• Journal of Communications and Networks
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• v.16 no.6
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• pp.592-599
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• 2014

Cloud computing enables users to easily store their data and simply share data with others. Due to the security threats in an untrusted cloud, users are recommended to compute verification metadata, such as signatures, on their data to protect the integrity. Many mechanisms have been proposed to allow a public verifier to efficiently audit cloud data integrity without receiving the entire data from the cloud. However, to the best of our knowledge, none of them has considered about the efficiency of public verification on multi-owner data, where each block in data is signed by multiple owners. In this paper, we propose a novel public verification mechanism to audit the integrity of multi-owner data in an untrusted cloud by taking the advantage of multisignatures. With our mechanism, the verification time and storage overhead of signatures on multi-owner data in the cloud are independent with the number of owners. In addition, we demonstrate the security of our scheme with rigorous proofs. Compared to the straightforward extension of previous mechanisms, our mechanism shows a better performance in experiments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.565-586
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• 2022

Cloud storage's elastic expansibility not only provides flexible services for data owners to store their data remotely, but also reduces storage operation and management costs of their data sharing. The data outsourced remotely in the storage space of cloud service provider also brings data security concerns about data integrity. Data integrity verification has become an important technology for detecting the integrity of remote shared data. However, users without data access rights to verify the data integrity will cause unnecessary overhead to data owner and cloud service provider. Especially malicious users who constantly launch data integrity verification will greatly waste service resources. Since data owner is a consumer purchasing cloud services, he needs to bear both the cost of data storage and that of data verification. This paper proposes a verification control algorithm in data integrity verification for remotely outsourced data. It designs an attribute-based encryption verification control algorithm for multiple verifiers. Moreover, data owner and cloud service provider construct a common access structure together and generate a verification sentinel to verify the authority of verifiers according to the access structure. Finally, since cloud service provider cannot know the access structure and the sentry generation operation, it can only authenticate verifiers with satisfying access policy to verify the data integrity for the corresponding outsourced data. Theoretical analysis and experimental results show that the proposed algorithm achieves fine-grained access control to multiple verifiers for the data integrity verification.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.6
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• pp.1077-1086
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• 2023

The searchable encryption model allows to selectively search for encrypted data stored on a remote server. In a real-world scenarios, the model must be able to support multiple search keywords, multiple data owners/users. In this paper, these models are referred to as Multi Ranked Searchable Encryption model. However, at the time this paper was written, the proposed models use fully-trusted trapdoor centers, some of which assume that the connection between the user and the trapdoor center is secure, which is unlikely that such assumptions will be kept in real life. In order to improve the practicality and security of these searchable encryption models, this paper proposes a new Multi Ranked Searchable Encryption model which uses random keywords to protect search words requested by the data downloader from an honest-but-curious trapdoor center with an external attacker without the assumptions. The attacker cannot distinguish whether two different search requests contain the same search keywords. In addition, experiments demonstrate that the proposed model achieves reasonable performance, even considering the overhead caused by adding this protection process.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2002.03a
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• pp.39-51
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• 2002

Online exchange is a cost-effective approach to trade goods and information among multiple sellers and buyers. Shipping industry includes lots of global entities such as shippers, liners, ship owners and shipping agents. Marine insurance companies and ship repairers and many other groups are also supporting the industry. However, international shipping exchanges are located on few cities in the world. Its our motivation that a shipping market can be online so that market participants do the dealing while sitting where they are with more efficient manner, preferable price and larger pool of candidates of trading partners. This paper presents Korean governmental project of building a cyber shipping exchange. The exchange covers ship sale and purchase, charter, insurance, freight futures, repairs, supplying of ships oil and database service. The workflows of each business were analyzed and designed to fit for online environment. The project includes design of trading mechanism, online documents, data flow, data storage and security. Online match making and trading mechanisms such as auction, reverse auction, bid are used. The whole trading process involves multiple organizations and business processes. So, this Paper focuses on how each organization would play their roles so that users can complete transactions with integrated and transparent view. The online exchange selves also as maritime portal site that links to other sites for cooperation vertically or horizontally, and serves database and information in global perspective. This paper also issues and discusses the justification of an online shipping exchange

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.05a
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• pp.149-154
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• 2001

Ship owners are demanding quieter vessels since crews have become more sensitive to their acoustic environment. Accordingly, designers of shipyards need to respond intelligently to the challenging requirements of delivering a quiet vessel. In early design stage, to predict shipboard noise the statistical approach is preferred to other methods because of simplicity. However, since the noise characteristics of the ships vary continuously with the environments, it is necessary to update the prediction formula with data base management system. This paper describes the feature of database program with the prediction method. Database management programs with GUI, are applied to Intranet system that is accessible by any users. Statistical approach to the prediction of A-weighted noise level in ship cabins, based on multiple regression analysis, is conducted. The noise levels in ship cabins are mainly affected by the parameters of the deadweight, the type of ship, the relative location of engines and cabins, the type of deckhouse, etc. As a result of verification, the formulas ensure the accuracy of 3 ㏈ in 83 % of cabins.

• Journal of the Korea Institute of Building Construction
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• v.13 no.4
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• pp.333-340
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• 2013

As construction projects become bigger, PMIS is being used as a project collaboration tool for project participants, owners, designers, inspectors and contractors. As the data type used in PMIS is usually text and most PMIS have no standard information classification system, there is a problem with data usability, such as the capacity for data search and analysis. BIM uses Objects and Properties, and this information might be used for relating with other construction information. As such, BIM technologies can be used with PMIS to enhance the data usability. The web environment is very convenient for multiple users, but the problem is that the data transfer speed is low for big files such as BIM model files. In this study, we suggested a Virtual Technology (VT) application to enhance the performance of BIM data exchange in PMIS, and tested and analyzed its efficiency when it is used to integrate BIM and PMIS in the web environment. The results of the study showed that VT can be used to enhance the efficiency of BIM data exchange in the web environment.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.647-654
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• 2023

Deep Learning is a useful method for classifying and recognizing complex data such as images and text, and the accuracy of the deep learning method is the basis for making artificial intelligence-based services on the Internet useful. However, the vast amount of user da vita used for training in deep learning has led to privacy violation problems, and it is worried that companies that have collected personal and sensitive data of users, such as photographs and voices, own the data indefinitely. Users cannot delete their data and cannot limit the purpose of use. For example, data owners such as medical institutions that want to apply deep learning technology to patients' medical records cannot share patient data because of privacy and confidentiality issues, making it difficult to benefit from deep learning technology. In this paper, we have designed a privacy preservation technique-applied deep learning technique that allows multiple workers to use a neural network model jointly, without sharing input datasets, in multi-party system. We proposed a method that can selectively share small subsets using an optimization algorithm based on modified stochastic gradient descent, confirming that it could facilitate training with increased learning accuracy while protecting private information.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.10
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• pp.429-436
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• 2017

There is a growing tendency to outsource sensitive or important data in cloud computing recently. However, it is very important to protect the privacy of outsourced data. So far, a variety of secure and efficient multi-keyword search schemes have been proposed in cloud computing environment composed of a single data owner and multiple data users. Zhang et. al recently proposed a search protocol based on multi-keyword in cloud computing composed of multiple data owners and data users but their protocol has two problems. One is that the cloud server can illegally infer the relevance between data files by going through the keyword index and user's trapdoor, and the other is that the response for the user's request is delayed because the cloud server has to execute complicated operations as many times as the size of the keyword index. In this paper, we propose an improved multi-keyword based search protocol which protects the privacy of outsourced data under the assumption that the cloud server is completely unreliable. And our experiments show that the proposed protocol is more secure in terms of relevance inference between the data files and has higher efficiency in terms of processing time than Zhang's one.