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Current Result Document :

ÇѱÛÁ¦¸ñ(Korean Title) MongoDB ±â¹ÝÀÇ ºÐ»ê ħÀÔŽÁö½Ã½ºÅÛ ¼º´É Æò°¡
¿µ¹®Á¦¸ñ(English Title) Evaluation of Distributed Intrusion Detection System Based on MongoDB
ÀúÀÚ(Author) HyoJoon Han   HyukHo Kim   Yangwoo Kim   ÇÑÈ¿ÁØ   ±èÇõÈ£   ±è¾ç¿ì  
¿ø¹®¼ö·Ïó(Citation) VOL 08 NO. 12 PP. 0287 ~ 0296 (2019. 12)
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(Korean Abstract)
IoT, Ŭ¶ó¿ìµå ÄÄÇ»Æðú °°Àº ÀÎÅÍ³Ý ¼­ºñ½ºÀÇ ¹ßÀü°ú »ç¿ë·®ÀÇ Áõ°¡·Î ÀÎÇØ ¼ö¸¹Àº ÆÐŶµéÀÌ ÀÎÅͳݻ󿡼­ ºü¸£°Ô »ý¼ºµÇ°í ÀÖ´Ù. ¾ÈÀüÇÑ ÀÎÅÍ³Ý »ç¿ë ȯ°æÀ» ¸¸µé±â À§Çؼ­´Â ÀÌ ¼ö¸¹Àº ÆÐŶ Áß¿¡ Á¸ÀçÇÒ ¼ö ÀÖ´Â ¾Ç¼º µ¥ÀÌÅÍÀÇ ºü¸¥ 󸮰¡ ÀÌ·ïÁ®¾ß ÇÑ´Ù. º» ³í¹®¿¡¼­´Â ºòµ¥ÀÌÅÍ º¸¾È À̺¥Æ®ÀÇ ½Å¼ÓÇÑ Ã³¸®¸¦ À§ÇØ ºñÁ¤Çü µ¥ÀÌÅÍ ºÐ¼®°ú ºòµ¥ÀÌÅÍ Ã³¸®¿¡ ƯȭµÈ MongoDB¸¦ ħÀÔŽÁö½Ã½ºÅÛ¿¡ Àû¿ëÇÏ¿´´Ù. ¶ÇÇÑ º¸È£ ´ë»óÀÎ »ç¼³ Ŭ¶ó¿ìµåÀÇ ÀϺΠÀÚ¿øÀ» ÀÌ¿ëÇÏ¿© ħÀÔŽÁö½Ã½ºÅÛÀ» ±¸ÃàÇÔÀ¸·Î½á Áõ°¡ ¶Ç´Â °¨¼ÒÇÏ´Â º¸¾È À̺¥Æ® ¼ö¿¡ µû¶ó ź·ÂÀûÀ¸·Î ÄÄÇ»Æà ÀÚ¿ø À籸¼ºÀÌ °¡´ÉÇϵµ·Ï ÇÏ¿´´Ù. º» ³í¹®¿¡¼­ Á¦¾ÈÇÏ´Â MongoDB ±â¹Ý ħÀÔŽÁö½Ã½ºÅÛÀÇ ¼º´ÉÀ» Æò°¡Çϱâ À§ÇÏ¿© MongoDB ±â¹ÝÀÇ Ä§ÀÔŽÁö½Ã½ºÅÛ°ú ±âÁ¸ÀÇ °ü°èÇü µ¥ÀÌÅͺ£À̽º¸¦ ±â¹ÝÀ¸·Î ÇÑ Ä§ÀÔŽÁö½Ã½ºÅÛÀÇ ÇÁ·ÎÅäŸÀÔÀ» ±¸ÃàÇÏ°í ¼º´ÉÀ» ºñ±³ÇÏ¿´´Ù. ¶ÇÇÑ ºÐ»êÈ­ ±¸¼º¿¡ µû¸¥ ¼º´É º¯È­¸¦ È®ÀÎÇϱâ À§ÇÏ¿© °¡»ó¸Ó½ÅÀÇ ¼ö¸¦ º¯°æÇÏ¸ç ¼º´É º¯È­¸¦ È®ÀÎÇÏ¿´´Ù. ±× °á°ú ÀüüÀûÀ¸·Î MongoDB ȯ°æ¿¡¼­ µ¿ÀÏÇÑ ¼º´ÉÀÇ ½Ã½ºÅÛÀ» ºÐ»êÈ­½ÃÄÑ °¡»ó ¸Ó½ÅÀÇ ¼ö¸¦ Áõ°¡½Ãų¼ö·Ï ħÀÔŽÁö½Ã½ºÅÛÀÇ ¼º´ÉÀÌ Çâ»óµÇ´Â °ÍÀ» È®ÀÎÇÏ¿´´Ù. ºÐ»ê MongoDB ±â¹ÝÀÇ º¸¾È À̺¥Æ® ÀúÀå ¼Óµµ°¡ °ü°èÇü µ¥ÀÌÅͺ£À̽º ±â¹Ý¿¡ ºñÇØ ÃÖ´ë 60%, ±×¸®°í ºÐ»ê MongoDB ±â¹ÝÀÇ Ä§ÀÔ µ¥ÀÌÅÍ Å½Áö ¼Óµµ°¡ °ü°èÇü µ¥ÀÌÅͺ£À̽º ±â¹Ý¿¡ ºñÇØ ÃÖ´ë 100% ºü¸¥ °á°ú¸¦ ¾ò¾ú´Ù.
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(English Abstract)
Due to the development and increased usage of Internet services such as IoT and cloud computing, a large number of packets are being generated on the Internet. In order to create a safe Internet environment, malicious data that may exist among these packets must be processed and detected quickly. In this paper, we apply MongoDB, which is specialized for unstructured data analysis and big data processing, to intrusion detection system for rapid processing of big data security events. In addition, building the intrusion detection system(IDS) using some of the private cloud resources which is the target of protection, elastic and dynamic reconfiguration of the IDS is made possible as the number of security events increase or decrease. In order to evaluate the performance of MongoDB – based IDS proposed in this paper, we constructed prototype systems of IDS based on MongoDB as well as existing relational database, and compared their performance. Moreover, the number of virtual machine has been increased to find out the performance change as the IDS is distributed. As a result, it is shown that the performance is improved as the number of virtual machine is increased to make IDS distributed in MongoDB environment but keeping the overall system performance unchanged. The security event input rate based on distributed MongoDB was faster as much as 60%, and distributed MongoDB-based intrusion detection rate was faster up to 100% comparing to the IDS based on relational database.
Å°¿öµå(Keyword) Big Data   Intrusion Dectection System   Cloud Computing   Distributed Processing   ºòµ¥ÀÌÅÍ   ħÀÔŽÁö½Ã½ºÅÛ   MongoDB   Ŭ¶ó¿ìµå ÄÄÇ»Æà  ºÐ»ê 󸮠 
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