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Voice phishing prevention application through real-time voice call analysis : 실시간 통화내용 분석을 통한 보이스피싱 예방 애플리케이션 제안보고서
- 2 -
목 차
[ ]
!"#$%&'%(%)*+%
1. (Background and Significance)
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5. (The Role of Researchers)
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6. (Reference)
표
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그림
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[ 6] Overall pre-training and fine-tuning procedures for BERT
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- 3 -
프로젝트 제안서
1. !"#$%&'%(%)*+%(Background and Significance)
,. -./%01%!"#$%23
ijklm 7% •X–% lm —}% ˜p™š; lm
(voice-phishing) (phishing) .
s?›% y‹% œ•% Šž% #ƒOiŸ% ¡¢£; ¤% 7¥`% #ƒOi
‘ ’ (private
¦% v •% §+¨% ©d•j; ijklm–% lmj>¤% ª•%%
data) (fishing) .
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(voice) . ,
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2016
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17,040 1,468 , 2020
$p»c¤% » º% lž†¼% ½X²`% ¹f% ¿±% $p»c¤%
31,681 , 7,000 5
lž†¼–% À,Á;%
85.9%, 376.8% [2].
표 국내 보이스피싱 범죄의 발생 현황
[ 1]
연 도 총 발생건수 총 피해금액
2016 »
17,040 ½X
1,468
2017 »
24,259 ½X
2,470
2018 »
34,312 ½X
4,040
2019 »
37,667 ½X
6,398
2020 »
31,181 ½X
7,000
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- 6 -
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- 7 -
항목
번호
선행 연구개발의 문제점 개선 목표 및 관련 세부과제
1
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표 선행 연구개발의 문제점 및 개선 목표 요약
[ 2] ( )
- 8 -
3
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4. FG<9H%!"#$%BC%
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- 10 -
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- 11 -
3. !"#$%.K%(%LM%(Research Design and Method)
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- 13 -
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[ 5] [12]
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- 16 -
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- 17 -
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[ 8]
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- 23 -
4. _`ab%c6%de
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[ 8]
- 24 -
6. Vg8h%(Reference)
[ 1 ] ƒK
https://www.fss.or.kr/fss/main/contents.do?menuNo=200354, 2022.03.23.
[ 2 ƒK
] https://www.data.go.kr/data/15063815/fileData.do, 2022.03.23.
[ 3 ž+ Ã@'% ijklm7% uL<% @ù÷1•% ì¨% !" ¨-Óss%%
] (2009). .
・
Où!"X.
[ 4 ] j?c Dã%ijklm7%nocM%23<%M±%@ÕLü nocs•!"
(2018). . ,
7, pp3-19.
[ 5 í+Q lm%s?no—%@¨%ƒ„h%(%-,H%@ÕOù%Þî!" 'l•
] (2019). .
%º, 14(1), pp101-130.
[ 6 ] Og– vEÝ wÂ? x€±b€ÜŸ%±K¨%ijklm%sÇ]È sÎô••
, , (2017). :
)x²` sÎ<•!"
. , 28(4), pp181-194.
[ 7 ] vïX ?y7%Úvf%ijklm k¥m%LË%vn%}Þk Žj„
(2020). AI . 2020
・
•Ýw„%sÇJ, pp64-73.
[ 8 vwO v–¥ ijklm% lž% '”% (% E3*ƒ% ]È XÞQ89!"
] (2021). . ,
・
52(1), pp52-71.
[ 9 ƒK
] https://www.boannews.com/media/view.asp?idx=100557, 2022.03.23.
[10] https://www.donga.com/news/Society/article/all/20220105/111095788/1,
ƒK
2022.03.23.
[11] https://github.com/SKTBrain/KoBERT ƒK
, 2022.04.05.
[12] https://www.fss.or.kr/fss/bbs/B0000207/list.do?menuNo=200691, 2022.04.04.
ƒK
[13] https://konlpy.org/en/latest/ ƒK
, 2022.04.05.
[14] https://github.com/hyunwoongko/kss ƒK
, 2022.04.05.
[15] https://github.com/ssut/py-hanspell ƒK
, 2022.04.05.
[16] https://github.com/lovit/soynlp ƒK
, 2022.04.05.
[17] Jacob Devlin, Ming-Wei Chang, Kenton Lee, Kristina Toutanova(2019). BERT:
Pre-training of Deep Bidirectional Transformers for Language
Understanding. NAACL-HLT (1) 2019, pp4171-4186.
[18] https://www.skt.ai/kr/press/detail.do?seq=27 ƒK
, 2022.04.05.
[19] https://gbpolice-preventphishing.kr/ ƒK
, 2022.04.05.

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Voice phishing prevention application through real-time voice call analysis : 실시간 통화내용 분석을 통한 보이스피싱 예방 애플리케이션 제안보고서

  • 2. - 2 - 목 차 [ ] !"#$%&'%(%)*+% 1. (Background and Significance) , -./%01%!"#$%23 . 4 56%!"#$7%89:% . ; !"#$%<97% . =*+%( )*+% > ?@A< . !"#$%BC% 2. (Specific Aims) , DE%BC%%% . 4 FG<9H%!"#$%BC . ; ?I#$%BC . > BC%@J . !"#$%.K%(%LM% 3. (Research Design and Method) , !"#$%.K . 4 !"#$%LM . ; !"#$%NO . PK%?QR%(%RS% 4. (Equipment Required) , #* . 4 PKTU%(%?@A<%% . VW!"X%YZ%(%[]^% 5. (The Role of Researchers) , VW!"X%YZ . 4 _`ab%c6%de%% . ; VW!"X%f%[]^ . Vg8h% 6. (Reference) 표 C [ -.%ijklm%no7%$p%YZ 1] C% 56%!"#$7%89:%(%#5%BC *q [ 2] ( ) C% FG<9H%BC *q [ 3] ( ) C% "Y%rBH%FGsr [ 4] C% t8ds%uv [ 5] C% FG<9H%!"#$%NO% [ 6] C% VW!"X%YZ [ 7] C% VW!"X%f%[]^%. [ 8] [ 그림 wx% yz%!"<97%"d{ [ 1] wx% [ 2] DFD (Data Flow Diagram) wx% |}{ [ 3] wx% ~•€•j‚%sKQ%ƒ„…jk [ 4] wx% †‡ˆ‰X%ijklm%no%Š‹%Œ•%Žj„• [ 5] wx% [ 6] Overall pre-training and fine-tuning procedures for BERT wx% 7%•‘%’< [ 7] KoBERT wx% ijklm%no%v4€“%z”%"d{ [ 8] wx% _`ab%c6%de{ [ 9]
  • 3. - 3 - 프로젝트 제안서 1. !"#$%&'%(%)*+%(Background and Significance) ,. -./%01%!"#$%23 ijklm 7% •X–% lm —}% ˜p™š; lm (voice-phishing) (phishing) . s?›% y‹% œ•% Šž% #ƒOiŸ% ¡¢£; ¤% 7¥`% #ƒOi ‘ ’ (private ¦% v •% §+¨% ©d•j; ijklm–% lmj>¤% ª•%% data) (fishing) . «—%•+ 7%7¥,%¬,-%®j; ¯ ijklm–%yQŠ©cª%)% (voice) . , y‹Ÿ% Šž% °M±²`% #ƒOiŸ% jK³W% †y±% j´•% µ³¤% noŸ%% 7¥¨;%[1]. ijklm% no7% lž% YZ•% ¶·i¸% ¹% -.% ijklm% no7%% 2016 º% $p»c¤% »²`% º% lž†¼–% ½X—% ¾³g ¹% º%% 17,040 1,468 , 2020 $p»c¤% » º% lž†¼% ½X²`% ¹f% ¿±% $p»c¤% 31,681 , 7,000 5 lž†¼–% À,Á;% 85.9%, 376.8% [2]. 표 국내 보이스피싱 범죄의 발생 현황 [ 1] 연 도 총 발생건수 총 피해금액 2016 » 17,040 ½X 1,468 2017 » 24,259 ½X 2,470 2018 » 34,312 ½X 4,040 2019 » 37,667 ½X 6,398 2020 » 31,181 ½X 7,000 ijklm%no¦%01¨%56!"Ÿ%¶·i¸ ž+ Ã@'–%Ä€4>¦% , · @Å NÆ ¥-7%ijklm%sÇŸ%]ȳÉ; ]È’< NÆ7%sÇ—}¤% · · . , ¯Ê±ƒ%†‡OËvkÌ%"Í%(%lžQ%lžÎÏ%vkÌ7%=*+• @Å7% , sÇ—}¤%-,±%uL?07%©t%(%uLM7%=*+• ¥-7%sÇ—}¤% , ijklm%ÐÅ%¡Ñ>%Òs¨%ÓÔ7%no—%@ž%@Õ³¤%?07%=*+• Öd³É; ¨-7% 'Ä% M×± 9{± . · ·?I±% ظ7% 89:•% ˱³É;. M×±%ÙX—}%†‡ÚÛÜÝ%(%Þß%ià—%0¨%M×%#O GOTá%Ëâ% , OË% 9{7% M×±% ãÜ% Ö‹ /-äÜÝMJ% °M% å†% æç% ãÜ% Ö‹ , , -9%y‹†‡s?%æç—%0¨%èHM%9O%œ%ijklm%noŸ%éO³¤%% 01Mê—% @¨% #Oj% =*³g% 9{±% ÙX—}¤% y^% cs?"7% ë9, lžuL•% ì¨% íi% (% îï èð ñƒò• ( , @J²`% ¨% îï_`wó7%%%% Úv -9%ôdcsz9%õö ijklm<%01-%-9Mé%÷1 #ƒOi ), , ,
  • 4. - 4 - iø%@ù%÷1%œ%ijklm%no7%uL%(%cs—%@¨%zT±%9{¦%no lžŸ% ÎÏ% c% ú¤% 9{,% =*³û% ?I± ÙX—}¤% OiŠ©?I<%%% iüzT%õö å†%v%•+ý8Q%þx%}Þk%% , õ@ ÿj“pz%ƒ!•%Š¨ , å†%Ùª "ÿN%#$<%ƒ„%%#$7%iüd& , Ö‹ •%Š¨%Ùª%œ7% , VPN LM•%PK³W%?I±ƒ%GR`%ƒ³W%$p³¤ ijklm%noŸ%uL³g% cs³?%ì¨%ñ'j%=*³;g%(à³É;%[3]. j?c¤%Dã%ijklm7%nocM%23<%M±%@ÕLü•%]ȳû%M± #5Lü•%")³É; ijklm7%nocM7%Ë*‹¦%+‹—{%°"³g% . j¥%Ê%ªTH%6ìê•%æç%c%ú¤%éOêj%,R³û%01%Ó-{%,.Ë /?% 08—% 1`2% "+*»7% ©t–% =*³Ë% /;g% (à³É; w34% . noc4% –57% é9% (% æç% œ—% 0¨% M× J% )@no 67% WG¦%% ‘ ’ 「 」 @6Šà%9ô%œ%Ldn%æç7%Ö‹%WGŸ%89%=*,%ú;g%˱³É;. Åq%ijklm%no6ì—%@¨%æç<%7:%noc47%;c<Ë%j=•> ;¸%nouL—%?@%?W%c%ú; jŸ%ìž}%ijklm%noQêj%Ó . MJ% noªz—% žA¨;g% B% c% ú•% O{7% de•% "+³É;¤% :•%%% CÀžD³4%:de²`%2E™¤%ijklm%no%è+²`%ƒž%j¤%FË% /; 8>}%ijklm%noŸ%noc4–57%é9%(%æç%œ—%0¨%M×% . 9 d7% )@no —% 67vG% ijklm7% noc4—% @¨% ;c,% ,*%% 2 ‘ ’ ³{H% žD% ¨;g% (à³É; I @6Šà% "Jù% œ7% Ldn7% 'Ä%%% . , -.—}% KÜ™L>{% ijklm% noƒË% ;M;g% Gƒ% 'Ä% no7%%% g7Ÿ%ƒO³?%•NO%ôn+j%ƒO™Ë%/•%c%ú?%08—%no7%g7% WG—%0TPj%æç•%Ö‹³WD%¨;g%(à³É;%[4]. í+Q–%RSTU<%˜Äkb ,%9v¨%no%uL%% (Brantingham & Faust) ªT%"V•%±K³W%W3%4>7%lm%no%uL@ù•%]ȳû%¡Ý%W%,Ë 3 *XŸ% Öd³É; YZ ªTH . , uL% zT‹Ÿ% Öd³É; ijklm% œ%%% . D©%lmsÇŸ%[…jË4%]i{Ÿ%Šž%íi³W%(7³{H%³g%lm no,%$pÁ•%0%@æ%c%ú{H%Y†Ëâ?4%–6%œ%†‡?0j%^" —}%no6ì%lžQ,%;¼Y†•%ƒ_³Ü4%决N%%0%`%L%±a±²` ijklm%œ%lm%lžQ,%¡bË%õƒ³¤%cÙŸ%def‹%³¤%LM I¤ , )²`% õƒ³¤% Lü{% gNžD³û% ž/—% ú¤% 2 noQ—% @¨% cs,%%% ©g³@%j=•9%c%ú{H%ƒ„h<7% i' jj4> , )- =€k @Å%% , , œ7%'l%f%em±%OiôÒŸ%³g ô2@Õ•%ì¨%Î74%-9%F¥4Ÿ% , #D³W%Jøi'•%9gžD¨;g%(à³É; nZ MJ6?0%/7%0T . , ?0{%lžuL•%ì¨%ñ'•%žD¨;g%Öd³É; NÆ7%'Ä%Q&ªz . <Ë% 4}}% ijklm% œ% lm% uL—% 4}g% ú¤Ž% vo7% ñƒêj%%%%% s?Ÿ%A³¤%'Ä—%jæp%Q&ªzŸ%Š¨%uL*q<%©gLM•%îï%(% íi³¤%®j%A<±N ®%j>g%(à³É; •Z ž/%noƒ%åä%i'% . , Ö‹Ÿ%Öd³É; ¨-7%%'Ä%)-%œ%jj4>—%rs„,%úg%¨-ƒ•% . @J²`% ¨% lmj% tj% $p³g% ú?% 08—% -9±% ôdcs¦% noƒ%%% åäP2j% )*³;g% (à³É; %Z lžÎÏ% ñ'% 9gŸ% Öd³É; . , . lm7%è+j%-9±jg lžÎÏj%•NO%lm%no7%ãÆXƒ•%9ܳ¤% ®•% DÄ5% <9`% Q¡D ³4% no% R$L˦% 7:% lžÎÏ•% ì¨%%%%% ñ'{%u6³WD%¨;g%(à³É;%[5]. Og– vEÝ wÂ?¤%ijklm<% ,%9ü¨%x€±%b€Ü¦7 · · Gragg(2003) !0+•%!"³É; ?I±ƒ%q:•%aϳ¤%®<%¾€%ƒf?y%sÎô•% .
  • 5. - 5 - ôz•%ˆË³g%uL³¤%®–%{Ä%•|g%x€±ƒ%}q:–%?I±%ظj% i~-%JZ—}{%ƒf%62—%Ëg±ƒ%E3•%¥•%c%ú?%08—%ijk% lm—%@¨%?I±%ظ7%!"ÐÅ%¡Ñ>%x€± }q:—%@¨%!"Ÿ%Šž% ƒf?y%sÎô•%ôz•%uL³¤%®{%)*³;g%(à³É;%[6]. ijklm%no7%?I±%uL<%01¨%#$%sÇŸ%¶·i¸ €€•‚ƒÑ¤ , ¹%<?OŠG7% Žj„%•Ýw„%s… ËX•%†¡% ?y7%Úvf% 2020 ' ' AI ijklm k¥m%LË%vn}ÞkŸ%#$Á; Š© †‡ cs‡—%¿±-% , . , , ijklm k¥m% œ7% y?Š©†‡s?% OiŸ% PK³W% ijklm%%%%% , s?n7%BX€Ÿ% Ÿ%Šž%ˆH³¤%?I•%#$³É;% AI [7]. ijklm%no7%uLîï<%01¨%!"%sÇŸ%¶·i¸ vwO v–¥¤ , · +ƒ% ‰Š% Û•% @J²`% Úv¨% ¹<Ë7% ‹Œ•QQdsŸ% 7,590 2017~2019 ÿŽ²`%ijklm%lž%'”<%E3*ƒ•%!"³É; ]È%’<%†‡%s? . uL% îï•% †Ë% /–% Jªi;% †–% Jª—}% ijklm% lžŸ% "¸%%% õ×j% O±²`% Ò7¨% E3•% ij¤% ®•% ãÜ`% †‡s?% îï% WG¦%%% ijklm%01%'”j%!0+j%ú••%••; ’]±²`%ijklm%uL• . ìž% x‹% R‘Ë!•% ’jg% †‡s?% uLîï7% 9± “±% 9g,% =*%% , ³;¤%vs:•%{_³É;%[8]. 4. 56%!"#$7%89:% ijklm%uL7%)*+–%Tgž}%Öd™g%úËŠˆ<Ë7%56%% , !"—}¤%ijklm7%#”<%no%cM% ijklm%lž%sÇ%œ—%% [4], 0¨%]È% ijklm%uL•%ì¨%M×±%•–%9{±%@ÕLü% œ• [8], [5] (`%9vž%–; ijklm%no%uL•%ì¨%?I±%ž’LM%(%uL% . îï±%0:—%0¨%!"¤%Þî±%P$ð%j=•ËË%/g%úš;. ijklm%no%uL%?I•%"Y¨%@C±%sÇ% ¤%Š‹.K%]È•%% [7] Š¨%ijklm%—Ë%?*•%):²`%#$™•%ijklm%Š‹Ÿ%—˳g, jŸ%ˆË%'Ä%sKQ—@%þx•%y峤%®j%(*¨%?*j; ijk . lm%no%uL•%ìž}¤%ijklm•%?I±²`%—˳g%sKQ—@%% ƒË%c%ú{H%³¤%®{%)*³ËÅ sKQ%kk`%ijklm%WGŸ%% , ˆª% c% ú¤% *'•% ˜3(¤% uL% îï% I¨% )*³;% ³ËÅ% ?%%% [8]. #$-%}Þk—¤%ijklm%no%uL%îï<%01¨%?*j%,R³Ë%/¤;. I¨ ,™%(%˃•%sš³Ü4%›&Ÿ%œQ¨%ijklm%no7%'Ä , , ,™<% ˃—@% jŸ% ©g³@% ôÒ³W% ¬,±ƒ% lž% õ••% L˳¤% ®j%)*³; ?%#$-%}Þk% —}{%ijklm%7x%Š‹7%Œ•% . [7] ?*•%9ô³g¤%úËÅ Œ•-%˜N•%ôÒ³?%•|g%,™%(%˃%œ , X³¤%sžê—@%¨%Ÿ—%ôÒ%c%ú¤%?*–%9ô³Ë%/g%ú;. 8>}%Æ%!"—}¤%Ú9%ijklm%no%Š‹7%Œ}%Žj„Ÿ%ÿŽ²` ijklm%WGŸ%ˆH%c%ú¤%ƒôË*%"V%(%~•€•j‚•%#$ ³¤%¨ë ijklm%no%uL%îï%(%ijklm%7x%Š‹%.K—%@¨% , ôÒ%?*• #$³gQ%¨;. ;. !"#$%<97%=*+%(%)*+ -Î% O‘ìXÎ% Ò2c% 7X ƒ % T“¡ j% ¹% 'l¢²`G„% †–% ( ) 2021 QS—% 8£¸% ijklm% no`% ƒ¨% lž¤% ˤ% ¹f% Å% » 10 23 3,287 ,
  • 6. - 6 - lž¼–% d% ½X—% ¾¨;% ijklm% no,% (`% ñ¹ò•%%%%% 3 2,333 [9]. @J²`%Q¥¦%<ܦ¤%¾€%Dã—¤% @Ÿ%@J²`%¨%ijklm%lž 20 I¨%§%¨²`%À,³g%ú;% ‰ŠñXŸ%,€Ë%/g%$p³¤%ijk [10]. lm%no,%sα%89`%@©™û%ijklm%uL—%@¨%-w±%0x%I¨ À,³g%ú; Æ%!"—}%#$³¤%ƒôË*%"V%(%~•€•j‚–%ijk . lm%no%uL%(%ž’—%{ª•%«%c%ú•%®j;. >. ?@A< Æ% !"7% ’<¬`% 9-™¤% ijklm% uL% ~•€•j‚•% jK³¸, sKQ,%ijklm%WGŸ%ˆª³Ë%®³¤%JZ—}{%ƒôË*%"Vj%Š‹ .K•%Úvf²`%]ȳW%~•€•j‚•%Šž%þx•%9ô³?%08— ijk lm%JZ•%ƒË%c%ú; jŸ%Šž%ijklm%y‹,%Ú9%no%lž`% . j•Ë¤% ®•% ¯•% c% úg ~•€•j‚—}% 9ô³¤% ijklm% no%%% , uL%îï%?*•%Šž%sKQ%kk`%ijklm%uLM<%@æLM•%•‘³W ?I±% ¨T`% ƒž% ~•€•j‚—}% ijklm•% !H³Ë% ®³¤% JZ%%% —}{% sKQ% kk`% ijklm•% ƒË³g% lžŸ% uL% c% ú; I¨%% . ijklm%Š‹%.K%ôÒ%?*•%Šž%,™j4%˃%œ•%sš¨%ijklm y‹Ÿ%†–%'Ä%Š‹%.K•%(+ƒê—@%©g³@%yå³W%¬,%lžŸ% ¯•%c%úg 'l%œ%Ò0?0²`%©g¨%©g%(%Š‹%.K%ôÒ,%,*³; , . 2. !"#$%BC%(Specific Aims) ,. DE%BC Æ%!"—}¤%JI¨%56%!"#$—}7%89:•%i~³W%ijklm•% —Ë%c%ú¤%ƒôË*%"V<%jŸ%±K¨%ijklm%—Ë%~•€•j‚•% #$¨; ~•€•j‚–%ƒôË*%"V•%sK³W%sKQ7%Š‹Ÿ%Úvf . ²`%]ȳg ƒôË*%"V—}%ijklm•%—˳É;¸ ~•€•j‚– , , sKQ—@%Š‹%ESŸ%Ò{³¤%þx•%yå¨; Š‹,%ES-%'Ä%(+ . ƒ—@% Š‹% .K•% ôÒ% ®ƒË% ¬•i¤% °…•% $pv±; jŸ% Šž%% . ,™%(%˃%œ•%sš¨%ijk²%no—%@ž%¬,%lžŸ%ˆXv³%c%ú;. ~•€•j‚— ´R-%ijklm%no%uL%îï%?*–%sKQ%ÒÓ%]È% ’<Ÿ%ÿŽ²`%ijklm%no%v4€“%z” ijklm%no%Š‹%z” , , ijklm%no%@æ%LM%µ¶ ijklm%nouL%·¸¹ 2EJ º» , ( , ) œ% ;“¨%îï%QSŸ%9ô¨; sKQ¤%~•€•j‚—}%9ô³¤%ijk . lm% uL%îï%?*•%Šž%ijklm%no%uL%(%@æ%LM•%•‘%c%ú;.
  • 7. - 7 - 항목 번호 선행 연구개발의 문제점 개선 목표 및 관련 세부과제 1 ijklm%lž%sÇ%(% ŠT%]È%01%.K%ì(% [3][4][5] #5%BC 1. ijklm% Š‹Ÿ% ˆH% c% ú¤% ƒôË*% "V% (% ~•€ •j‚•%#$¨;. FG%<9 2. ,. ijklm%no%Š‹%Œ• Žj„•%cJ 4 ijklm% no% Š‹Ÿ% . ˆH%c%ú¤%ƒôË*% "V%#$% ; Úvf²`% Š‹% .K•% . }¼`% y峤% ~•€ •j‚%#$ 2 ijklm%no uLîï%?*7%GR%[7][8] #5%BC 1. sKQ,%ijklm•%kk`% ƒË³g% uL% c% ú{H%%% ijklm% uL% îï% ·¸¹ µ¶ v4€“%z” Š‹%z ( , , ” º»% (% 2EJ% QS Ÿ , ) 9ô³¤%~•€•j‚•%#$ ¨;. FG%<9 2. ,. •‘Q%½¾Ó%îï•%ì¨ sKQ%ÒÓ%]È%?*%#$ 4 ijklm%no%v4€“% . z”%?*%#$ ;. ijklm%no%Š‹%z” ?*%#$ >. ijklm%no%@æ%LM µ¶%?*%#$ ÷. ijklm%uL%·¸¹º» ( , 2EJ%œ 9ô%?*%#$ ) 표 선행 연구개발의 문제점 및 개선 목표 요약 [ 2] ( )
  • 8. - 8 - 3 ijklm%Š‹%Œ•%˜N• (+ƒ<%ôÒ³?%•Nª%[8] #5%BC 1. ,™% (% ˃% œ•% sš¨%%% ijklm% y‹Ÿ% †–% 'Ä% Š‹%.K•%Fg%¿£@%ôÒ %c%ú¤%?*%#$ FG%<9 2. ,. Š‹ Œ••%ôÒ%wÀ• p+³g%0€³¤%?*%#$ 4. Š‹%Œ•%˜N•%¥€%ËO¨ wÀH`%ÁF@%ôÒ%c ú¤%?*%#$ 4. 'l% œ% Ò0?0—@% Š‹%% Œ•% ˜N• ¿£@% 9ô% c ú¤%?* #$
  • 9. - 9 - 4. FG<9H%!"#$%BC% 세 부 과 제 목 표 ijklm%•+% Žj„•%cJ • Â%jJ%•+˜N% »%jJ%cJ 60 400 ijklm%—Ë% ƒôË*%"V%#$ • ˆH%Oõ{% jJ 70% • Š‹%v-%€% Â%j.%ˆË 120 ijklm%uL% ~•€•j‚%#$ • Ãw>2Œ%Ú6%)%y‹%c©%v%Q2²`%P+‹ ijklm%uL% îï%·¸¹%9ô • sKQ%ÒÓ%]È•%Š¨%½¾Ó%îï%9ô • ijklm%no%v4€“%z”%?*%9ô • ijklm%no%Š‹%z”%?*%9ô • ijklm%no%@æ%LM%µ¶%9ô • ijklm%no%uL%îïQS º» 2EJ%œ 9ô ( , ) Š‹%Œ• ôÒ%?* • ,™ ăŠ˃%œ%wÀ%tO%?*%ËX , , • ijklm% 7x% Š‹% ES% €% X³¤% wÀ²`%%% ¨Ÿ—%ôÒ³¤%?*%#$ • ijklm% 7x% Š‹% ES% €% Ò0?0²`7%%%% ôÒ%(%©g¨%©g%?*%#$ 표 세부과제별 목표 요약 [ 3] ( ) ;. ?I#$%BC Æ% !"—}¤% ijklm% Š‹Ÿ% —Ë% c% ú¤% ƒôË*% "V<%%%%%% 1) ijklm%uL%îï%·¸¹%(%Š‹%Œ•%ôÒ%?*•%9ô³¤%~•€•j‚• 2) #$¨; ~•€•j‚–%ÆJv%sKQ—@%ijklm%no%uL%îï%?*• . 9ô³g y‹%c©%v%Q2²`%P+‹™•%Š‹%.K•%Úvf²`%]ȳg , ijklm%WGŸ%ˆH³¤%®j%BCj;. J?-% ?*% "Y•% ì³W% Æ% !"—}¤% —}% #$¨% ¨-•% SK TBrain "V% ¦% †‡ˆ‰X—}% 9ô³¤% ijklm% no% sÇ%%% BERT KoBERT [11] Žj„•% •%?y²`%ijklm%—Ë%"V•%#$¨; [12] . Žj„•–% Ÿ% 7%ÞÇ`%]€ Train data, Validation data, Test data 6:2:2 ¨; ]€-%Žj„•%)% Ÿ% ¦% Ÿ%jK³W% . Train data KoNLPy [13] KSS [14] ¨; j€% •% jK³W% •M% “ÈŸ% cO³g Tokenizing . py-hanspell [15] , Ÿ% jK³W% O鋨; ì% <O•% Šž% y% æ€-% Žj„••% Soynlp [16] .
  • 10. - 10 - ¦% Ÿ%jK³W% ¨; "V7%Oõ{¤%Š‹%v-% PyTorch KoBERT Fine-tuning . € ]%j.% jJ%—ËŸ%BC`%¨; 2 70% . üŒ`jŒ%~•€•j‚–% •%sK³W%#$¨; ~•€•j‚–%Š‹ Kotlin . v Š‹%.K•%Úvf²`%É>ÄŒ%}¼—%yå³g }¼¤%j%Š‹.K•%]È , ³W%ijklm%WGŸ%ˆH¨; k÷bÊ—}%}¼<Ë7%Žj„%Š©–%ô#Ë . Ìø‹%L!• jK¨ Eª%f%Ìø‹Ÿ%±K¨;. ƒôË*%"V7%ˆH%’<%YR%Š‹,%ijklm²`%7x-;¸%sKQ —@%þx•%yå³W%Š‹%ESŸ%Ò{¨; Š‹%Œ•%ôÒ . ?*–%sKQ,% ijklm%7x%Š‹Ÿ%ES³¸, sKQ—@%L†%Š‹¨%Š‹%.K•%ôÒ% ®ƒË%¬•i¤%°…•%$pv±;. Š‹%.K•%ôÒ%wÀ–%~•€•j‚ —}%sy—%tO%,*³û, sKQ,%ôÒ%wÀ•%5ͳ¸%ÎΓÏ%dvËŸ jK³W%Š‹%Œ•%˜Nj ôÒ-;. ijklm%uL%îï%?*–%4j +H e…Е%ÿŽ²`%¨%sKQ%ÒÓ% , , ]È% ’<Ÿ% ÿŽ²`% •‘Q% ½¾Ó ijklm% uL% îï% ?*•% 9ô¨;. ijklm%v4€“% z” ijklm% Š‹%z” ijklm%no% @æ%LM%% , , µ¶ ijklm% uL% ·¸¹ º» 2EJ œ% ;“¨% LM²`% ijklm% , ( , ) uL%îï•%%c%ú{H%?*•%#$³¤%®j%BCj;. >. BC%@J Æ%!"7%BC%@J–%k÷bÊ•%,Ëg%ú¤%"Ñ%sžj; 4j +H . , , •'% œ•% °8³g% ¿"4% ijklm% no7% @Jj% Ò% c% ú?% 08—%%%% @J•% °8³g% Æ% !"—}% #$³¤% ~•€•j‚•% jK³¸% ijklm%% no%lž%uLj%,*%®j; Š‹%.K%]È•%Š³W%YR%Š‹7%ijk . lm% WGŸ% þN(¤% ?*ÐÅ% ¡Ñ> ~•€•j‚—% ´R-% ijklm%% , no%uL%îï%?*•%jK³¸ ijklm%—Ë%?I7%id%Pj{%jKQ% , kk`%ijklm•%uL³g%@æ%c%ú¤%*'•%?Ÿ%c%ú•%®j;.
  • 11. - 11 - 3. !"#$%.K%(%LM%(Research Design and Method) ,. !"#$%.K 그림 전체 연구과제의 구조도 [ 1]
  • 12. - 12 - 4. !"#$%LM *"]È%LM 1) €€•‚ƒÑ—}%#$¨%ijklm%ˆH%~•€•j‚7%'Ä%Š‹.K•% Œ•³W%Úvf²`%ijklm•%ˆHž«%c%ú²4%Œ•˜N%ôÒ?*•% ËX³Ë%/g%ú•%ijklm% Œ•˜N•%ôÒ³¤%®j%ŸÜÓg%sKQ% kk`% ijklm•% ˆH% c% ú{H% Ô¤% îï% ·¸¹Ÿ% 9ô³g% úË%% /?%08—%sKQ,%~•€•j‚—%7,³¤%'3•%iN%c%ú;. Æ% !"—}% #$³¤% ~•€•j‚–% Úvf% ijklm% ˆH–% ¬]%%%% ijklm%Œ•%˜N%ôÒ?*•%Šž%sKQ,%ÁF@%Œ•˜N•%(+ƒê< ôÒ³W%'Êx•%x•(g%,™%(%˃%sšÓ%noŸ%uL³¤Ž%{ª•% «%c%ú; I¨ sKQ7%ÒÓ•%]ȳg%½¾Ó%îï%·¸¹Ÿ%9ô³W% . , sKQ,%A%ì”j%ú¤%ijklm7%ÒÓ<%w—%8Õ%@æM•%•‘% c% ú²û% Ú9% ijklm% y‹Ÿ% †¥•% 0 ¢ÿ£@% @æ% c% ú{H%% , Ô¤;. tT 2) DFD ① (Data Flow Diagram) 그림 [ 2] DFD(Data Flow Diagram)
  • 13. - 13 - |}{ ② 그림 순서도 [ 3]
  • 14. - 14 - sKQ%ƒ„…jk ③ 그림 애플리케이션 사용자 인터페이스 [ 4]
  • 15. - 15 - Žj„• ④ Æ% !"—}¤% †‡ˆ‰X—}% 9ô³¤% ijklm% no% ‘ Š‹% Œ•% Žj„’ Ÿ%Žj„•²`%sK¨; j%Žj„¤%ˤ% ¹f%Ú9`%$p¨%ijk [12] . 7 lm% no7%Š‹%.K•%Œ•¨%Žj„`% ]%./7%•+%˜Nj; j%Žj„ê–% 1 . no%ÒÓ—%8>%©%,Ë`%]È™¤Ž Kl 'l †‡ˆ‰X%œ•%sš³¤% , , , cs?0%sšÓ <%Ö†€%@_•%¥×`%m㳤% @_s?Ó j; †‡ˆ‰X ‘ ’ ‘ ’ . —}¤%º% »7%Œ•%Žj„Ÿ%9ô³¤Ž j%)% cs?0%sšÓ j% » 412 , ‘ ’ 227 , @_s?Ó j% »²`%"+™•%ú; ‘ ’ 185 . Æ%!"—}¤%Žj„••%JI¨%©%,Ë%ÒÓ²`%]Ȩ%€ ÊÊ•%‘-ì` , ÞÇ`% 4¿•% Ÿ% ` Ÿ% ` 4ØË% 6:2:2 60% Train data , 20% Validation data , Ÿ% `%sK¨; Žj„¤%y%æ€%€%"V%•‘—%sK-; 20% Test data . Train . ¤%•‘%<O%)%"V7%+*•%KÀ³g ÊE%˜>¥„Ÿ%cO Validation data , ³¤% <O—% sK-; ÷˯²`% ¤% DE±ƒ% "V7% +*•% Æ,%% . Test data ³?% ìž% sK-; Ÿ% ¦% ]€³¤% jÒ¤ "V%%% . Validation data Test data , +*%KÀ%(%˜>¥„%cO%<O—}% Ÿ%jK³¸% <±§ j Test data Overfitting( ) $p%c%ú?%08j; Åq%"V•%•‘vˤ%<O—}%Žj„%G™²`%ƒ¨ . <X±§ j%$p%'Ä îÙ%KÀ •%sK³W% Underfitting( ) , Cross validation( ) 89Ÿ%ž’¨;. 그림 금융감독원 보이스피싱 범죄 통화 녹음 데이터셋 [ 5] [12] BERT ⑤ (Pre-training of Deep Bidirectional Transformers for Language Understanding) ¤% BERT Pre-training of Deep Bidirectional Transformers for Language 7%qQ` ¹%"Ù7% j%9ü¨%Q!•%æ€%©'Ú% Understanding , 2018 Devlin "dj; ìËlÛ¡7% ½# 7% ½#% Žj„Ÿ%jK . 25 , BookCorpus 8 Unlabled ³W%sy%Ü1-% ¤%?,7%ªL3%Q!•%æ€%"Vê7%ª:•%i~¨% BERT “L3%Q!•%æ€%"Vj?%08—%8à7%«<%Ý7%8Þ•%gN³W%L%t–% OiŸ%yE%c%ú; 8>}%ªL3%æ€%L!•%sK³¤% œ%;Õ . GPT, ELMo
  • 16. - 16 - •% "Vi;% ’–% +*•% iƒ; ¤% @-7% ßkb% Žj„¦% ;“¨%%% . BERT •Ÿ%ÿŽ²`%sy%Ü1-%"V•%à@`%èO%-…•%ì¨%©'Ú•%¬,³¤ yj%•‘ LM•%sK³W%á–%•‘%vf²`%Äc¨%+*•%.?% (Fine-tuning) 08— YR%!"Qê%sj—}%,à%Êâ%†¤%•%"Vj; , . 그림 [ 6] Overall pre-training and fine-tuning procedures for BERT [17] KoBERT ⑥ Æ%!"—}¤% —}%ô#¨%¨-•% "V Ÿ%sK¨; SK TBrain BERT (KoBERT) . j%"V–%"Ù—}%#$¨% "V•%?y²`% Å#%jJ7%8à²`%"+-% BERT 500 ¨-• ì˦% Å% #% jJ7% 8à²`% "+-% ¨-•% ek% Žj„Ÿ% •‘³É;% 2 [11]. ¤%YR% ãäå%rs„%J^sê7%…‘%AÇ‹Ÿ%ì¨%J^%æç< KoBERT SK M‘%(%èè%œH%…‘% AÇ‹Ÿ%ì¨% K)% }Þk s.7%L@¨% ÷•T%%% AI , QS—}% Oõ¨% é+•% ¬_ž% .¤% ?T‰ž% ?I7% êx% "V`{% sK™g%%% ú;%[18]. 그림 의 학습 결과 [ 7] KoBERT [11]
  • 17. - 17 - ijklm%no%uL%îï ⑦ Æ%!"—}%#$³¤%~•€•j‚—}¤%sKQ—@%;“¨%ÓÔ`%ijklm no%uL%îïQSŸ%9ô¨; sKQ¤%ijklm%no%v4€“%z” ijk . , lm%no%Š‹%z” ijklm%no%@æ%LM%µ¶ ijklm%no%uL%% , , ·¸¹ º» 2EJ% œ Ÿ% Šž% ijklm% no% uL% îï•% †•% c% ú; ( , ) . I¨%µ¶%:cH%œâ9 R]¶ Ú¼ oŒ ;j¡%œ Ÿ%{C³W%sKQê×€ ( , , , ) 'ë•%Ò{³¤%¨ë Q©7%œâ•% —%ôÒ%c%ú¤%?*•%#$³W% , SNS •p%(%ì–%ò7%±a±ƒ%VWŸ%Ò{¨;. sKQ%ÒÓ%]È ㉮ Æ%!"—}¤%A<±ƒ%•‘Q%½¾Ó%îï•%ì³W%~•€•j‚7%DÂ% Ú6%v%sKQ7 ÒÓ•%]Ȩ; j€%!q @ @ @ @% . (10 , 20-30 , 4-50 , 60 jJ < ) +H e…Ð%?y7%sKQ%ÒÓ%]È%’<Ÿ%ÿŽ²`%Ê%sKQ%% , —@%,à%A<±ƒ%îï%QSŸ%Q2²`%¬ ¨;. ijklm%no%v4€“%z” ㉯ Æ%!"—}¤%sKQ,%Ú9%ijklm%sÇŸ%?y²`%¨%v4€“Ÿ% z”%c%ú{H%¨; v4€“¤% . —}%c6¨%sKQ%ÒÓ%]È%’<Ÿ% ㉮ ÿŽ²`%sKQ—@%,à%A<±ƒ%ÒÓ²`%9ô-;. sKQ¤% wx% [ 7]1) 7%<O•%Šž%Ê%ªT÷;%Q©7 62•%5Í%c%ú; Åq%ijklm% . lžŸ% A% c% ú¤% 62•% 5ͨ% 'Ä ~•€•j‚—}¤% sKQ—@%% , žA% 62j% ijklm% lžŸ% A% c ú¤% 62í•% þN(g w3¨%%% , JZ—}% •î@%@æžD%³¤Ë%þNï; sKQ¤% ijklm%v4€“% . z”•%Šž%ijklm%JZ—}%•î@%62žD%³¤Ë%•‘³û Ú9`%% , ijklm% no% JZ•%mÁ•% 0% ¢ÿÕ% @Õ% LM•%sK³W%ðñ³@% @æ%c%ú@%-;. 1) wx% ijklm%no%v4€“%z”%"d{¤%'Jò{'l¢—}%9-³W%ô#¨%ijklm%"7% [ 8] z”0 7% QSŸ% ÿŽ²`% 9-™š²û ¬€% #$% ªT—}¤% !">j% c6% ijklm% sÇ%% [19] , ]È7%’<Ÿ%ÿŽ²` Ê%sKQ%ÒÓH%½¾Ó%v4€“Ÿ%9ô%TUí.
  • 18. - 18 - 그림 보이스피싱 범죄 시나리오 체험 구조도 [ 8]
  • 19. - 19 - ijklm%no%Š‹%z” ㉰ ijklm%Š‹%z”–%†‡ˆ‰X—}%9ô¨%Ú9%ijklm%Š‹%Œ•%% Žj„% Ÿ%em%ê•%c%ú¤%?*j; sKQ%]È•%Šž%ó•>%sKQ [12] . ÒÓ%Žj„Ÿ%ÿŽ²`% W»7%Š‹%.K%)%sKQ%ÒÓ—%þ½¤%sÇŸ%% 400 ¬ ¨;. sKQ¤%ijklm%no%Š‹%z”•%Šž%ijklm7%Ú9%lž sÇŸ%pp³@%m³û Q©—@%Òs¨%JZj%$pÁ•%0%i;%YÛ³@%% , @æ%c%ú;. ijklm%no%uL%îï%·¸¹ ㉱ ijklm%no%uL%îï%·¸¹¤%†‡ˆ‰X—}%9ô³¤%ijklm%% uL%·¸¹ º» 2EJ%œ Ÿ%ˆJ%c%ú¤%?*j; sKQ%]È•%Šž% ( , ) . ó•>% sKQ% ÒÓ% Žj„Ÿ% ÿŽ²`% sKQ,% ô¥Ÿ% õöŨ% ·¸¹Ÿ% Q2²`% ¬ ¨; sKQ¤% ·¸¹Ÿ% ˆJ³û% Q!k÷@% ijklm7%%% . #” ÒÓ @æLM%œ—%@ž%•‘%c%ú; , , .
  • 20. - 20 - "Y 3) 표 구현 항목별 세부사항 [ 4] 항목 세부 사항 #$%ä' • Jetbrains IntelliJ IDEA, Google Colab #$%• • Python >jR3€ • PyTorch, KoBERT, KoNLPy, KSS, py-hanspell, Soynlp Žj„• • †‡ˆ‰X%ijklm%no%Š‹%Œ•%Žj„ 2Ez9 • Windows, MacOS, Android, Linux Ú” 4) ~•€•j‚% #$% €% t8dsŸ% 9-³W% øùúk„ê—@% &6¨;. Æ,¤% :% Å{`% "+™û øùúkT% ES% €% t8ds% ’<Ÿ% c&‹%% 5 , ³W%j€%~•€•j‚7%cO%(%i~%-…—%PK¨;.
  • 21. - 21 - 표 설문조사 예시 [ 5] 항목 문항 점수 점 (1~5 ) ~•€•j‚ ~•€•j‚%.%·¸¹êj%û%Ú6™¤,? ~•€•j‚•%sK³?%Kj¨,? îï%·¸¹ sKQ7%ÒÓ—%±§¨%·¸¹Ÿ%9ô³É¤,? ijklm•%uL³¤Ž%{ªj%™š¤,? ƒôË* "%%%%V ijklm%WGŸ%Oõð%ˆHÁ¤,? ijklm%WGŸ%±c¨%vf%.`%ˆHÁ¤,? Š‹%Œ• ôÒ%?* ôÒ?*j%û%Ú6™¤,? ¿"4%F@%?*•%sK%c%ú¤,? ;. !"#$%NO 세 부 과 제 연 구 개 발 일 정 비 고 월 12 월 1 월 2 월 3 월 4 월 5 월 6 (9%5O%(%tT ƒôË*%"V%#$ ~•€•j‚%#$ úkb ÒËic 표 세부과제별 연구개발 일정 [ 6]
  • 22. - 22 - 4. 활용 기자재 및 재료 (Equipment Required) ,. #* Dã%Q!•%æ€%]D—}%,à%ü–%+*•%ijg%ú¤% "V•%PK BERT ¨; ³ËÅ% ¤%¨-•%怗%}q³ý` ¨-•%Žj„•²`%•‘-% . BERT , ?y7% 7% Ÿ% PK³W% yj% •‘ •%%% BERT SK Tbrain KoBERT (Fine-tuning) >6¨;. ~•€•j‚–% "Ù—}% üŒ`jŒ% #$•% ì¨% ô!% •`% ËO¨% •%sK³W%#$¨; Kotlin . 4. PKTU%(%?@A< Úvf²`%ijklm•%ˆË³W%ijklm%no%lžŸ%uL¨; I¨ . , ijklm% z”•% Þþ¨% W3% îïK% ·¸¹Ÿ% 9ô³W% sKQ,% kk`%% ijklm•% ˆH³g% ¢ÿÕ% @æŸ% % c% ú{H% {ª•% ï; îïK%%%% . ·¸¹¤%sKQ7%4j +H e…%œ•%˜ÿ³W%½¾Ó%}ÞkŸ%9ô³û , , , sKQ,% (7žD% ³¤% ijklm% ÒÓ<% @æLü•% JFð% þNï;. sKQ¤%Ú9%ijklm%y‹Ÿ%†L>{%îï%·¸¹—}%•‘¨%@`%±c ³@%@æ%c%ú²û%ijklm%Š‹%.K•%Œ•³g%(+ƒê<%ôÒž% ,™%(%˃%sšÓ%ijklm%no7%¬,±ƒ%lžŸ%uL%c%ú;. 5. VW!"X%YZ%(%[]^%(The Role of Researchers) ,. VW!"X%YZ 학 과 이 름 학 번 학년 학기 연 락 처 ‚!„îï< “ËÜ 3 1 ‚!„îï< j"Ü 3 1 표 참여연구원 현황 [ 7]
  • 23. - 23 - 4. _`ab%c6%de 그림 프로젝트 수행 조직도 [ 9] ;. VW!"X%f%[]^ 연 구 원 역 할 분 담 세 부 내 역 비 고 “ËÜ #3$%"V%#$ - Žj„%æ€%}¼%"Í - Š‹%.K%Úvf%yå%?*%"Y - ijklm%uL%îï%?*%"Y - j"Ü #3$%"V%#$ - Žj„•%cJ%(%yæ€ - ijklm%Š‹%Œ•%(%ôÒ%?*%"Y - ijklm%uL%îï%?*%"Y - 표 참여연구원 간 역할분담 내역 [ 8]
  • 24. - 24 - 6. Vg8h%(Reference) [ 1 ] ƒK https://www.fss.or.kr/fss/main/contents.do?menuNo=200354, 2022.03.23. [ 2 ƒK ] https://www.data.go.kr/data/15063815/fileData.do, 2022.03.23. [ 3 ž+ Ã@'% ijklm7% uL<% @ù÷1•% ì¨% !" ¨-Óss%% ] (2009). . ・ Où!"X. [ 4 ] j?c Dã%ijklm7%nocM%23<%M±%@ÕLü nocs•!" (2018). . , 7, pp3-19. [ 5 í+Q lm%s?no—%@¨%ƒ„h%(%-,H%@ÕOù%Þî!" 'l• ] (2019). . %º, 14(1), pp101-130. [ 6 ] Og– vEÝ wÂ? x€±b€ÜŸ%±K¨%ijklm%sÇ]È sÎô•• , , (2017). : )x²` sÎ<•!" . , 28(4), pp181-194. [ 7 ] vïX ?y7%Úvf%ijklm k¥m%LË%vn%}Þk Žj„ (2020). AI . 2020 ・ •Ýw„%sÇJ, pp64-73. [ 8 vwO v–¥ ijklm% lž% '”% (% E3*ƒ% ]È XÞQ89!" ] (2021). . , ・ 52(1), pp52-71. [ 9 ƒK ] https://www.boannews.com/media/view.asp?idx=100557, 2022.03.23. [10] https://www.donga.com/news/Society/article/all/20220105/111095788/1, ƒK 2022.03.23. [11] https://github.com/SKTBrain/KoBERT ƒK , 2022.04.05. [12] https://www.fss.or.kr/fss/bbs/B0000207/list.do?menuNo=200691, 2022.04.04. ƒK [13] https://konlpy.org/en/latest/ ƒK , 2022.04.05. [14] https://github.com/hyunwoongko/kss ƒK , 2022.04.05. [15] https://github.com/ssut/py-hanspell ƒK , 2022.04.05. [16] https://github.com/lovit/soynlp ƒK , 2022.04.05. [17] Jacob Devlin, Ming-Wei Chang, Kenton Lee, Kristina Toutanova(2019). BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. NAACL-HLT (1) 2019, pp4171-4186. [18] https://www.skt.ai/kr/press/detail.do?seq=27 ƒK , 2022.04.05. [19] https://gbpolice-preventphishing.kr/ ƒK , 2022.04.05.