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Ȩ Ȩ > ¿¬±¸¹®Çå > Çмú´ëȸ ÇÁ·Î½Ãµù > Çѱ¹Á¤º¸Åë½ÅÇÐȸ Çмú´ëȸ > 2017³â Ãá°èÇмú´ëȸ

2017³â Ãá°èÇмú´ëȸ

Current Result Document :

ÇѱÛÁ¦¸ñ(Korean Title) ºòµ¥ÀÌŸ ºñ½Äº°È­ ±â¼ú°ú À̽´
¿µ¹®Á¦¸ñ(English Title) De-identification Techniques for Big Data and Issues
ÀúÀÚ(Author) ÃÖ½ÂÇ¥   ½Å»ó¿í   Seoung Pyo Choi   Sang Uk Shin   ¿ì¼ºÈñ   SungHee Woo  
¿ø¹®¼ö·Ïó(Citation) VOL 21 NO. 01 PP. 0750 ~ 0753 (2017. 06)
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(Korean Abstract)
ÃÖ±Ù ½º¸¶Æ®Æù, SNS, »ç¹°ÀÎÅͳÝÀÌ È®»êµÇ¸é¼­ »ý°Ü³ª´Â ºòµ¥ÀÌŸÀÇ Ã³¸®¿Í È°¿ëÀÌ ICT ºÐ¾ßÀÇ »õ·Î¿î ¼ºÀå µ¿·ÂÀ¸·Î ºÎ»óÇÏ°í ÀÖ´Ù. ÇÏÁö¸¸ ÀÌ·¯ÇÑ ºòµ¥ÀÌÅÍÀÇ È°¿ëÀ» À§Çؼ­´Â °³ÀÎÁ¤º¸ ºñ½Äº°È­°¡ ÀÌ·ç¾îÁ®¾ßÇÑ´Ù. ºñ½Äº°È­´Â °³ÀÎÀÇ µ¥ÀÌÅÍ°¡ ƯÁ¤Àΰú ¿¬°áµÇÁö ¾Êµµ·Ï µ¥ÀÌÅÍ ¼ÂÀ¸·ÎºÎÅÍ ½Äº°Á¤º¸¸¦ Á¦°ÅÇÏ´Â °ÍÀ¸·Î Á¤º¸¸¦ ¼öÁý, ó¸®, º¸°ü ȤÀº ¹èÆ÷Çϴµ¥ ÀÖ¾î ¹ß»ýÇÒ ¼ö ÀÖ´Â °³ÀÎÁ¤º¸³ëÃâÀÇ À§ÇèÀ» ÁÙÀÌ¸ç ±× Á¤º¸¸¦ È°¿ëÇÏ°í °øÀ¯Çϴµ¥ ±× ¸ñÀûÀ» µÎ°í ÀÖ´Ù. ºñ½Äº°È­µÈ Á¤º¸´Â ¶ÇÇÑ Àç½Äº°È­µÇ¾î °³ÀÎÁ¤º¸º¸È£ÀÇ ³í¶õÀÌ µÇ°í ÀÖÁö¸¸ ºòµ¥ÀÌÅ͵îÀÇ °³ÀÎÁ¤º¸°¡ ºñ½Äº° 󸮵Ǿî È°¿ëµÇ´Â »ç·Ê´Â Á¡Â÷ Áõ°¡ÇÏ°í ÀÖ´Ù. ¶ÇÇÑ ¸¹Àº ºñ½Äº°È­ °¡À̵å¶óÀÎÀÇ µîÀå°ú ÇÔ²² °³ÀÎÁ¤º¸ ºñ½Äº°È­ ¹æ¹ýÀÌ Á¦½ÃµÇ°í ÀÖ´Ù. µû¶ó¼­ º» ¿¬±¸¿¡¼­´Â ºòµ¥ÀÌŸ ºñ½Äº°È­ °úÁ¤°ú »çÈÄ°ü¸®¸¦ ¼­¼ú, ºñ½Äº°È­ ¹æ¹ýÀ» ºñ±³ºÐ¼®ÇÏ°í ºñ½Äº°È­¿Í °³ÀÎÁ¤º¸º¸È£ °ü·Ã À̽´¿Í ÇØ°á°úÁ¦¸¦ Á¦½ÃÇÑ´Ù.
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(English Abstract)
Recently, the processing and utilization of big data, which is generated by the spread of smartphone, SNS, and the internet of things, is emerging as a new growth engine of ICT field. However, in order to utilize such big data, De-identification of personal information should be done. De-identification removes identifying information from a data set so that individual data cannot be linked with specific individuals. De-identification can reduce the privacy risk associated with collecting, processing, archiving, distributing or publishing information, thus it attempts to balance the contradictory goals of using and sharing personal information while protecting privacy. De-identified information has also been re-identified and has been controversial for the protection of personal information, but the number of instances where personal information such as big data is de-identified and processed is increasing. In addition, many de-identification guidelines have been introduced and a method for de-identification of personal information has been proposed. Therefore, in this study, we describe the big data de-identification process and follow-up management, and then compare and analyze de-identification methods. Finally we provide personal information protection issues and solutions.
Å°¿öµå(Keyword) HCI(Hyper Converged Infrastructure)   Hyper Converged   ¸ÁºÐ¸®   °¡»óÈ­   VDI(Virtual Desktop Infrastructure)   ºñ½Äº°È­   Á¤º¸º¸È£   Àç½Äº°È­   ºòµ¥ÀÌÅÍ  
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