings of the 2006 ACM Symposium on Applied Computing

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The utilisation of grid computing to support healthcare research is becoming increasingly widespread, as is the use of IT to support healthcare delivery. Furthermore, it seems that the two areas are on an inevitable convergence path as clinical communities in several countries start to investigate how real data stored in electronic patient records can be utilised to facilitate research. The use of IT within healthcare gives rise to unique social and ethical challenges; the area of grid computing has given rise to significant novel security challenges; and the anticipated convergence of these two fields will inevitably give a new lease of life to established challenges. In this paper we consider the phenomenon of tracker attacks in this emerging context, and outline a potential approach to addressing the problem.

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Dynamic Disclosure Monitor (D 2 Mon): An Improved Query Processing Solution

Cited by 10 publications

References 20 publications

Protection of Database Security via Collaborative Inference Detection

Protection of Database Security via Collaborative Inference Detection

Disclosure prevention in XML

On tracker attacks in health grids

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