Kangsoo Jung

An Introduction to Authorization Conflict Problem in RDF Access Control

In this paper, related with RDF security, we introduce an RDF triple based access control model considering explicit and implicit authorization propagation. Since RDF Schema represents ontology hierarchy of upper and lower classes or properties, our access control model supports the explicit authorization propagation where an authorization specified against an upper concept is propagated to lower concepts by inheritance. In addition, we consider the implicit authorization propagation where an authorization specified against an lower concept is propagated to upper concepts by RDF inference. RDF Semantics, which is recommended by W3C, guides some primary RDF inference rules related with subClassOf and subPropertyOf where lower concepts are interpreted into upper concepts. Based on these two contrary propagations, we introduce an authorization conflict problem in RDF access control.

Context-Aware Role Based Access Control Using User Relationship

We suggest relationship-based access control model that considers the relationship among users in an organization and surrounding user identification as context information. We assume mobile office environment as our domain this paper. In mobile office, employees who use mobile device such as smartphone and tablet PC have relation with other employees for cooperative work to perform organizations task. But existing access control model do not consider relationship among employees as context information in mobile office. Proposed access control model consider relations among surrounding users for access control in mobile office systems.

An RDF triple based access authorization specification considering subsumption relationships

RDF and OWL are the primary base technologies for implementing semantic Web. Recently, many researches related with them, or applying them into the other application domains, have been introduced. However, relatively little work has been done for securing the RDF and OWL data. In this paper, we introduce an RDF triple based access authorization specification related with RDF security. Additionally, to efficiently find the authorization conflict by RDF inference, we introduce a method using graph labeling techniques. The problem of authorization conflict by RDF inference is that although the lower concept is permitted to be accessed, it can be inaccessible due to the disapproval for the upper concept. Because by the RDF inference, the lower concept can be interpreted into the upper concept.

A game theoretic approach for collaborative caching techniques in privacy preserving location-based services

The number of users who use location-based services (LBS) is increasing rapidly along with the proliferation of mobile devices such as the smartphone. However, LBS users have concerned about their privacy because the collected individual location information can pose a privacy violation. Therefore, it is no wonder that a lot of research is being conducted on topic such as location k-anonymity and pseudonym to prevent privacy threats. However, existing research has several limitations when applied to real world applications. In this paper, we propose a novel architecture to preserve the location privacy in LBS using the Virtual Individual Server (VIS) to overcome drawbacks in existing techniques. We also introduce the collaborative caching technique which shares extra query results among users to mitigate privacy/performance tradeoffs. Game theory is used to overcome the free rider problem that can occur during the sharing process. Simulation results show that the proposed technique achieves sufficient privacy protection and reduces system performance degradation.

A Privacy Preserving Technique to Prevent Sensitive Behavior Exposure in Semantic Location-based Service

Abstract The increasing number of mobile device users indicates the expansion of personalized location-based services (LBS). Despite their proliferation, the risk of violating users’ privacy by exposing users location information remains. For this reason, many studies have researched to prevent privacy violation in LBS. However, previous researches only focused on protecting users’ location information without considering semantic location privacy violation through contextual information. In this paper, we explain the process of inferring a users behavior using semantic information which includes spatial and temporal information. We also suggest a privacy preserving technique to prevent exposure of sensitive behavior in semantic LBS. We implement an android application to validate the proposed technique. In accordance with the experimental results, the proposed b-diversity technique is validated to prevent exposure of sensitive behavior and also minimizing data utilization degradation.

A noise parameter configuration technique to mitigate detour inference attack on differential privacy

Nowadays, data has become more important as the core resource for the information society. However, with the development of data analysis techniques, the privacy violation such as leakage of sensitive data and personal identification exposure are also increasing. Differential privacy is the technique to satisfy the requirement that any additional information should not be disclosed except information from the database itself. It is well known for protecting the privacy from arbitrary attack. However, recent research argues that there is a several ways to infer sensitive information from data although the differential privacy is applied. One of this inference method is to use the correlation between the data. In this paper, we investigate the new privacy threats using attribute correlation which are not covered by traditional studies and propose a privacy preserving technique that configures the differential privacys noise parameter to solve this new threat. In the experiment, we show the weaknesses of traditional differential privacy method and validate that the proposed noise parameter configuration method provide a sufficient privacy protection and maintain an accuracy of data utility.

A Method of Pre-detecting Privacy Leak in Social Network Service Using Collaborative Filtering

Nowadays, the number of SNS user is increasing very quickly and importance of information in SNS is getting higher. While other traditional web services treat only photos and articles of users, SNS covers more sort of information. SNS privacy issue receives more attention because SNS users upload and update information about them in real time spontaneously. Existing researches mainly concentrate about extracting profiles from each user or connections between users. In this paper, we present a possible privacy attacking method for an attacker may use, and show that the method can be adopted in real social network service form as the third party application. Especially, we show how the application works to analyze threats to which SNS users can be exposed, and to show in what way users should react when using SNS.

Notice of Retraction Group prime number labeling scheme for light-weight access control

The existing access control environment relies on the server to solve security problems. The current environment has spawned the need for light-weight access control by clients, which have a resource limited environment. In this paper, an adaptable light-weight access control scheme is proposed for an evolutionary computing environment. Existing studies using role-based prime number labeling are limited by the scalability of the prime number. The problem of scalability of the prime number was addressed with the use of the strong point of role-based prime number labeling and implementation of persistent XML labeling and efficient query processing. The proposal has the advantage of having an adaptable access control scheme for an existing XML labeling method. We showed the efficiency of the proposed approach through experiments.