• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.3
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• pp.799-808
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• 2016

To find the pattern of personal data leak incidents and confirm which distribution is suitable for, this paper searched the personal data leak incidents reported by the media from 2011 to 2014. Based on result, this research estimated the statistical distribution using the 'K-S Statistics' and tested the 'Goodness-of-Fit'. As a result, the fact that in 95% significance level, the Poisson & Exponential distribution have high 'Goodness-of-Fit' has been proven quantitatively and, this could find it for major personal data leak incidents to occur 12 times in a year on average. This study can be useful for organizations to predict a loss of personal data leak incidents and information security investments and furthermore, this study can be a data for requirements of the cyber-insurance.

• Journal of Internet Computing and Services
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• v.19 no.3
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• pp.1-6
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• 2018

Widely used around the world, smartphones contain many features and can store content such as contacts, photos, and videos. Information that can be leaked in proportion to the information that the smartphone can store has also been increased. In recent years, accidents such as personal information leakage have occurred frequently. Personal information leakage is happening in the Android environment, which accounts for more than half of the smartphone operating system market share. Analyzing malicious apps that leak information can tell you how to prevent information leakage. Malicious apps that leak information will send importantinformation to the hacker's (C & C) server, which will use network communication. Malicious apps that are emerging nowadays encrypt and transmit important information through SSL communication. In this case, it is difficult to knowwhat kind of information is exposed to network. Therefore, we suggest a method to analyze malicious apps when leak important information through SSL communication. In this paper, we identify the way malicious apps leak information. And we propose a method for analyzing information leaked by SSL communication. Data before encryption was confirmed in the device through SSL hooking and SSL Strip method.

• 한국IT서비스학회:학술대회논문집
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• 2008.05a
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• pp.567-571
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• 2008

As computer technology grows, the risk of personal information leak on the internet is also increasing. A so-called "cookie" is used as one of the ways personal information leaks. A cookie offers convenience on the internet but serves as a major reason for personal information leakage at the same time. In this paper, we discuss risks and potential managements of a cookie.

• Convergence Security Journal
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• v.14 no.3_2
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• pp.3-12
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• 2014

The government was fully aware of the gravity of a recent massive leak of personal information of credit card users. Meanwhile, the government just took a light disciplinary action by imposing a fine, but it showed its intention to strengthen the regulations by taking the severest disciplinary action. The tightened regulations against personal information leak will be applied to the private security industry without exception to protect individual people's property and lives if such an incident occurs in that industry that deals with a wide variety of personal information such as CCTV data or privacy information all the time. The purpose of this study was to examine the state of the protection and management of personal information for service users among private security firms in an effort to suggest some reform measures. The findings of the study were as follows: First, administrators or managers who are involved with personal information protection should make a full-fledged effort to gather information. Second, counseling or related programs should be provided for small and mid-sized security firms to guarantee thorough personal information protection. Third, Korea Security Association should improve the educational system related to personal information protection to resolve problems with this education currently provided for managers and employees of these companies.

• Journal of Advanced Navigation Technology
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• v.18 no.5
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• pp.494-500
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• 2014

Recently the leak of personal information from in-house and contract-managed companies has been continually increasing, which leads a regular observation on outsourcing companies that perform the personal information management system to prevent dangers from the leakage, stolen and loss of personal information. However, analyzing many numbers of computers in limited time has found few difficulties in some circumstances-such as outsourcing companies that own computers that have personal information system or task continuities that being related to company's profits. For the reason, it is necessary to select an object of examination through identifying a high-risk of personal data leak. In this paper, this study will formulate a proposal for the selection of high-risk subjects, which is based on the user interface, by digital forensic. The study designs the integrated analysis tool and demonstrates the effects of the tool through the test results.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.257-260
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• 2014

Digital Forensics in the event of an accident, the system restore files and the only way to find evidence KT Website hacking happening now, credit card companies, and leakage of personal information by three recent spills occurred, such as Skin Food Home Up Customer Information hackers to find these crimes only means as well. This study attempted to bypass the KT website hacking attacks utilizing automated programs hacking programs, and if you try to experiment on whether any information has been disclosed and if so what home attacked forensics evidence for hackers to locate the can make a report is described.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.4
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• pp.657-667
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• 2020

The Android framework allows apps to take full advantage of personal information through granting single permission, and does not determine whether the data being leaked is actual personal information. To solve these problems, we propose a tool with static/dynamic analysis. The tool analyzes the Source and Sink used by the target app, to provide users with information on what personal information it used. To achieve this, we extracted the Source and Sink through Control Flow Graph and make sure that it leaks the user's privacy when there is a Source-to-Sink flow. We also used the sensitive permission information provided by Google to obtain information from the sensitive API corresponding to Source and Sink. Finally, our dynamic analysis tool runs the app and hooks information from each sensitive API. In the hooked data, we got information about whether user's personal information is leaked through this app, and delivered to user. In this process, an automated Source/Sink classification model was applied to collect latest Source/Sink information, and the we categorized latest release version of Android(9.0) with 88.5% accuracy. We evaluated our tool on 2,802 APKs, and found 850 APKs that leak personal information.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.11
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• pp.489-494
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• 2013

Personal information has been transmitted in a variety of services of Internet environment, but individual users do not know what information is sent. In this paper, we aim to develop a monitoring tool that continuously monitors personal sensitive information in network packets and informs the user whether or not to leak. So we implement a monitoring tool of personal information and analyze the experiment results. In addition, we introduce a prevention of confidential information in company and a leakage prevention of medical information, for applications that take direct advantage. The results of this study, by contributing to prevent leakage of personal information, can help reduce cyber threats variously targeting personal information of users.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.1
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• pp.195-203
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• 2019

Mobile applications stores such as Google Play Store and Apple App Store, are widely used to distribute a variety of applications including finance, shopping, and entertainment. Recently, however, vulnerabilities of the mobile applications are likely to violate users' privacy such as personal information leakage. In this paper, we classify mobile applications that can be download from mobile stores, and analyze the personal information that could be leaked when users are using the mobile applications. As a result of analysis, we found that personal information are leaked in some widely used mobile applications in practice. On the basis of our experiment results, we propose some mitigations to enhance security of the mobile applications and prevent leakage of personal information.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.6
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• pp.1199-1206
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• 2013

SNS is relationship based service and its users are increasing rapidly because it can be used in variety forms as penetration rate of Smartphone increased. Accordingly personal information can be exposed easily and spread rapidly in SNS so self-control on information management, right to control open and distribution of own personal information is necessary. This research suggest way of measuring personal information leaking risk factor through personal information leaking possible territory's, based on property value and relationship of personal information in SNS, personal information exposure frequency and access rate. Suggested method expects to used in strengthening self-control on information management right by arousing attention of personal information exposure to SNS users.