Information Privacy Concern in Context-Aware Personalized Services: Results of a Delphi Study

이연님,권오병 한국경영정보학회 2010 Asia Pacific Journal of Information Systems Vol.20 No.2

Personalized services directly and indirectly acquire personal data, in part, to provide customers with higher-value services that are specifically context-relevant (such as place and time). Information technologies continue to mature and develop, providing greatly improved performance. Sensory networks and intelligent software can now obtain context data, and that is the cornerstone for providing personalized, context-specific services. Yet, the danger of overflowing personal information is increasing because the data retrieved by the sensors usually contains privacy information. Various technical characteristics of context-aware applications have more troubling implications for information privacy. In parallel with increasing use of context for service personalization, information privacy concerns have also increased such as an unrestricted availability of context information. Those privacy concerns are consistently regarded as a critical issue facing context-aware personalized service success. The entire field of information privacy is growing as an important area of research, with many new definitions and terminologies, because of a need for a better understanding of information privacy concepts. Especially, it requires that the factors of information privacy should be revised according to the characteristics of new technologies. However, previous information privacy factors of context-aware applications have at least two shortcomings. First, there has been little overview of the technology characteristics of context-aware computing. Existing studies have only focused on a small subset of the technical characteristics of context-aware computing. Therefore, there has not been a mutually exclusive set of factors that uniquely and completely describe information privacy on context-aware applications. Second, user survey has been widely used to identify factors of information privacy in most studies despite the limitation of users’ knowledge and experiences about context-aware computing technology. To date, since context-aware services have not been widely deployed on a commercial scale yet, only very few people have prior experiences with context-aware person alized services. It is difficult to build users’ knowledge about context-aware technology even by increasing their understanding in various ways: scenarios, pictures, flash animation, etc. Nevertheless, conducting a survey, assuming that the participants have sufficient experience or understanding about the technologies shown in the survey, may not be absolutely valid. Moreover, some surveys are based solely on simplifying and hence unrealistic assumptions (e.g., they only consider location information as a context data). A better understanding of information privacy concern in context-aware personalized services is highly needed. Hence, the purpose of this paper is to identify a generic set of factors for elemental information privacy concern in context-aware personalized services and to develop a rank-order list of information privacy concern factors. We consider overall technology characteristics to establish a mutually exclusive set of factors. A Delphi survey, a rigorous data collection method, was deployed to obtain a reliable opinion from the experts and to produce a rank-order list. It, therefore, lends itself well to obtaining a set of universal factors of information privacy concern and its priority. An international panel of researchers and practitioners who have the expertise in privacy and context-aware system fields were involved in our research. Delphi rounds formatting will faithfully follow the procedure for the Delphi study proposed by Okoli and Pawlowski. This will involve three general rounds: (1) brainstorming for important factors; (2) narrowing down the original list to the most important ones; and (3) ranking the list of important factors. For this round only, experts were treated as individuals, not panels. Adapted from Okoli and Pawlowsk...

Information Privacy Concern in Context-Aware Personalized Services: Results of a Delphi Study

Lee, Yon-Nim,Kwon, Oh-Byung The Korea Society of Management Information System 2010 Asia Pacific Journal of Information Systems Vol.20 No.2

Personalized services directly and indirectly acquire personal data, in part, to provide customers with higher-value services that are specifically context-relevant (such as place and time). Information technologies continue to mature and develop, providing greatly improved performance. Sensory networks and intelligent software can now obtain context data, and that is the cornerstone for providing personalized, context-specific services. Yet, the danger of overflowing personal information is increasing because the data retrieved by the sensors usually contains privacy information. Various technical characteristics of context-aware applications have more troubling implications for information privacy. In parallel with increasing use of context for service personalization, information privacy concerns have also increased such as an unrestricted availability of context information. Those privacy concerns are consistently regarded as a critical issue facing context-aware personalized service success. The entire field of information privacy is growing as an important area of research, with many new definitions and terminologies, because of a need for a better understanding of information privacy concepts. Especially, it requires that the factors of information privacy should be revised according to the characteristics of new technologies. However, previous information privacy factors of context-aware applications have at least two shortcomings. First, there has been little overview of the technology characteristics of context-aware computing. Existing studies have only focused on a small subset of the technical characteristics of context-aware computing. Therefore, there has not been a mutually exclusive set of factors that uniquely and completely describe information privacy on context-aware applications. Second, user survey has been widely used to identify factors of information privacy in most studies despite the limitation of users' knowledge and experiences about context-aware computing technology. To date, since context-aware services have not been widely deployed on a commercial scale yet, only very few people have prior experiences with context-aware personalized services. It is difficult to build users' knowledge about context-aware technology even by increasing their understanding in various ways: scenarios, pictures, flash animation, etc. Nevertheless, conducting a survey, assuming that the participants have sufficient experience or understanding about the technologies shown in the survey, may not be absolutely valid. Moreover, some surveys are based solely on simplifying and hence unrealistic assumptions (e.g., they only consider location information as a context data). A better understanding of information privacy concern in context-aware personalized services is highly needed. Hence, the purpose of this paper is to identify a generic set of factors for elemental information privacy concern in context-aware personalized services and to develop a rank-order list of information privacy concern factors. We consider overall technology characteristics to establish a mutually exclusive set of factors. A Delphi survey, a rigorous data collection method, was deployed to obtain a reliable opinion from the experts and to produce a rank-order list. It, therefore, lends itself well to obtaining a set of universal factors of information privacy concern and its priority. An international panel of researchers and practitioners who have the expertise in privacy and context-aware system fields were involved in our research. Delphi rounds formatting will faithfully follow the procedure for the Delphi study proposed by Okoli and Pawlowski. This will involve three general rounds: (1) brainstorming for important factors; (2) narrowing down the original list to the most important ones; and (3) ranking the list of important factors. For this round only, experts were treated as individuals, not panels. Adapted from Okoli and Pawlowski, we out

Community based Context-aware Information for the Intelligent Personalized Information Service

Jae-gu Song,Seoksoo Kim 보안공학연구지원센터 2008 International Journal of Multimedia and Ubiquitous Vol.3 No.3

With the advent of ubiquitous computing environments, it has become increasingly various context-aware technology implemented. It is researched; however, rather than providing a simple situations, is not possible following the large scope of context-aware data. Nevertheless, it is possible to effectively manage and categorize information by using the characteristic of professional contextual information, which is inherently limited in scope as it is a professional language. This paper presents the system architecture of community based context-aware management service with the properties, operations, and tasks for context-aware services. We apply the proposed a method to community context information by converting various application terminologies used to provide information services. The implemented content recommendation service, a mobile service agent, and advertisement recommendation for suit one’s taste.

A Study on an Object-orientation and Extensibility in Context-aware Systems

최종명,김익수 한국지식정보기술학회 2017 한국지식정보기술학회 논문지 Vol.12 No.2

There has been a lot of research on context-aware computing, but software extensibility in the development of those systems has not gotten much attention in spite of its importance in software engineering. In this paper, we introduce some extension requirements for context-aware systems, and identify four extension types for them: sensors, context inference algorithms, contexts, and context-aware services. For those extension requirements, we propose four extension mechanisms based on object-oriented technology: separation between abstraction and implementation of context, separation of context from sensors, modular and separate model for context-aware functions, and overloading model for context-aware functions. By adopting those mechanisms, developers or maintainers can add new sensors, context inference algorithms, contexts, or context-aware services without modifying the source code after deployment. Those mechanisms are all based on object-orientation. Our approach represents a context as a class, and context services as methods with context parameter. Context inference is a class with a method which understands sensor values and infers the current context from the values. This approach will reduce costs, time, and efforts in context-aware system maintenance which requires new context-aware features after deployment because it will increase the software reusability and extensibility. In this paper, we also specify a case study which shows how to extend a context-aware system with the extension requirements.

Context Aware System based on Bayesian Network driven Context Reasoning and Ontology Context Modeling

Ko, Kwang-Eun,Sim, Kwee-Bo Korean Institute of Intelligent Systems 2008 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGE Vol.8 No.4

Uncertainty of result of context awareness always exists in any context-awareness computing. This falling-off in accuracy of context awareness result is mostly caused by the imperfectness and incompleteness of sensed data, because of this reasons, we must improve the accuracy of context awareness. In this article, we propose a novel approach to model the uncertain context by using ontology and context reasoning method based on Bayesian Network. Our context aware processing is divided into two parts; context modeling and context reasoning. The context modeling is based on ontology for facilitating knowledge reuse and sharing. The ontology facilitates the share and reuse of information over similar domains of not only the logical knowledge but also the uncertain knowledge. Also the ontology can be used to structure learning for Bayesian network. The context reasoning is based on Bayesian Networks for probabilistic inference to solve the uncertain reasoning in context-aware processing problem in a flexible and adaptive situation.

컨텍스트 인지 시스템을 위한 요구사항 도출 및 명세화 방법

최종명 한국정보과학회 2008 정보과학회논문지 : 시스템 및 이론 Vol. No.

Even though context is the most important feature in context-aware systems, the existing requirements engineering cannot support methodology for elicitation and specification of contexts. In this paper, we propose a requirements elicitation method and a requirements specification method for context-aware systems. Our requirements elicitation method is a 6-stepped, incremental, and iterative process. At the beginning steps in the process, we identify the requirements for business logic. Afterwards, we gather the requirements for context logic, model contexts, and identify subsystems. For requirements specification, we suggest a context-aware use case diagram, a context diagram for context modeling, and a context-type-use-case-dependency diagram for the traceability of use cases on the change of context types. We also introduce a case study that we apply our approaches to a real system, and a qualitative evaluation of our approaches. Our study will help stakeholders to efficiently elicit requirements for context-aware systems and to specify them clearly. 컨텍스트 인지 시스템에서 컨텍스트는 매우 중요한 요소이지만, 기존 요구공학은 컨텍스트를 도출하고 명세화하는 방법을 지원하지 못하기 때문에 이를 지원할 수 있는 연구가 필요하다. 본 논문은 컨텍스트 인지 시스템의 요구사항을 효과적으로 도출하기 위한 방법과 명세화 방법을 제안한다. 논문에서 제안하는 요구사항 도출 방법은 6단계로 구성된 점진적이고 반복적인 프로세스로서 비즈니스 로직을 위한 요구사항을 먼저 파악하고, 이를 기반으로 컨텍스트 로직을 위한 요구사항을 파악하고, 컨텍스트 모델링과 서브시스템 식별 등의 작업을 수행한다. 요구사항 명세화 방법으로는 컨텍스트 인지 유스케이스 다이어그램, 컨텍스트의 개념을 표현할 수 있는 컨텍스트 다이어그램, 컨텍스트 타입에 영향을 받는 유스케이스를 표현하는 컨텍스트타입-유스케이스 의존 다이어그램을 제안한다. 논문에서는 또한 제안한 방법을 적용한 시스템에 대한 사례연구를 소개하고, 이를 정성적으로 평가한 내용을 제시한다. 본 연구는 이해관계자가 컨텍스트 인지 시스템의 요구사항을 효과적으로 파악하고, 이를 명확히 기술하며, 이해할 수 있도록 도움을 줄 수 있다.

유비쿼터스 환경에서의 컨텍스트-인식을 위한 자생적 컨텍스트 모델과 서비스의 설계

오동열,오해석,Oh Dong yeol,Oh Hae seok 한국통신학회 2005 韓國通信學會論文誌 Vol.30 No.4B

유비쿼터스 컴퓨팅에서 컨텍스트-인식은 사용자에게 개인화된 최적의 서비스를 제공하기 위하여 서비스 추론을 위한 입력 데이터를 획득하는 중요한 과정이다. 기존 연구는 사용자와 주변 환경 정보를 컨텍스트 인식의 주요대상으로 간주하고, 이를 위한 센싱 기반의 미들웨어나 공간 내의 대상에 식별자를 부여하여 이를 관리하는 서버를 제시하고 있다. 가정이나 사무실, 혹은 자동차와 같이 사용자가 많은 시간을 보내는 동일한 공간에서는 사용자에게 제공되었던 서비스의 일련적인 상황 정보가 개인화된 최적의 서비스를 추론하기 위한 중요한 요소가 될 수 있다. 본 논문은 사용자와 사용자에게 제공된 서비스 간에 일련의 상황 정보를 사용자의 휴대용 디바이스에 저장하고, 이를 컨텍스트-인식의 대상으로 확장하는 자생적 컨텍스트 모델을 제안한다. 제안 모델은 컨텍스트-인식 단계에서 발생하는 중복된 센싱과 불필요한 검색을 최소화하고 사용자의 익명성을 최대한 보장하며 미들웨어의 컨텍스트 관리를 비용을 줄인다. Context-Aware is the most important facts to reason a personalized and optimized service and to provide it to user. In the previous researches, user and surrounding environment were main facts of Context-Aware and middleware or center server has been proposed to support Context-Aware. In the daily space(for example, home, office, Car, etc), interactions between user and service can be a important facts of Context-Aware. In this paper, Context Autogenesis service model is introduced, simplified the Context-Aware process and designed the middleware which performs decentralize management for Context-Aware information of user's portable devices, so that problems occurred during the management and operation of existing Context-Aware system can be minimized and supporting user anonymity

Development of Context Aware System based on Bayesian Network driven Context Reasoning Method and Ontology Context Modeling

Kwang-Eun Ko,Kwee-Bo Sim 제어로봇시스템학회 2008 제어로봇시스템학회 국제학술대회 논문집 Vol.2008 No.10

Uncertainty of result of context awareness always exists in any context-awareness computing. This falling-off in accuracy of context awareness result is mostly caused by the imperfectness and incompleteness of sensed data, because of this reasons, we must improve the accuracy of context awareness. In this article, we propose a novel approach to model the uncertain context by using ontology and context reasoning method based on Bayesian Network. Our context aware processing is divided into two parts: context modeling and context reasoning. The context modeling is based on ontology for facilitating knowledge reuse and sharing. The ontology facilitates the share and reuse of information over similar domains of not only the logical knowledge but also the uncertain knowledge. Also the ontology can be used to structure learning for Bayesian network. The context reasoning is based on Bayesian Network for probabilistic inference to solve the uncertain reasoning in context-aware processing problem in a flexible and adaptive situation.

Context Aware System based on Bayesian Network driven Context Reasoning and Ontology Context Modeling

Kwang-Eun Ko,Kwee-Bo Sim 한국지능시스템학회 2008 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGE Vol.8 No.4

Uncertainty of result of context awareness always exists in any context-awareness computing. This falling-off in accuracy of context awareness result is mostly caused by the imperfectness and incompleteness of sensed data, because of this reasons, we must improve the accuracy of context awareness. In this article, we propose a novel approach to model the uncertain context by using ontology and context reasoning method based on Bayesian Network. Our context aware processing is divided into two parts: context modeling and context reasoning. The context modeling is based on ontology for facilitating knowledge reuse and sharing. The ontology facilitates the share and reuse of information over similar domains of not only the logical knowledge but also the uncertain knowledge. Also the ontology can be used to structure learning for Bayesian network. The context reasoning is based on Bayesian Networks for probabilistic inference to solve the uncertain reasoning in context-aware processing problem in a flexible and adaptive situation.

Context Aware System based on Bayesian Network driven Context Reasoning and Ontology Context Modeling

고광은,심귀보 한국지능시스템학회 2008 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGE Vol.8 No.4

Uncertainty of result of context awareness always exists in any context-awareness computing. This falling-off in accuracy of context awareness result is mostly caused by the imperfectness and incompleteness of sensed data, because of this reasons, we must improve the accuracy of context awareness. In this article, we propose a novel approach to model the uncertain context by using ontology and context reasoning method based on Bayesian Network. Our context aware processing is divided into two parts: context modeling and context reasoning. The context modeling is based on ontology for facilitating knowledge reuse and sharing. The ontology facilitates the share and reuse of information over similar domains of not only the logical knowledge but also the uncertain knowledge. Also the ontology can be used to structure learning for Bayesian network. The context reasoning is based on Bayesian Networks for probabilistic inference to solve the uncertain reasoning in context-aware processing problem in a flexible and adaptive situation.