• Journal of Internet Computing and Services
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• v.19 no.2
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• pp.1-7
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• 2018

Due to advances in DNA sequencing technologies, its medical value continues to grow. However, once genome data leaked, it cannot be revoked, and disclosure of personal genome information impacts a large group of individuals. Therefore, secure techniques for managing genomic big data should be developed. We first propose a privacy-preserving inner product protocol for large data sets using the homomorphic encryption of Gentry et al., and then we introduce an efficient privacy-preserving DNA matching protocol based on the proposed protocol. Our efficient protocol satisfies the requirements of correctness, confidentiality, and privacy.

• The Journal of Asian Finance, Economics and Business
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• v.5 no.1
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• pp.29-41
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• 2018

These days, corporate risk management has become a major concern in the corporate world. Companies in the global environment are exposed to diverse kinds of risks that are affecting the decisions of investors and other stakeholders. Therefore, companies are expected to not only identify and manage risks but also voluntarily report the same to the stakeholders. Increasingly, standard setters and regulators are requiring firms to disclose such information. On the contrary, there also exists a perception that risk reporting can create a negative impression among the stakeholders about the future of the company. In line with such growing dilemma for risk disclosures, the issue of corporate risk reporting (CRR) has been receiving immense emphasis from the accounting academicians. The main objective of this article is to conduct a comprehensive literature review on corporate risk disclosures. In order to fulfill this objective, at first, a summary of the relevant available literature is presented to identify the current regulations on risk reporting, existing trends of CRR research and theories applied in research. Then, through analysis, several research avenues are identified. It is expected that if these dimensions are explored by the future researchers, a better and broader understanding of the risk reporting practices can be achieved.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.3
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• pp.162-168
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• 2014

Cross-Site Request Forgery is one of the attack techniques occurring in today's Web Applications. It allows an unauthorized attacker to send authorized requests to Web Server through end-users' browsers. These requests are approved by the Web Server as normal requests therefore unexpected results arise. The problem is that the Web Server verifies an end-user using his Cookie information. In this paper, we propose an enhanced CSRF defense scheme which uses Page Identifier and user password's hash value in addition to the Cookie value which is used to verify the normal requests. Our solution is simple to implement and solves the problem of the token disclosure when only a random token is used for normal request verification.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.14 no.3
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• pp.145-153
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• 2004

Digital fingerprinting schemes are cryptographic methods that a seller can identify a traitor who illegally redistributed digital contents by embedding it into buyer's information. Recently, Josep Domingo-Ferrer suggested an anonymous digital fingerprinting scheme based on committed oblivious transfer protocol. It is significant in the sense that it is completely specified from a computation point of view and is thus readily implementable. But this scheme has the serious problem that it cannot provide the security of buyers. In this paper, we first show how to break the existing committed oblivious transfer-based fingerprinting schemes and then suggest secure fingerprinting scheme by introducing oblivious transfer protocol with two-lock cryptosystem based on discrete logarithm. All computations are performed efficiently and the security degree is strengthened in our proposal.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.323-342
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• 2021

Personal health records (PHRs) is an electronic medical system that enables patients to acquire, manage and share their health data. Nevertheless, data confidentiality and user privacy in PHRs have not been handled completely. As a fine-grained access control over health data, ciphertext-policy attribute-based encryption (CP-ABE) has an ability to guarantee data confidentiality. However, existing CP-ABE solutions for PHRs are facing some new challenges in access control, such as policy privacy disclosure and dynamic policy update. In terms of addressing these problems, we propose a privacy protection and dynamic share system (PPADS) based on CP-ABE for PHRs, which supports full policy hiding and flexible access control. In the system, attribute information of access policy is fully hidden by attribute bloom filter. Moreover, data user produces a transforming key for the PHRs Cloud to change access policy dynamically. Furthermore, relied on security analysis, PPADS is selectively secure under standard model. Finally, the performance comparisons and simulation results demonstrate that PPADS is suitable for PHRs.

• The Journal of Information Systems
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• v.31 no.3
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• pp.67-87
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• 2022

Purpose This study quantified companies' views on the COVID-19 pandemic with sentiment analysis of U.S. public companies' disclosures. It aims to provide timely insights to shareholders, investors, and consumers by analyzing and visualizing sentiment changes over time as well as similarities and differences by industry. Design/methodology/approach From more than fifty thousand Form 10-K and Form 10-Q published between 2020 and 2021, we extracted over one million texts related to the COVID-19 pandemic. Using the FinBERT language model fine-tuned in the finance domain, we conducted sentiment analysis of the texts, and we quantified and classified the data into positive, negative, and neutral. In addition, we illustrated the analysis results using various visualization techniques for easy understanding of information. Findings The analysis results indicated that U.S. public companies' overall sentiment changed over time as the COVID-19 pandemic progressed. Positive sentiment gradually increased, and negative sentiment tended to decrease over time, but there was no trend in neutral sentiment. When comparing sentiment by industry, the pattern of changes in the amount of positive and negative sentiment and time-series changes were similar in all industries, but differences among industries were shown in neutral sentiment.

• Journal of Distribution Science
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• v.20 no.9
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• pp.73-81
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• 2022

Purpose: This study aimed to examine whether key audit matters (KAMs) readability influences investor reaction. Research design, data, and methodology: The signaling theory was applied to explain the behavior of investors when they receive useful information for their decisions. Data were collected from 1,866 firm-year observations from Thai listed companies in both the Stock Exchange of Thailand (SET) and the Market for Alternative Investment (MAI) for the fiscal years of 2016-2019. The study was based on secondary data, which were collected from the SET Market Analysis and Reporting Tool (SETSMART) database and the Stock Exchange of Thailand's website (www.set.or.th). A statistical regression method was used with panel data analysis to evaluate possible associations between KAMs readability and investor reaction. The study relied on popular readability measures (Fog Index). Moreover, investor reaction was measured by absolute cumulative abnormal return and abnormal trading volume. Results: It was found that the KAMs readability has positive significance on both absolute cumulative abnormal return and abnormal trading volume. Conclusion: This study showed a significant contribution to the implication of KAMs in an emerging economy. The results reveal that more readable KAMs disclosure distributed new insights and useful information to investors and led to reducing the information gap between auditors and investors.

• Asia pacific journal of information systems
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• v.32 no.3
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• pp.601-629
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• 2022

Social networking sites (SNSs) have become an essential part of people's lives. It is thus crucial to understand how individuals use these platforms. Previous literature has divided usage into numerous activities and then grouped them into dimensions to avoid excessive granularity. However, these categories have not been derived from a uniform theoretical background; consequently, these dimensions are dispersed, overlapping, and disconnected from each other. This study argues that "SNS usage" is a complex phenomenon consisting of multiple activities that can be grouped into dimensions under the umbrella of communication theories and these dimensions are related to each other in a particular multi-dimensional architecture. "SNS usage" is conceptualized as a third-order construct formed by "producing," "consuming," and "communicating." "Producing," in turn, is proposed as a second-order construct manifested by "commenting," "general information sharing," and "self-disclosure." The proposed model was assessed with data collected from 414 USA adult users and PLS-SEM technique. The results show empirical support for the theorized model. SNS providers now have this architecture that clarifies the role of each dimension of use, which will allow them to design effective strategies to encourage the use of these networks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.4
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• pp.1090-1100
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• 2024

While the incorporating ESG indicator is recognized as crucial for sustainability and increased firm value, inconsistent disclosure of ESG data and vague assessment standards have been key challenges. To address these issues, this study proposes an ambiguous text-based automated ESG rating strategy. Earnings Call Transcript data were classified as E, S, or G using the Refinitiv-Sustainable Leadership Monitor's over 450 metrics. The study employed advanced natural language processing techniques such as BERT, RoBERTa, ALBERT, FinBERT, and ELECTRA models to precisely classify ESG documents. In addition, the authors computed the average predicted probabilities for each label, providing a means to identify the relative significance of different ESG factors. The results of experiments demonstrated the capability of the proposed methodology in enhancing ESG assessment criteria established by various rating agencies and highlighted that companies primarily focus on governance factors. In other words, companies were making efforts to strengthen their governance framework. In conclusion, this framework enables sustainable and responsible business by providing insight into the ESG information contained in Earnings Call Transcript data.

• Journal of Convergence for Information Technology
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• v.7 no.2
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• pp.125-130
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• 2017

In the business environment of the modern society, it is not possible for the company, which is a producer of accounting information, to provide accounting information to the users of accounting information because it can not satisfy the information demand of the accounting information users due to the problem of information asymmetry. Therefore, the purpose of this study is to find out what information should be provided for satisfying the information needs of users of accounting information. This study investigates the qualitative characteristics of accounting information based on K-IFRS in the provision of accounting information and conducts empirical studies based on the users of accounting information of listed companies and unlisted companies. And how to improve the satisfaction. As a result of empirical research, it was confirmed that the accounting information satisfying the qualitative characteristics is useful for meeting the information needs of users of accounting information.