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微信恶意账号检测研究 - 杨征, 殷其雷, 李浩然, 苗园莉, 元东, 王骞, 沈超, 李琦.pdf
42
14页
1次
2021-11-10
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DOI
:
issn
JournalofCom
p
uterResearchandDevelo
p
ment
(
):
,
 
稿
:
;
:
 
:
(
YFB
);
(
,
UB
,
,
,
,
U
,
);
(
BNRRC
);
西
(
ZDLGY
)
Thisworkwassu
pp
ortedb
y
theNationalKe
y
ResearchandDevelo
p
mentPro
g
ram ofChina
(
YFB
),
theNational
NaturalScience Foundation ofChina
(
,
UB
,
,
,
,
U
,
),
the
Pro
j
ectofBNRist
(
BNRRC
),
andtheShaanxiProvinceKe
y
Industr
y
InnovationPro
g
ram
(
ZDLGY
)
 
:
(
q
litsin
g
huaeducn
)
 
 
 
 
 
 
 
 
 
 
 
 
(
 
 
)
(
 
 
)
(
西
 
西
 
)
(
y
zmailstsin
g
huaeducn
)
Stud
y
ofWechatS
y
bilDetection
Yan
g
Zhen
g
,
YinQilei
,
LiHaoran
,
MiaoYuanli
,
YuanDon
g
,
Wan
g
Qian
,
ShenChao
,
andLiQi
(
Institute
f
orNetworkSciencesandC
y
bers
p
ace
,
Tsin
g
huaUniversit
y
,
Bei
j
in
g
)
(
Schoolo
f
C
y
berScienceandEn
g
ineerin
g
,
WuhanUniversit
y
,
Wuhan
)
(
Schoolo
f
C
y
berScienceandEn
g
ineerin
g
,
Xi􀆳anJiaoton
g
Universit
y
,
Xi􀆳an
)
Abstract Onlinesocialnetworks
(
OSNs
)
areefficient
p
latformsforinformationdisseminationand
facilitateourdail
y
lifeThevalueofOSNaccountsincreaseswiththe
p
o
p
ularit
y
ofOSNsInorderto
obtain
p
rofitsille
g
all
y
,
attackerslevera
g
e OSNstoconstructvariousattackssuch asfraudand
g
amblin
g
Anumberofsolutionshavebeen
p
ro
p
osedto
p
rotectusers􀆳securit
y
,
whichmainl
y
focuses
ondetectin
g
maliciousaccounts
(
orS
y
bils
)
b
y
anal
y
zin
g
userbehaviororthe
p
ro
p
a
g
ationofuser
relationsUnfortunatel
y
,
itusuall
y
takes muchtimetocollectenou
g
hdatato
p
erform malicious
accountdetectionAttackerscan
p
erform differentkindsofattacksdurin
g
thedatacollection
p
hase
TodetectS
y
bilsefficientl
y
,
we
p
ro
p
oseanewa
pp
roachthatlevera
g
esaccountre
g
istrationattributes
todetectS
y
bilsFirst
,
weanal
y
zetheexistin
g
detectionmethodsins
y
bildetectionThen
,
weanal
y
ze
there
g
istration dataof WeChatWeanal
y
zeandcom
p
arethedistributionofS
y
bilsand beni
g
n
accountsindifferentre
g
istrationattributes
,
andfindthatS
y
bilsare
p
ronetocluster withsome
re
g
istrationattributesAccordin
g
tothesestatistics
,
weextracttwokindsoffeaturesfrom different
attributes
,
ie
,
s
y
nchronizationbased features and anomal
y
based features
,
and calculate the
similarit
y
oftwoaccountsbasedonthosefeaturesTheaccountsthathavehi
g
hsimilarit
y
aremore
likel
y
tobe maliciousFinall
y
,
webuilda
g
ra
p
hu
p
onaccountshavin
g
ahi
g
hsimilarit
y
tocluster
malicioususersWecalculatea maliciousscoreforeach usertoinfer whetheritisaS
y
bilWe
p
rotot
yp
eoura
pp
roach
,
andtheex
p
erimentalresultswithrealWeChatshowthatoura
pp
roachcan
achieve
p
recisionand recall
Ke
y
words onlinesocialnetwork
;
clusterin
g
;
s
y
bildetection
;
accountre
g
istrationcharacteristics
;
statisticalanal
y
sis
 
 
,
使便
,
线
,
,
,
,
,
,
,
;
,
 
线
;
;
;
;
 TP
  
,
,
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,
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,
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使
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,
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,
(
)
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),
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]
;
(
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,
[
]
,
,
,
,
,
,
,
广
,
,
,
,
,
,
,
,
,
,
,
使
,
IP
,
使
,
,
IP
,
,
使
,
,
,
便
,
,
,
:
)
,
;
)
,
;
)
,
 
,
(
)
of 14
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