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Current Result Document :

ÇѱÛÁ¦¸ñ(Korean Title) ¸ð¹ÙÀÏ È¯°æ¿¡ ÀûÇÕÇÑ DNN ±â¹ÝÀÇ ¾Ç¼º ¾Û ŽÁö ¹æ¹ý¿¡ °üÇÑ ¿¬±¸
¿µ¹®Á¦¸ñ(English Title) Study on DNN Based Android Malware Detection Method for Mobile Environment
ÀúÀÚ(Author) À¯ÁøÇö   ¼­ÀÎÇõ   ±è½ÂÁÖ   Jinhyun Yu   In Hyuk Seo   Seungjoo Kim  
¿ø¹®¼ö·Ïó(Citation) VOL 06 NO. 03 PP. 0159 ~ 0168 (2017. 03)
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(Korean Abstract)
½º¸¶Æ®Æù »ç¿ëÀÚ°¡ Áõ°¡ÇÏ°í ½º¸¶Æ®ÆùÀÌ ´Ù¾çÇÑ ¼­ºñ½º¿Í ÇÔ²² ÀÏ»ó»ýÈ°¿¡¼­ ³Î¸® »ç¿ëµÊ¿¡ µû¶ó ½º¸¶Æ®Æù »ç¿ëÀÚ¸¦ ³ë¸®´Â ¾Ç¼ºÄÚµå ¶ÇÇÑ Áõ°¡ÇÏ°í ÀÖ´Ù. ¾Èµå·ÎÀ̵å´Â 2012³â ÀÌÈÄ·Î °¡Àå ¸¹ÀÌ »ç¿ëµÇ°í ÀÖ´Â ½º¸¶Æ®Æù ¿î¿µÃ¼Á¦ÀÌÁö¸¸, ¾Èµå·ÎÀÌµå ¸¶ÄÏÀÇ °³¹æ¼ºÀ¸·Î ÀÎÇØ ¼ö¸¹Àº ¾Ç¼º ¾ÛÀÌ ¸¶ÄÏ¿¡ Á¸ÀçÇÏ¸ç »ç¿ëÀÚ¿¡°Ô À§ÇùÀÌ µÇ°í ÀÖ´Ù. ÇöÀç ´ëºÎºÐÀÇ ¾Èµå·ÎÀÌµå ¾Ç¼º ¾Û ŽÁö ÇÁ·Î±×·¥ÀÌ »ç¿ëÇÏ´Â ±ÔÄ¢ ±â¹ÝÀÇ Å½Áö ¹æ¹ýÀº ½±°Ô ¿ìȸ°¡ °¡´ÉÇÒ »Ó¸¸ ¾Æ´Ï¶ó, »õ·Î¿î ¾Ç¼º ¾Û¿¡ ´ëÇؼ­´Â ´ëÀÀÀÌ ¾î·Æ´Ù´Â ¹®Á¦°¡ Á¸ÀçÇÑ´Ù. º» ³í¹®¿¡¼­´Â ¾ÛÀÇ Á¤ÀûºÐ¼®°ú µö·¯´×À» °áÇÕÇÏ¿© ½º¸¶Æ®Æù¿¡¼­ Á÷Á¢ ¾Ç¼º ¾ÛÀ» ŽÁöÇÒ ¼ö ÀÖ´Â ¹æ¹ýÀ» Á¦¾ÈÇÑ´Ù. ¼öÁýÇÑ 6,120°³ÀÇ ¾Ç¼º ¾Û°ú 7,000°³ÀÇ Á¤»ó ¾Û µ¥ÀÌÅÍ ¼ÂÀ» °¡Áö°í Á¦¾ÈÇÏ´Â ¹æ¹ýÀ» Æò°¡ÇÑ °á°ú 98.05%ÀÇ Á¤È®µµ·Î ¾Ç¼º ¾Û°ú Á¤»ó ¾ÛÀ» ºÐ·ùÇÏ¿´°í, ÇнÀÇÏÁö ¾ÊÀº ¾Ç¼º ¾Û Æйи®ÀÇ Å½Áö¿¡¼­µµ ÁÁÀº ¼º´ÉÀ» º¸¿´À¸¸ç, ½º¸¶Æ®Æù ȯ°æ¿¡¼­ Æò±Õ 10ÃÊ ³»¿Ü·Î ºÐ¼®À» ¼öÇàÇÏ¿´´Ù.
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(English Abstract)
Smartphone malware has increased because Smartphone users has increased and smartphones are widely used in everyday life. Since 2012, Android has been the most mobile operating system. Owing to the open nature of Android, countless malware are in Android markets that seriously threaten Android security. Most of Android malware detection program does not detect malware to which bypass techniques apply and also does not detect unknown malware. In this paper, we propose lightweight method for detection of Android malware using static analysis and deep learning techniques. For experiments we crawl 7,000 apps from the Google Play Store and collect 6,120 malwares. The result show that proposed method can achieve 98.05% detection accuracy. Also, proposed method can detect about unknown malware families with good performance. On smartphones, the method requires 10 seconds for an analysis on average.
Å°¿öµå(Keyword) ½º¸¶Æ®Æù   ¾Èµå·ÎÀ̵堠 ¾Ç¼º ¾Û ŽÁö   µö·¯´×   Smartphone   Android   Malware Detection   Deep Learning  
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