• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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• 2006.06a
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• pp.765-773
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• 2006

In ubiquitous environment, private enterprise or public institution's privacy data are sometimes exposed to hackers because of the lack of the sense of information security. We apply secret sharing scheme to solve the privacy problems. But, the existing secret sharing scheme are not suitable for the management of large a quantity of data because that required operation of large capacity. In this paper, We propose new secret sharing scheme for privacy data management. Our scheme makes high-speed operation possible, and it also allows for set weight for each secret pieces depending on weight of participants. The scheme proposed in this paper makes it efficient to collect and manage secure privacy data in ubiquitous environment.

• Journal of Computing Science and Engineering
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• v.2 no.2
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• pp.137-160
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• 2008

The increasing availability of personal location data pushed by the widespread use of location-sensing technologies raises concerns with respect to the safeguard of location privacy. To address such concerns location privacy-preserving techniques are being investigated. An important area of application for such techniques is represented by Location Based Services (LBS). Many privacy-preserving techniques designed for LBS are based on the idea of forwarding to the LBS provider obfuscated locations, namely position information at low spatial resolution, in place of actual users' positions. Obfuscation techniques are generally based on the use of geometric methods. In this paper, we argue that such methods can lead to the disclosure of sensitive location information and thus to privacy leaks. We thus propose a novel method which takes into account the semantic context in which users are located. The original contribution of the paper is the introduction of a comprehensive framework consisting of a semantic-aware obfuscation model, a novel algorithm for the generation of obfuscated spaces for which we report results from an experimental evaluation and reference architecture.

• Journal of Digital Convergence
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• v.13 no.2
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• pp.121-126
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• 2015

SME informatization level analysis is significant as an indicator for analyzing the performance and competitiveness of enterprises. However, as has recently been highlighted, the importance of privacy recognized as infrastructure, and mindset are very important indicators for security and privacy. Therefore, In this study, analysis of SMEs at the informatization level, with a focus on how we can assess whether the privacy-related activities were carried out.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.450-470
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• 2023

Traditional cloud computing faces some challenges such as huge energy consumption, network delay and single point of failure. Edge computing is a typical distributed processing platform which includes multiple edge servers closer to the users, thus is more robust and can provide real-time computing services. Although outsourcing data to edge servers can bring great convenience, it also brings serious security threats. In order to provide image retrieval while ensuring users' data privacy, a privacy preserving image retrieval scheme in edge environment is proposed. Considering the distributed characteristics of edge computing environment and the requirement for lightweight computing, we present a privacy-preserving image retrieval scheme in edge computing environment, which two or more "honest but curious" servers retrieve the image quickly and accurately without divulging the image content. Compared with other traditional schemes, the scheme consumes less computing resources and has higher computing efficiency, which is more suitable for resource-constrained edge computing environment. Experimental results show the algorithm has high security, retrieval accuracy and efficiency.

• The Korean Journal of Health Service Management
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• v.9 no.2
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• pp.23-32
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• 2015

In this paper, we evaluated web security vulnerability and privacy information management of hospital web sites which are registered at the Korea Hospital Association. Vulnerability Scanner (WVS) based on the OWASP Top 10 was used to evaluate the web security vulnerability of the web sites. And to evaluate the privacy information management, we used ten rules which were based on guidelines for protecting privacy information on web sites. From the results of the evaluation, we discovered tertiary hospitals had relatively excellent web security compared to other type of hospitals. But all the hospital types had not only high level vulnerabilities but also the other level of vulnerabilities. Additionally, 97% of the hospital web sites had a certain level of vulnerability, so a security inspection is needed to secure the web sites. We discovered a few SQL Injection and XSS vulnerabilities in the web sites of tertiary hospitals. However, these are very critical vulnerabilities, so all hospital types have to be inspected to protect their web sites against attacks from hacker. On the other hand, the inspection results of the tertiary hospitals for privacy information management had a better compliance rate than that of the other hospital types.

• Journal of Digital Convergence
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• v.11 no.1
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• pp.237-242
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• 2013

SNS is emerging as an academic and social interest, as Facebook and Twitter are developed explosively. But, SNS has a problem of exposing user's privacy because it is originated by exchanging user's personal information and opinion. This paper proposes SNS user privacy protecting model using data separation and false data information instead of blocking which is using to protect user's personal privacy. The proposed model do not let the third party extract precise information after collecting user's context information by adding false information to separated context information. Also, it gets user's agreement beforehand if SNS service provider uses user's information not to be used illegally by the third party.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.17 no.1
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• pp.89-96
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• 2007

Radio Frequency Identification system based on EPC(Electronic Product Code) Network Environment can read or write information of tagged objects, using Rf signals without direct contact. This advantage which is to provide storage ability and contactless property is better than Bar-code system. Mobile RFID system which integrates Mobile system with RFID system will provide new additional service to users. However, an advantage for obtaining information of objects using RF signal causes personal privacy problem. In this paper, we propose techniques that can protect personal privacy based on mobile. Our scheme provides privacy protection of users and is more efficiently than another application service.

• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.137-142
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• 2021

Machine-learning systems have proven their worth in various industries, including healthcare and banking, by assisting in the extraction of valuable inferences. Information in these crucial sectors is traditionally stored in databases distributed across multiple environments, making accessing and extracting data from them a tough job. To this issue, we must add that these data sources contain sensitive information, implying that the data cannot be shared outside of the head. Using cryptographic techniques, Privacy-Preserving Machine Learning (PPML) helps solve this challenge, enabling information discovery while maintaining data privacy. In this paper, we talk about how to keep your data mining private. Because Data mining has a wide variety of uses, including business intelligence, medical diagnostic systems, image processing, web search, and scientific discoveries, and we discuss privacy-preserving in deep learning because deep learning (DL) exhibits exceptional exactitude in picture detection, Speech recognition, and natural language processing recognition as when compared to other fields of machine learning so that it detects the existence of any error that may occur to the data or access to systems and add data by unauthorized persons.

• International Journal of Computer Science & Network Security
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• v.21 no.12spc
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• pp.399-408
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• 2021

Information security reports four types of basic attacks on information. One of the attacks is named as fabrication. Even though mobile devices and applications are showing its maturity in terms of performance, security and ubiquity, location-based applications still faces challenges of quality of service, privacy, integrity, authentication among mobile devices and hence mobile users associated with the devices. There is always a continued fear as how location information of users or IoT appliances is used by third party LB Service providers. Even adversary or malicious attackers get hold of location information in transit or fraudulently hold this information. In this paper, location information fabrication scenarios are presented after knowing basic model of information attacks. Peer-to-Peer broadcast model of location privacy is proposed. This document contains introduction to fabrication, solutions to such threats, management of fabrication mitigation in collaborative or peer to peer location privacy and its cost analysis. There are various infrastructure components in Location Based Services such as Governance Server, Point of interest POI repository, POI service, End users, Intruders etc. Various algorithms are presented and analyzed for fabrication management, integrity, and authentication. Moreover, anti-fabrication mechanism is devised in the presence of trust. Over cost analysis is done for anti-fabrication management due to nature of various cryptographic combinations.

• Asia pacific journal of information systems
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• v.22 no.4
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• pp.7-29
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• 2012

Smartphone and its applications (i.e. apps) are increasingly penetrating consumer markets. According to a recent report from Korea Communications Commission, nearly 50% of mobile subscribers in South Korea are smartphone users that accounts for over 25 million people. In particular, the importance of smartphone has risen as a geospatially-aware device that provides various location-based services (LBS) equipped with GPS capability. The popular LBS include map and navigation, traffic and transportation updates, shopping and coupon services, and location-sensitive social network services. Overall, the emerging location-based smartphone apps (LBA) offer significant value by providing greater connectivity, personalization, and information and entertainment in a location-specific context. Conversely, the rapid growth of LBA and their benefits have been accompanied by concerns over the collection and dissemination of individual users' personal information through ongoing tracking of their location, identity, preferences, and social behaviors. The majority of LBA users tend to agree and consent to the LBA provider's terms and privacy policy on use of location data to get the immediate services. This tendency further increases the potential risks of unprotected exposure of personal information and serious invasion and breaches of individual privacy. To address the complex issues surrounding LBA particularly from the user's behavioral perspective, this study applied the privacy calculus model (PCM) to explore the factors that influence the adoption of LBA. According to PCM, consumers are engaged in a dynamic adjustment process in which privacy risks are weighted against benefits of information disclosure. Consistent with the principal notion of PCM, we investigated how individual users make a risk-benefit assessment under which personalized service and locatability act as benefit-side factors and information privacy risks act as a risk-side factor accompanying LBA adoption. In addition, we consider the moderating role of trust on the service providers in the prohibiting effects of privacy risks on user intention to adopt LBA. Further we include perceived ease of use and usefulness as additional constructs to examine whether the technology acceptance model (TAM) can be applied in the context of LBA adoption. The research model with ten (10) hypotheses was tested using data gathered from 98 respondents through a quasi-experimental survey method. During the survey, each participant was asked to navigate the website where the experimental simulation of a LBA allows the participant to purchase time-and-location sensitive discounted tickets for nearby stores. Structural equations modeling using partial least square validated the instrument and the proposed model. The results showed that six (6) out of ten (10) hypotheses were supported. On the subject of the core PCM, H2 (locatability ${\rightarrow}$ intention to use LBA) and H3 (privacy risks ${\rightarrow}$ intention to use LBA) were supported, while H1 (personalization ${\rightarrow}$ intention to use LBA) was not supported. Further, we could not any interaction effects (personalization X privacy risks, H4 & locatability X privacy risks, H5) on the intention to use LBA. In terms of privacy risks and trust, as mentioned above we found the significant negative influence from privacy risks on intention to use (H3), but positive influence from trust, which supported H6 (trust ${\rightarrow}$ intention to use LBA). The moderating effect of trust on the negative relationship between privacy risks and intention to use LBA was tested and confirmed by supporting H7 (privacy risks X trust ${\rightarrow}$ intention to use LBA). The two hypotheses regarding to the TAM, including H8 (perceived ease of use ${\rightarrow}$ perceived usefulness) and H9 (perceived ease of use ${\rightarrow}$ intention to use LBA) were supported; however, H10 (perceived effectiveness ${\rightarrow}$ intention to use LBA) was not supported. Results of this study offer the following key findings and implications. First the application of PCM was found to be a good analysis framework in the context of LBA adoption. Many of the hypotheses in the model were confirmed and the high value of $R^2$ (i.,e., 51%) indicated a good fit of the model. In particular, locatability and privacy risks are found to be the appropriate PCM-based antecedent variables. Second, the existence of moderating effect of trust on service provider suggests that the same marginal change in the level of privacy risks may differentially influence the intention to use LBA. That is, while the privacy risks increasingly become important social issues and will negatively influence the intention to use LBA, it is critical for LBA providers to build consumer trust and confidence to successfully mitigate this negative impact. Lastly, we could not find sufficient evidence that the intention to use LBA is influenced by perceived usefulness, which has been very well supported in most previous TAM research. This may suggest that more future research should examine the validity of applying TAM and further extend or modify it in the context of LBA or other similar smartphone apps.