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Discovery of the Bursty Botnet by unusual tweeting behavioursstatisticalcyber.com/talks/Zhou, Shi...

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Juan Echeverria, Christoph Besel, Shi Zhou Department of Computer Science University College London (UCL) Discovery of the Bursty Botnet by unusual tweeting behaviours Discovery of the Bursty Botnet by unusual tweeting behaviours
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Page 1: Discovery of the Bursty Botnet by unusual tweeting behavioursstatisticalcyber.com/talks/Zhou, Shi slides.pdf · Twitter bot detection •Many methods based on ‘common features’

JuanEcheverria,ChristophBesel,ShiZhouDepartmentofComputerScienceUniversityCollegeLondon(UCL)

DiscoveryoftheBurstyBotnetbyunusualtweeting

behaviours

DiscoveryoftheBurstyBotnetbyunusualtweeting

behaviours

Page 2: Discovery of the Bursty Botnet by unusual tweeting behavioursstatisticalcyber.com/talks/Zhou, Shi slides.pdf · Twitter bot detection •Many methods based on ‘common features’

Twitterbotsandbotnet

Threats:Fakenews;spam;phishing;opinionmanipulation;streamingAPIcontamination;advertisementfraud...

Page 3: Discovery of the Bursty Botnet by unusual tweeting behavioursstatisticalcyber.com/talks/Zhou, Shi slides.pdf · Twitter bot detection •Many methods based on ‘common features’

Twitterbotdetection

• Manymethodsbasedon‘commonfeatures’ofbots• Onlysmallnumbersofbotsdetected

• Lackofgroundtruth

Page 4: Discovery of the Bursty Botnet by unusual tweeting behavioursstatisticalcyber.com/talks/Zhou, Shi slides.pdf · Twitter bot detection •Many methods based on ‘common features’

Outlineofthistalk

•RecentdiscoveryofStarWarsBotnet• 350,000bots

•OurdiscoveryoftheBurstyBotnet• 500,000bots• Unusualtweetingbehaviours• Directlinkwithaspammingattack

•ReflectiononTwitterbotdetection

Page 5: Discovery of the Bursty Botnet by unusual tweeting behavioursstatisticalcyber.com/talks/Zhou, Shi slides.pdf · Twitter bot detection •Many methods based on ‘common features’

Distributionofthelocationtagsoftweetsby1%Twitterusers

FirstclueoftheStarWarsbotnet

Page 6: Discovery of the Bursty Botnet by unusual tweeting behavioursstatisticalcyber.com/talks/Zhou, Shi slides.pdf · Twitter bot detection •Many methods based on ‘common features’

Uniformdistributionintworectanglezones?Evenonseaanddesert?

Page 7: Discovery of the Bursty Botnet by unusual tweeting behavioursstatisticalcyber.com/talks/Zhou, Shi slides.pdf · Twitter bot detection •Many methods based on ‘common features’

TweetsofrandomquotationsfromStarWarsnovels

Alltweets

Thesuspicioustweets

Page 8: Discovery of the Bursty Botnet by unusual tweeting behavioursstatisticalcyber.com/talks/Zhou, Shi slides.pdf · Twitter bot detection •Many methods based on ‘common features’

TheStarWarsBotnet• OnlytweetedrandomquotationsfromSWnovels.• OnlytweetedfromthesourceofWindowsphone

• Windowsphoneaccountsforonly0.02%ofalltweets.

• <10followers,<32friends,<11tweets....• >350,000Botsareidentified.

Page 9: Discovery of the Bursty Botnet by unusual tweeting behavioursstatisticalcyber.com/talks/Zhou, Shi slides.pdf · Twitter bot detection •Many methods based on ‘common features’

Nicestory...And?

Page 10: Discovery of the Bursty Botnet by unusual tweeting behavioursstatisticalcyber.com/talks/Zhou, Shi slides.pdf · Twitter bot detection •Many methods based on ‘common features’

0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.294

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Twitter ID (0 ~ 232)

Perc

en

tag

e

Twitter Users

ID Range containing Star−Wars Bots

Billions

1500 1510 1520 1530 1540 1550 1560 1570 1580 1590 1600

1%

5%

10%

30%

Twitter ID

Pe

rce

nta

ge

of

ID s

pa

ce

us

ed

Random Users

StarWars Bots

SWbotswerecreatedinburst!

Page 11: Discovery of the Bursty Botnet by unusual tweeting behavioursstatisticalcyber.com/talks/Zhou, Shi slides.pdf · Twitter bot detection •Many methods based on ‘common features’

SWbotsalsotweetedinburst!

• Alltheirtweetsweregeneratedimmediatelyaftertheircreation.

• Definitionof‘burstyusers’:• Usersthattweetedatleast3timesintheirfirsthour• Thentheynevertweetedagain

Page 12: Discovery of the Bursty Botnet by unusual tweeting behavioursstatisticalcyber.com/talks/Zhou, Shi slides.pdf · Twitter bot detection •Many methods based on ‘common features’

0 0.5 1.0 1.5 2.0 2.5 3.0 3.50

25%

50%

75%

100%

Twitter user ID space

Perc

en

tag

e o

f us

er ID

s

All users Bursty users

Star Wars bots

x10^9

Bursty bots

0 0.5 1.0 1.5 2.0 2.5 3.0 3.50

20,000

40,000

60,000

80,000

100,000

120,000

140,000

Twitter user ID space

Num

ber o

f bu

rsty

users

x10^9

Bursty bots

Star Wars bots

July 2013March 2012Feb 2012

June 2013

DiscoveryoftheBurstyBotnet

Page 13: Discovery of the Bursty Botnet by unusual tweeting behavioursstatisticalcyber.com/talks/Zhou, Shi slides.pdf · Twitter bot detection •Many methods based on ‘common features’

TheBurstyBotnet

• BurstyBotsonlytweetedintheirfirst2minutes.• TheywerecreatedinFebruaryandMarch2012.• TheyonlytweetedfromthesourceofMobileWeb.• Theymostlytweeted(i)aURL;and/or(ii)amention.

0 2 4 6 8 100

0.2

0.4

0.6

0.8

1

Minutes from creation to last tweet

Dis

trib

uti

on

Bursty bots

Star Wars bots

Page 14: Discovery of the Bursty Botnet by unusual tweeting behavioursstatisticalcyber.com/talks/Zhou, Shi slides.pdf · Twitter bot detection •Many methods based on ‘common features’

TheBurstyBotnet

• >500,000BurstyBotsareidentified.• StillaliveinTwitter.

• MostburstyusersareBurstyBots!

500 505 510 515 520 525 530 5350

2

4

6

8

10

12x 10

4

Twitter user IDs (x10^6)

Nu

mb

er

of

use

rs

Bursty users Bursty bots Difference

Page 15: Discovery of the Bursty Botnet by unusual tweeting behavioursstatisticalcyber.com/talks/Zhou, Shi slides.pdf · Twitter bot detection •Many methods based on ‘common features’

500 505 510 515 520 525 530 5350

5

10

15x 10

4

Twitter user IDs (x10^6)

Nu

mb

er

of

users

September 2015

September 2016

Disappeared Bursty bots

The‘disappeared’BurstyBots

• Another300,000BurstyBotshavebeenremovedbyTwitterbetweenSept.2015andSept.2016.• AvotefromTwitterthattheseareindeedbadbots?• ItseemsTwitterdoesnotknowwhatweknow?

Page 16: Discovery of the Bursty Botnet by unusual tweeting behavioursstatisticalcyber.com/talks/Zhou, Shi slides.pdf · Twitter bot detection •Many methods based on ‘common features’

• MostBurstyBotshavenofriendorfollower.• TheymostlytweetedonlyaURLand/oramention.

• Spammingattack?

TheBurstyBotnetproperties

Page 17: Discovery of the Bursty Botnet by unusual tweeting behavioursstatisticalcyber.com/talks/Zhou, Shi slides.pdf · Twitter bot detection •Many methods based on ‘common features’

TheBurstyBotnetspammingattack• 99.9%(2.8m)URLsareunique• ComplexURLshortenersandredirects.•MostURLspointtotwospamcampaigns.• Awebpageblockedbytinyurl.com• Aknownphishingwebpage

• www.facebook-goodies.com

Page 18: Discovery of the Bursty Botnet by unusual tweeting behavioursstatisticalcyber.com/talks/Zhou, Shi slides.pdf · Twitter bot detection •Many methods based on ‘common features’

Acarefullydesignedspammingattack

• 500,000botswerecreatedinburst,andtheytweetedinburst-- toevadebotdetection.• 2.8millionsuniqueURLsusingshortenersandredirects– tofoolspamdetection.• 1.3distinctTwitteruserswerementioned-- toincreasevisibilityandchanceofbeingclicked.• Success:61%ofURLswereactuallyclicked!• Aremarkablerevenue?

Page 19: Discovery of the Bursty Botnet by unusual tweeting behavioursstatisticalcyber.com/talks/Zhou, Shi slides.pdf · Twitter bot detection •Many methods based on ‘common features’

TheBurstyBotnet

•Nodoubtitisabotnet,anditwasforspammingattacks.•Furtherstudycanevenrevealtheallegedbotmaster.•Fullanalysisofthespammingattackwillbepublishedelsewhere.J• withalotofinterestingdetails...

Page 20: Discovery of the Bursty Botnet by unusual tweeting behavioursstatisticalcyber.com/talks/Zhou, Shi slides.pdf · Twitter bot detection •Many methods based on ‘common features’

ReflectiononTwitterbotsdetection•Existingmethodsfailtodetectlargebotnets•Theassumed“commonfeatures”arenotneccessarilycommon.•Understandable:lackofgroundtruth;evolvingbotnets

Page 21: Discovery of the Bursty Botnet by unusual tweeting behavioursstatisticalcyber.com/talks/Zhou, Shi slides.pdf · Twitter bot detection •Many methods based on ‘common features’

Along-termbattle• Thetwobotnetswerediscoveredbytheirunusualtweetingbehaviours.•Wecannotexpecttorepeatourluck.

•Botmasterswilllearnlessons.• Newbotnetswillavoidanyknownfeatures,especiallythecommonfeatures.

• Isa‘general’approachrealistic?• Todetectcommonorunusualfeatures?

Page 22: Discovery of the Bursty Botnet by unusual tweeting behavioursstatisticalcyber.com/talks/Zhou, Shi slides.pdf · Twitter bot detection •Many methods based on ‘common features’

ThankYou!

Dr.ShiZhouUniversityCollegeLondon(UCL)

ThankYou!

Dr.ShiZhouUniversityCollegeLondon(UCL)


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