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Ȩ Ȩ > ¿¬±¸¹®Çå > ±¹³» ³í¹®Áö > Çѱ¹Á¤º¸Ã³¸®ÇÐȸ ³í¹®Áö > Á¤º¸Ã³¸®ÇÐȸ ³í¹®Áö ÄÄÇ»ÅÍ ¹× Åë½Å½Ã½ºÅÛ

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Current Result Document :

ÇѱÛÁ¦¸ñ(Korean Title) ¼Ò¼È ºòµ¥ÀÌÅÍ ¸¶ÀÌ´× ±â¹Ý ½Ç½Ã°£ ·£¼¶¿þ¾î ÀüÆÄ °¨Áö ½Ã½ºÅÛ
¿µ¹®Á¦¸ñ(English Title) Real-Time Ransomware Infection Detection System Based on Social Big Data Mining
ÀúÀÚ(Author) ±èÁö½É   ¹Ú¹Ì¼ø   ±è°æ¾Æ   ¹®³²¹Ì   ÀÌÁ¤¿ø   ÃÖÀ¯ÁÖ   Ji-Sim Kim   MiSoon Park   Kyong Ah Kim   Nammee Moon   Jung-Won Lee   Yoo-Joo Choi   ±è¹ÌÈñ   À±ÁØÇõ   Mihui Kim   Junhyeok Yun  
¿ø¹®¼ö·Ïó(Citation) VOL 07 NO. 10 PP. 0251 ~ 0258 (2018. 10)
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(Korean Abstract)
ÆÄÀÏÀ» ¾Ïȣȭ½ÃÄÑ ¸ö°ªÀ» ¿ä±¸ÇÏ´Â ¾Ç¼º ¼ÒÇÁÆ®¿þ¾îÀÎ ·£¼¶¿þ¾î´Â ºü¸¥ ÀüÆķ°ú Áö´ÉÈ­·Î ´õ¿í À§ÇùÀûÀÌ µÇ°í ÀÖ´Ù. ÀÌ¿¡ ºü¸¥ ŽÁö ¹× À§Çè ºÐ¼®ÀÌ ¿ä±¸µÇ°í ÀÖÁö¸¸, ½Ç½Ã°£ ºÐ¼® ¹× º¸°í°¡ ¹ÌºñÇÑ »óÅÂÀÌ´Ù. º» ³í¹®¿¡¼­´Â ½Ç½Ã°£ ºÐ¼®ÀÌ °¡´ÉÇϵµ·Ï ¼Ò¼È ºòµ¥ÀÌÅÍ ¸¶ÀÌ´× ±â¼úÀ» È°¿ëÇÏ¿© ·£¼¶¿þ¾î ÀüÆÄ °¨Áö ½Ã½ºÅÛÀ» Á¦¾ÈÇÑ´Ù. º» ½Ã½ºÅÛ¿¡¼­´Â Æ®À§ÅÍ ½ºÆ®¸²À» ½Ç½Ã°£ ºÐ¼®ÇÏ¿© ·£¼¶¿þ¾î¿Í °ü·ÃµÈ Å°¿öµå¸¦ °¡Áø Æ®À­À» Å©·Ñ¸µÇÑ´Ù. ¶ÇÇÑ ´º½ºÇÇµå ºÐ¼®±â¸¦ ÅëÇØ ´º½º¼­¹ö¸¦ Å©·Ñ¸µÇÏ¿© ·£¼¶¿þ¾î °ü·Ã Å°¿öµå¸¦ ÃßÃâÇÏ°í, º¸¾È¾÷üÀÇ ¼­¹ö³ª Ž»ö ¿£ÁøÀ» ÅëÇØ ´º½º³ª Åë°èµ¥ÀÌÅ͸¦ ÃßÃâÇÑ´Ù. ¼öÁýµÈ µ¥ÀÌÅÍ´Â µ¥ÀÌÅÍ ¸¶ÀÌ´× ¾Ë°í¸®ÁòÀ¸·Î ·£¼¶¿þ¾î °¨¿° Á¤µµ¸¦ ºÐ¼®ÇÑ´Ù. 2017³â ÀüÆÄ°¡ ¸¹ÀÌ µÇ¾ú´ø ¿ö³ÊÅ©¶óÀÌ¿Í ·ÏÅ° ·£¼¶¿þ¾î °¨¿°ÀüÆÄ ½Ã °ü·Ã Æ®À­ÀÇ ¼ö¿Í ±¸±Û Æ®·»µå(Åë°è Á¤º¸) Á¤º¸, °ü·Ã ±â»ç¸¦ ºñ±³ÇÏ¿© Æ®À­À» ÀÌ¿ëÇÑ º» ½Ã½ºÅÛÀÇ ·£¼¶¿þ¾î °¨¿° ŽÁö °¡´É¼ºÀ» º¸ÀÌ°í, ¿£Æ®·ÎÇÇ¿Í Ä«ÀÌ-½ºÄù¾î ºÐ¼®À» ÅëÇØ Á¦¾È ½Ã½ºÅÛ ¼º´ÉÀ» º¸ÀδÙ.
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(English Abstract)
Ransomware, a malicious software that requires a ransom by encrypting a file, is becoming more threatening with its rapid propagation and intelligence. Rapid detection and risk analysis are required, but real-time analysis and reporting are lacking. In this paper, we propose a ransomware infection detection system using social big data mining technology to enable real-time analysis. The system analyzes the twitter stream in real time and crawls tweets with keywords related to ransomware. It also extracts keywords related to ransomware by crawling the news server through the news feed parser and extracts news or statistical data on the servers of the security company or search engine. The collected data is analyzed by data mining algorithms. By comparing the number of related tweets, google trends (statistical information), and articles related wannacry and locky ransomware infection spreading in 2017, we show that our system has the possibility of ransomware infection detection using tweets. Moreover, the performance of proposed system is shown through entropy and chi-square analysis.
Å°¿öµå(Keyword) °ø°ú´ëÇÐ ¿©´ë»ý   ÄÄÇ»ÅÍ°øÇÐ ±³À°   Áø·ÎÁöµµ °¡À̵å¶óÀΠ  Female Students in Engineering College   Education on Computer Engineering   Guideline for Career Guidance   ·£¼¶¿þ¾î   ÀüÆÄ °¨Áö ½Ã½ºÅÛ   ¼Ò¼È ºòµ¥ÀÌÅÍ ¸¶ÀÌ´×   ¿£Æ®·ÎÇÇ   Ä«ÀÌ-½ºÄù¾î   Ransomware   Infection Detection System   Social Big Data Mining   Entropy   Chi-Square  
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