• Proceedings of the Korea Society for Industrial Systems Conference
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• 2007.02a
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• pp.190-196
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• 2007

With the rapid development of electronic commerce, online reputation management systems are of increasing importance in building trust and managing risk. Reputation rating mode and aggregating method are the most crucial parts of a reputation management system. In this paper, we analyze the merits and disadvantages associated with the rating mode and aggregating approach of current reputation management systems, and put forward some suggestions. These suggestions are helpful in improving current reputation management systems and developing new reputation management systems.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.14 no.2
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• pp.35-47
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• 2004

Though P2P network systems are widely used, not so much research has been done on security issues. One of the serious problem in P2P network is the authentication problem. To resolve this problem, we introduce a new concept, a "self-reputation system" in which a user manages her own reputation. We define self-reputation systems by presenting several requirements. We also give one instance of self-reputation system. The proposed instance satisfies the requirement including the prevention of erasing and the platform independence.ependence.

• Journal of Digital Convergence
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• v.11 no.2
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• pp.235-242
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• 2013

Reputation systems aggregate users' feedback after the completion of a transaction and compute the "reputation" of products, services, or providers, which can assist other users in decision-making in the future. With the rapid growth of online e-Learning content providing services, a suitable reputation system for more credible e-Learning content delivery has become important and is essential if educational content providers are to remain competitive. Most existing reputation systems focus on generating ratings only for user reputation; they fail to consider the reputations of products or services(item reputation). However, it is essential for B2C e-Learning services to have a reliable reputation rating mechanism for items since they offer guidance for decision-making by presenting the ranks or ratings of e-Learning content items. To overcome this problem, we propose a novel collaborative filtering based reputation rating method. Collaborative filtering, one of the most successful recommendation methods, can be used to improve a reputation system. In this method, dual information sources are formed with groups of co-oriented users and expert users and to adapt it to the reputation rating mechanism. We have evaluated its performance experimentally by comparing various reputation systems.

• Convergence Security Journal
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• v.18 no.1
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• pp.103-110
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• 2018

Modern society is increasingly demanding in many areas of big data processing technology to collect, aggregate, and analyze large amounts of data over the Internet and SNS. A typical application is to evaluate the reputation of a company or college. To measure and quantify a reputation, fair and precise data and efficient data processing are very important. For this purpose, a quantitative quotient was obtained using public data, a qualitative quotient was obtained through sentiment analysis using news articles, and a complex college reputation quotient was calculated. In this paper, a complex college reputation quotient was calculated based on the quantitative index, reflecting the sentimental reputation, and based on the proposed mixed university system. In this paper, the Complex College Reputation System(CCRS) was proposed, which produced the Complex College Reputation Quotient with an objective quantitative quotient and qualitative quotient reflecting the sentimental reputation to measure the college reputation.

• Journal of the Korea Society for Simulation
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• v.19 no.1
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• pp.83-90
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• 2010

We describe a novel method for improving the performance of the UCC retrieval using content reputation and user reputation. The UCC retrieval is a part of the information retrieval. The goal of the information retrieval system finds documents what users want, so the goal of the UCC retrieval system tries to find UCCs themselves instead of documents. Unlike the document, the UCC has not enough textual information. Therefore, we try to use the content reputation and the user reputation based on non-textual information to gain improved retrieval performance. We evaluate content reputation using the information of the UCC itself and social activities between users related with UCCs. We evaluate user reputation using individual social activities between users or users and UCCs. We build a network with users and UCCs from social activities, and then we can get the user reputation from the network by graph algorithms. We collect the information of users and UCCs from YouTube and implement two systems using content reputation and user reputation. And then we compare two systems. From the experiment results, we can see that the system using content reputation outperforms than the system using user reputation. This result is expected to use the UCC retrieval in the feature.

• Annual Conference of KIPS
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• 2007.05a
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• pp.847-848
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• 2007

In this work, we analyze the role of reputation in ubiquitous healthcare system as well as the relationship of security, trust and reputation in this environment in details. In addition, an example is given to show how to use reputation system in ubiquitous healthcare and how to use reputation system on decision making.

• Journal of KIISE
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• v.42 no.10
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• pp.1286-1293
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• 2015

Most e-marketplaces build a reputation system that provides potential buyers with reputation scores of sellers in order for buyers to identify the sellers that are more reliable and trustworthy. The reputation scores are computed based on the aggregation of buyers' ratings. However, when these ratings are used to compute the reputation scores, the existing reputation systems do not make a distinction according to the following two criteria: the capability of the seller and the quality of an item. We claim that a reputation system needs to separate the two criteria in order to provide more precise information about the seller. In this paper, we propose a method to compute seller's reputation by separating the rating into the seller's score and the item's score. The proposed method computes the reputation of the seller's capability by using only the 'seller's score' and helps potential buyers to find reliable sellers who provide fast delivery and better service. In experiments, we propose a simulation strategy that reflects the real life of an E-marketplace and verify the effectiveness of our method by using the generated simulation data.

• Journal of Korea Multimedia Society
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• v.21 no.12
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• pp.1448-1458
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• 2018

Vehicular Ad-Hoc Networks (VANETs) have become one of the active areas of research, standardization, and development because they have tremendous potentials to improve vehicle and road safety, traffic efficiency, and convenience as well as comfort to both drivers and passengers. However, message trustfulness is a challenge because the propagation of false message by malicious vehicles induces unreliable and ineffectiveness of VANETs, Therefore, we need a reliable reputation method to ensure message trustfulness. In this paper, we consider a vulnerability against the Sybil attack of the previous reputation systems based on blockchain and suggest a new reputation system which resists against Sybil attack on the previous system. We propose an initial authentication process as a countermeasure against a Sybil attack and provide a reliable reputation with a cooperative message delivery to cope with message omission. In addition, we use Homomorphic Commitment to protect the privacy breaches in VANETs environment.

• Journal of Digital Convergence
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• v.15 no.2
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• pp.115-120
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• 2017

Online reputation systems for social network services(SNS) aggregate users' feedback and estimate the reputation of contents or providers. The aim of this research is to enhance credibility of the online reputation system on the SNS based e-Commerce(we called it as social commerce). SNS users usually refer to evaluations from other users who bought the products before. Most social commerce sites provide reputation system to help their customer make a decision, but sometimes we can't believe the reputation because the reputation is too subjective and the seller can deceive the customer for sales promotion. Threrefore, we usually use just the average value to show the general customer's evaluation result. We applied collaborative filtering method to give more weighting to the users who have evaluated correctly in the past. As a result, we could get more accurate evaluation results by considering each customers' credibility value that was computed by collaborative filtering.

• The KIPS Transactions:PartA
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• v.13A no.7 s.104
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• pp.599-606
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• 2006

As the P2P service does not have any administration authorities that are able to manage the behavior of participants and control the malicious users, malicious user can give harm to legitimate users for the benefit of themselves. To perform the secure transaction with new members who did not have past experiences on transaction, service users can differentiate malicious users and legitimate users by referring to the reputation information that provided by users having past experience. However, users can intentionally give false evaluation to other users on Performed transaction. We call these users as 'liar'. In this Paper, we propose a new reputation system for liar reduction to guarantee an accuracy on reputation information.