• Title/Summary/Keyword: Personal Sensitive Information

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Big Data Key Challenges

  • Alotaibi, Sultan
    • International Journal of Computer Science & Network Security
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    • v.22 no.4
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    • pp.340-350
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    • 2022
  • The big data term refers to the great volume of data and complicated data structure with difficulties in collecting, storing, processing, and analyzing these data. Big data analytics refers to the operation of disclosing hidden patterns through big data. This information and data set cloud to be useful and provide advanced services. However, analyzing and processing this information could cause revealing and disclosing some sensitive and personal information when the information is contained in applications that are correlated to users such as location-based services, but concerns are diminished if the applications are correlated to general information such as scientific results. In this work, a survey has been done over security and privacy challenges and approaches in big data. The challenges included here are in each of the following areas: privacy, access control, encryption, and authentication in big data. Likewise, the approaches presented here are privacy-preserving approaches in big data, access control approaches in big data, encryption approaches in big data, and authentication approaches in big data.

Multi-type object detection-based de-identification technique for personal information protection (개인정보보호를 위한 다중 유형 객체 탐지 기반 비식별화 기법)

  • Ye-Seul Kil;Hyo-Jin Lee;Jung-Hwa Ryu;Il-Gu Lee
    • Convergence Security Journal
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    • v.22 no.5
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    • pp.11-20
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    • 2022
  • As the Internet and web technology develop around mobile devices, image data contains various types of sensitive information such as people, text, and space. In addition to these characteristics, as the use of SNS increases, the amount of damage caused by exposure and abuse of personal information online is increasing. However, research on de-identification technology based on multi-type object detection for personal information protection is insufficient. Therefore, this paper proposes an artificial intelligence model that detects and de-identifies multiple types of objects using existing single-type object detection models in parallel. Through cutmix, an image in which person and text objects exist together are created and composed of training data, and detection and de-identification of objects with different characteristics of person and text was performed. The proposed model achieves a precision of 0.724 and mAP@.5 of 0.745 when two objects are present at the same time. In addition, after de-identification, mAP@.5 was 0.224 for all objects, showing a decrease of 0.4 or more.

The Recommendation of Controls for Hospital Information System Using CRAMM: Case Studies of Two Korean Hospitals

  • Moon, Song-Chul;Han, In-Goo;Lee, Sang-Jae
    • Korean Management Science Review
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    • v.17 no.1
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    • pp.145-158
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    • 2000
  • The medical records of diagnostic and testing information include sensitive personal information that reveals some of the most intimate aspects of an individual's life. The hospital information system (HIS) operates in a state of high risk which may lead to the possible loss to the IS resources caused by various threats. This research addresses twofold : (1) to perform asset identification ad valuation and (2) to recommend countermeasures for secure HIS network using case studies This paper applied a risk management tool CRAMM (Central Computer and Tele-communications Agency's Risk Analysis and Management Method) to assess asset values and suggest countermeasures for the security of computerized medical information of two large hospitals in Korea. CRAMM countermeasures are recommended at the reference sites from the network security requirements of system utilized for the diagnosis and treatment of patients. The results of the study will enhance the awareness of IS risk management by IS managers.

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Limited Contention Scheme(LCS) to Reduce Collision in LR-WPAN (LR-WPAN에서 충돌을 줄이기 위한 제한경쟁 기법)

  • Ko, Su-Hwan;Lee, Jong-Kyu
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.33 no.5B
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    • pp.310-317
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    • 2008
  • Data collision in LR-WPAN(Low Rate Wireless Personal Area Network) causes retransmission of which energy consumption may reduce life of the entire network. Furthermore LR-WPAN is very sensitive to collision as it has relatively fewer frequencies of backoff retries. LCS(Limited Contention Scheme) suggested in this study is a way to transmit data by certain groups of the total nodes so that it can reduce possibilities of data collision and retransmission by decreasing the number of competing nodes. As a result LCS can increase a throughput and the life of the entire network. As using LCS in designing LR-WPAN in the future can extend battery life, LCS can be useful in any application that requires low energy consumption.

Privacy Preserving Data Publication of Dynamic Datasets (프라이버시를 보호하는 동적 데이터의 재배포 기법)

  • Lee, Joo-Chang;Ahn, Sung-Joon;Won, Dong-Ho;Kim, Ung-Mo
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.18 no.6A
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    • pp.139-149
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    • 2008
  • The amount of personal information collected by organizations and government agencies is continuously increasing. When a data collector publishes personal information for research and other purposes, individuals' sensitive information should not be revealed. On the other hand, published data is also required to provide accurate statistical information for analysis. k-Anonymity and ${\iota}$-diversity models are popular approaches for privacy preserving data publication. However, they are limited to static data release. After a dataset is updated with insertions and deletions, a data collector cannot safely release up-to-date information. Recently, the m-invariance model has been proposed to support re-publication of dynamic datasets. However, the m-invariant generalization can cause high information loss. In addition, if the adversary already obtained sensitive values of some individuals before accessing released information, the m-invariance leads to severe privacy disclosure. In this paper, we propose a novel technique for safely releasing dynamic datasets. The proposed technique offers a simple and effective method for handling inserted and deleted records without generalization. It also gives equivalent degree of privacy preservation to the m-invariance model.

A Trusted Sharing Model for Patient Records based on Permissioned Blockchain

  • Kim, Kyoung-jin;Hong, Seng-phil
    • Journal of Internet Computing and Services
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    • v.18 no.6
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    • pp.75-84
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    • 2017
  • As there has been growing interests in PHR-based personalized health management project, various institutions recently explore safe methods of recording personal medical and health information. In particular, innovative medical solution can be realized when medical researchers and medical service institutes can generally get access to patient data. As EMR data is extremely sensitive, there has been no progress in clinical information exchange. Moreover, patients cannot get access to their own health data and exchange it with researchers or service institutions. It can be operated in terms of technology, yet policy environment are affected by state laws as well as Privacy and Security Policy. Blockchain technology-independent, in transaction, and under test-is introduced in the medical industry in order to settle these problems. In other words, medical organizations can grant preliminary approval on patient information exchange by using the safely encrypted and distributed Blockchain ledger and can be managed independently and completely by individuals. More apparently, medical researchers can gain access to information, thereby contributing to the scientific advance in rare diseases or minor groups in the world. In this paper, we focused on how to manage personal medical information and its protective use and proposes medical treatment exchange system for patients based on a permissioned Blockchain network for the safe PHR operation. Trusted Model for Sharing Medical Data (TMSMD), that is proposed model, is based on exchanging information as patients rely on hospitals as well as among hospitals. And introduce medical treatment exchange system for patients based on a permissioned Blockchain network. This system is a model that encrypts and records patients' medical information by using this permissioned Blockchain and further enhances the security due to its restricted counterfeit. This provides service to share medical information uploaded on the permissioned Blockchain to approved users through role-based access control. In addition, this paper presents methods with smart contracts if medical institutions request patient information complying with domestic laws by using the distributed Blockchain ledger and eventually granting preliminary approval for sharing information. This service will provide an independent information transaction and the Blockchain technology under test will be adopted in the medical industry.

Semantics-aware Obfuscation for Location Privacy

  • Damiani, Maria Luisa;Silvestri, Claudio;Bertino, Elisa
    • 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.

Effect of Collective Efficacy on Self-Disclosure in Social Network Services (소셜네트워크서비스에서 집합적 효능감이 이용자들의 자기노출에 미치는 영향)

  • Chae, Seong Wook
    • Knowledge Management Research
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    • v.19 no.1
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    • pp.19-39
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    • 2018
  • With the development of information technology, social network services (SNS) such as Facebook and Twitter became popular and many users disclose their personal and sensitive information like private story, photographs and location information through posting and sharing. Despite the privacy concerns in SNSs, individuals continue to disclose their identity online. This phenomenon is called 'privacy paradox'. The purpose of this study is to examine the role of collective efficacy on self-disclosure in SNS context and to explain privacy paradox phenomenon. Drawing upon the communication privacy management theory, research model was developed and empirically tested with cross-sectional data from 306 individuals. Results revealed that collective efficacy has a direct positive effect on self-disclosure while privacy risk is negatively related to self-disclosure. However, privacy concern is not directly related to self-disclosure. The relationship between privacy concern and self-disclosure was moderated by collective efficacy.

Development of a Privacy-Preserving Big Data Publishing System in Hadoop Distributed Computing Environments (하둡 분산 환경 기반 프라이버시 보호 빅 데이터 배포 시스템 개발)

  • Kim, Dae-Ho;Kim, Jong Wook
    • Journal of Korea Multimedia Society
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    • v.20 no.11
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    • pp.1785-1792
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    • 2017
  • Generally, big data contains sensitive information about individuals, and thus directly releasing it for public use may violate existing privacy requirements. Therefore, privacy-preserving data publishing (PPDP) has been actively researched to share big data containing personal information for public use, while protecting the privacy of individuals with minimal data modification. Recently, with increasing demand for big data sharing in various area, there is also a growing interest in the development of software which supports a privacy-preserving data publishing. Thus, in this paper, we develops the system which aims to effectively and efficiently support privacy-preserving data publishing. In particular, the system developed in this paper enables data owners to select the appropriate anonymization level by providing them the information loss matrix. Furthermore, the developed system is able to achieve a high performance in data anonymization by using distributed Hadoop clusters.

Privacy Model based on RBAC for U-Healthcare Service Environment (u-헬스케어 환경에서 환자의 무결성을 보장하는 RFID 보안 프로토콜)

  • Rhee, Bong-Keun;Jeong, Yoon-Su;Lee, Sang-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.16 no.3
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    • pp.605-614
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    • 2012
  • Nowadays u-healthcare which is very sensitive to the character of user's information among other ubiquitous computing field is popular in medical field. u-healthcare deals extremely personal information including personal health/medical information so it is exposed to various weaknees and threats in the part of security and privacy. In this paper, RFID based patient's information protecting protocol that prevents to damage the information using his or her mobile unit illegally by others is proposed. The protocol separates the authority of hospital(doctor, nurse, pharmacy) to access to patient's information by level of access authority of hospital which is registered to management server and makes the hospital do the minimum task. Specially, the management server which plays the role of gateway makes access permission key periodically not to be accessed by others about unauthorized information except authorized information and improves patient's certification and management.