• 한국정보통신설비학회:학술대회논문집
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• 2008.08a
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• pp.563-565
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• 2008

In this paper, we construct an efficient fuzzy identity-based encryption scheme in the random oracle model. The fuzzy identity-based encryption is an extension of identity-based encryption schemes where a user's public key is represented as his identity. Our construction requires constant number of bilinear map operations for decryption and the size of private key is small compared with the previous fuzzy identity-based encryption of Sahai-Waters. We also presents that our fuzzy identity-based encryption can be converted to attribute-based encryption schemes.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1998.06b
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• pp.105-110
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• 1998

This paper proposes a method to manage individual information on large scale distributed geographic information systems. On such system, ordinary users usually cannot alter the contents of the server. The method proposed in this paper makes possible to alter the contents or add individual data onto such kinds of non-write-permitted data onto set. We call the method as GDSF, ‘geographic differential script file’. In this method, a client user makes a GDSF which contains the private information to be added onto the served data. Then, the client keeps the file on a local disk. After this, when the user uses the data, he applies the differential data sequence onto the down loaded data to restore the information. The GDSF is a collection of picture commands which tell pictures insertions, deletions, and modification operations. The GDSF also can contain the modification. The GDSF also can contain the modification of the attribute information of geographic entities. The method also applicable to modify data on a ROM device, for example CD-ROM or DVD-ROM. This paper describes the method and experimental results.

• Journal of Digital Convergence
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• v.15 no.3
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• pp.187-193
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• 2017

Objects Internet-based healthcare services provide healthcare and healthcare services, including measurement of user's vital signs, diagnosis and prevention of diseases, through a variety of object internet devices. However, there is a problem that new security vulnerability can occur when inter-working with the security weakness of each element technology because the internet service based on the object Internet provides a service by integrating various element technologies. In this paper, we propose a user privacy protection model that can securely process user's healthcare information from a third party when delivering healthcare information of users using wearable equipment based on IoT in a mobile environment to a server. The proposed model provides attribute values for each healthcare sensor information so that the user can safely handle, store, and store the healthcare information, thereby managing the privacy of the user in a hierarchical manner. As a result of the performance evaluation, the throughput of IoT device is improved by 10.5% on average and the server overhead is 9.9% lower than that of the existing model.

• Management & Information Systems Review
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• v.30 no.2
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• pp.1-25
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• 2011

In this study, a survey of online coupon user in their 20's and 30's was undertaken to explore how e-coupon attribute, perceived risk affect the intention to continuously use online coupons through mediation of online coupon user satisfaction. Four variables were used as E-coupon attribute variables(economy, amusement, reliability, usefulness) with coupon type and gender being used as moderating variables. The analysis results of relationship between e-coupon attributes, perceived risk and online coupon user satisfaction indicated that amusement, usefulness significantly affected online coupon user satisfaction, and this, in turn, significantly affected the intention to continuously use online coupons. In addition, the test of difference between groups in coupon type and gender, two moderating variables used in this study, found that with respect to coupon type, a moderating effect existed in reliability, usefulness whereas for gender, a moderating effect existed in only reliability. It is considered that this study will provide a credible evidence basis for Internet shopping malls in establishing a coupon promotion strategy including a specific promotional mix best suited to their needs and resources, while implicating that offering highly reliable online coupons will contribute to enhancing satisfaction level among customers using online coupons.

• Journal of the Korea Convergence Society
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• v.10 no.6
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• pp.139-146
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• 2019

In this study, we examined how consumers who experience HMD virtual reality advertising differ in their ad attitudes and memory effects according to Presence (cognitive presence, emotional presence, media presence) and engagement level. Particularly, in the case of memory effect, the information that the user memorizes through the advertising is divided into "Attribute-Related Memory (ARM)" and "Global-Related Memory (GRM)" Respectively. First, the attitudes toward HMD based virtual reality ads are positive regardless of the type of presence. Second, in the virtual reality advertising, if the level of engagement is low, ARM that memorizes the information of the product attribute is increased, whereas if the level of engagement is high, the GRM which is the memory of the attitude-based evaluation information about the product is increased appear. Third, if cognitive presence and media presence are low, then ARM is more memorable than GRM.

• Journal of Convergence Society for SMB
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• v.2 no.2
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• pp.35-41
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• 2012

The rapid development of cloud computing and mobile internet service changes to an mobile cloud service environment that can serve and pay computing source that users want anywhere and anytime. But when user misses mobile device, the respond to any threat like user's personal information exposal is insufficient. This paper proposes cloud service access control model to provide secure service for mobile cloud users to other level users. The proposed role-based model performs access authority when performs user certification to adapt various access security policy. Also, the proposed model uses user's attribute information and processes before user certification therefore it lowers communication overhead and service delay. As a result, packet certification delay time is increased 3.7% and throughput of certification server is increased 10.5%.

• Journal of KIISE:Software and Applications
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• v.37 no.5
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• pp.363-369
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• 2010

Demonstration-based learning has the advantage that a user can easily teach his/her robot new task knowledge just by demonstrating directly how to perform the task. However, many previous demonstration-based learning techniques used a kind of attribute-value vector model to represent their state spaces and policies. Due to the limitation of this model, they suffered from both low efficiency of the learning process and low reusability of the learned policy. In this paper, we present a new demonstration-based learning method, in which the relational model is adopted in place of the attribute-value model. Applying the relational instance-based learning to the training examples extracted from the records of the user demonstrations, the method derives a relational instance-based policy which can be easily utilized for other similar tasks in the same domain. A relational policy maps a context, represented as a pair of (state, goal), to a corresponding action to be executed. In this paper, we give a detail explanation of our demonstration-based relational policy learning method, and then analyze the effectiveness of our learning method through some experiments using a robot simulator.

• Journal of the Korea Convergence Society
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• v.8 no.11
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• pp.7-13
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• 2017

In recent years, cloud computing technology has been socially emerged that provides services remotely as various devices are used. However, there are increasing attempts by some users to provide cloud computing services with malicious intent. In this paper, we propose a property - based multi - level hierarchical approach to facilitate authentication access for users accessing servers in cloud environment. The proposed method improves the security efficiency as well as the server efficiency by hierarchically distributing a set of attribute values by replacing the order of the user 's attribute values in the form of bits according to a certain rule. In the performance evaluation, the proposed method shows that the accuracy of authentication according to the number of attributes is higher than that of the existing method by an average of 15.8% or more, and the authentication delay time of the server is decreased by 10.7% on average. As the number of attributes increases, the average overhead change is 8.5% lower than that of the conventional method.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.9 no.3
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• pp.53-62
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• 1999

The rapid growth of Internet supports a base that share useful information. It needs for mass of information that requires a fast processing capability. It needs a meta0information system. Meta-information system supports fast search service but occurs a problem in case of information security. In this paper we propose a information security attribute that are user access control for meta-information system to solve the problem.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1887-1898
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• 2018

In this paper, a method to classify insider threat activity is introduced. The internal threats help detecting anomalous activity in the procedure performed by the user in an organization. When an anomalous value deviating from the overall behavior is displayed, we consider it as an inside threat for classification as an inside intimidator. To solve the situation, Markov Chain Model is employed. The Markov Chain Model shows the next state value through an arbitrary variable affected by the previous event. Similarly, the current activity can also be predicted based on the previous activity for the insider threat activity. A method was studied where the change items for such state are defined by a transition probability, and classified as detection of anomaly of the inside threat through values for a probability variable. We use the properties of the Markov chains to list the behavior of the user over time and to classify which state they belong to. Sequential data sets were generated according to the influence of n occurrences of Markov attribute and classified by machine learning algorithm. In the experiment, only 15% of the Cert: insider threat dataset was applied, and the result was 97% accuracy except for NaiveBayes. As a result of our research, it was confirmed that the Markov Chain Model can classify insider threats and can be fully utilized for user behavior classification.