• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.875-876
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• 2011

본 논문은 온라인 사회 연결망을 위한 개인정보 보호 방안들에 대해 알아보고, 각 방안이 사회 연결망의 특성 변화에 미친 영향을 분석한다. 분석 결과, 개인정보 보호 방안들은 사회 연결망의 특성을 크게 훼손시키는 것으로 나타났다

• Proceedings of the Korea Information Processing Society Conference
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• 2007.11a
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• pp.1131-1134
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• 2007

본 논문에서는 랜덤대치(random substitution) 기법에 대하여 심도 있는 분석을 실시한다. 랜덤대치 기법의 효율적인 구현을 위하여 데이터 재구축(reconstruction) 과정에서 필요로 하는 역행렬을 구하는 공식을 제시한다. 또한, 랜덤대치에 사용되는 다양한 파라미터들의 의미를 실험적으로 밝혀내며, 정확도와 프라이버시를 합리적으로 측정할 수 있는 새로운 측도(measure)들을 제안한다.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.8
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• pp.1155-1160
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• 2013

The rapid growth of smart phones has made location-based services (LBSs) widely available. However, the use of LBS can raise privacy issues, as LBS can allow adversaries to violate the location privacy of users. There has been a considerable amount of research on preserving user location privacy. Most of these studies try to preserve location privacy by achieving what is known as location K-anonymity. In this paper, we propose a hierarchical clustering-based spatial cloaking algorithm for LBSs. The proposed algorithm constructs a tree using a modified version of agglomerative hierarchical clustering. The experimental results show, in terms of the ASR size, that the proposed algorithm is better than Hilbert Cloak and comparable to RC-AR (R-tree Cloak implementation of Reciprocal with an Asymmetric R-tree split). In terms of the ASR generation time, the proposed algorithm is much better in its performance than RC-AR and similar in performance to Hilbert Cloak.

• Journal of Computing Science and Engineering
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• v.5 no.3
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• pp.183-196
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• 2011

There has recently been a surge of interest in relational database mining that aims to discover useful patterns across multiple interlinked database relations. It is crucial for a learning algorithm to explore the multiple inter-connected relations so that important attributes are not excluded when mining such relational repositories. However, from a data privacy perspective, it becomes difficult to identify all possible relationships between attributes from the different relations, considering a complex database schema. That is, seemingly harmless attributes may be linked to confidential information, leading to data leaks when building a model. Thus, we are at risk of disclosing unwanted knowledge when publishing the results of a data mining exercise. For instance, consider a financial database classification task to determine whether a loan is considered high risk. Suppose that we are aware that the database contains another confidential attribute, such as income level, that should not be divulged. One may thus choose to eliminate, or distort, the income level from the database to prevent potential privacy leakage. However, even after distortion, a learning model against the modified database may accurately determine the income level values. It follows that the database is still unsafe and may be compromised. This paper demonstrates this potential for privacy leakage in multi-relational classification and illustrates how such potential leaks may be detected. We propose a method to generate a ranked list of subschemas that maintains the predictive performance on the class attribute, while limiting the disclosure risk, and predictive accuracy, of confidential attributes. We illustrate and demonstrate the effectiveness of our method against a financial database and an insurance database.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.5
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• pp.31-39
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• 2008

Recently, remote user authentication schemes using smart cards has been researched to provide user privacy because of increasing interest and demands. Previously, provided authentication schemes were only concerned about providing user privacy against outside attackers, but the scheme. which guarantees user privacy against both a remote server and outside attackers, has been recently demanded because the user's information has leaked out through the service providers. When the remote server perceives a user doing a malicious act, the server should be able to trace the malicious user by receiving help from a trust agency. In this paper, we suggest a scheme which not only guarantees user privacy against both a remote server and outside attackers, but also provides traceable anonymity authentication.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.6
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• pp.1147-1157
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• 2014

Intelligent transportation system (ITS) is realized through a highly ephemeral network, i.e. vehicular ad hoc network (VANET) which is on its way towards the deployment stage, thanks to the advancements in the automobile and communication technologies. However, it has not been successful, at least to date, to install the technology in the mass of vehicles due to security and privacy challenges. Besides, the users of such technology do not want to put their privacy at stake as a result of communication with peer vehicles or with the infrastructure. Therefore serious privacy measures should be taken before bringing this technology to the roads. To date, privacy issues in ephemeral networks in general and in VANET in particular, have been dealt with through various approaches. So far, multiple pseudonymous approach is the most prominent approach. However, recently it has been found out that even multiple pseudonyms cannot protect the privacy of the user and profilation is still possible even if different pseudonym is used with every message. Therefore, another privacy-aware mechanism is essential in vehicular networks. In this paper, we propose a novel identity exchange mechanism to preserve conditional privacy of the users in VANET. Users exchange their pseudonyms with neighbors and then use neighbors' pseudonyms in their own messages. To this end, our proposed scheme conditionally preserves the privacy where the senders of the message can be revoked by the authorities in case of any dispute.

• Journal of KIISE
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• v.44 no.10
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• pp.1112-1123
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• 2017

As content providers further offload content-centric services to the cloud, data retrieval over the cloud typically results in many redundant items because there is a prevalent near-duplication of content on the Internet. Simply fetching all data from the cloud severely degrades efficiency in terms of resource utilization and bandwidth, and data can be encrypted by multiple content providers under different keys to preserve privacy. Thus, locating near-duplicate data in a privacy-preserving way is highly dependent on the ability to deduplicate redundant search results and returns best matches without decrypting data. To this end, we propose an efficient near-duplicate detection scheme for encrypted data in the cloud. Our scheme has the following benefits. First, a single query is enough to locate near-duplicate data even if they are encrypted under different keys of multiple content providers. Second, storage, computation and communication costs are alleviated compared to existing schemes, while achieving the same level of search accuracy. Third, scalability is significantly improved as a result of a novel and efficient two-round detection to locate near-duplicate candidates over large quantities of data in the cloud. An experimental analysis with real-world data demonstrates the applicability of the proposed scheme to a practical cloud system. Last, the proposed scheme is an average of 70.6% faster than an existing scheme.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.9
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• pp.305-316
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• 2022

With the flood of digital data owing to the Internet of Things and big data, cloud service providers that process and store vast amount of data from multiple users can apply duplicate data elimination technique for efficient data management. The user experience can be improved as the notion of edge computing paradigm is introduced as an extension of the cloud computing to improve problems such as network congestion to a central cloud server and reduced computational efficiency. However, the addition of a new edge device that is not entirely reliable in the edge computing may cause increase in the computational complexity for additional cryptographic operations to preserve data privacy in duplicate identification and elimination process. In this paper, we propose an efficiency-improved duplicate data elimination protocol while preserving data privacy with an optimized user-edge-cloud communication framework by utilizing a trusted execution environment. Direct sharing of secret information between the user and the central cloud server can minimize the computational complexity in edge devices and enables the use of efficient encryption algorithms at the side of cloud service providers. Users also improve the user experience by offloading data to edge devices, enabling duplicate elimination and independent activity. Through experiments, efficiency of the proposed scheme has been analyzed such as up to 78x improvements in computation during data outsourcing process compared to the previous study which does not exploit trusted execution environment in edge computing architecture.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1553-1571
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• 2018

Currently, many of schemes for smart grid data aggregation are based on a one-level gateway (GW) topology. Since the data aggregation granularity in this topology is too single, the control center (CC) is unable to obtain more fine-grained data aggregation results for better monitoring smart grid. To improve this issue, Shen et al. propose an efficient privacy-preserving cube-data aggregation scheme in which the system model consists of two-level GW. However, a risk exists in their scheme that attacker could forge the signature by using leaked signing keys. In this paper, we propose a secure and fine-grained electricity consumption aggregation scheme for smart grid, which employs the homomorphic encryption to implement privacy-preserving aggregation of users' electricity consumption in the two-level GW smart grid. In our scheme, CC can achieve a flexible electricity regulation by obtaining data aggregation results of various granularities. In addition, our scheme uses the forward-secure signature with backward-secure detection (FSBD) technique to ensure the forward-backward secrecy of the signing keys. Security analysis and experimental results demonstrate that the proposed scheme can achieve forward-backward security of user's electricity consumption signature. Compared with related schemes, our scheme is more secure and efficient.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.6
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• pp.173-186
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• 2013

New information technologies make it easy to access and acquire information in various ways. However, It also enable powerful and various threat to system security. To challenge these threats, various extended access control methods are being studied. We suggest a new extended access control method that make it possible to conform to security policies enforcement even with discrepancy between policy based constraints rules and query based constraints rules via their semantic relationship. New our approach derives semantic implications using tree hierarchy structure and coordinates the exceed privileges using semantic gap factor calculating the degree of the discrepancy. In addition, we illustrate prototype system architecture and make performance comparison with existing access control methods.