/
Defending against Sybil Devices in Crowdsourced Mapping Services Defending against Sybil Devices in Crowdsourced Mapping Services

Defending against Sybil Devices in Crowdsourced Mapping Services - PowerPoint Presentation

unita
unita . @unita
Follow
344 views
Uploaded On 2021-01-27

Defending against Sybil Devices in Crowdsourced Mapping Services - PPT Presentation

Gang Wang Bolun Wang Tianyi Wang Ana Nika Haitao Zheng Ben Y Zhao UC Santa Barbara bolunwangcsucsbedu Mobile Life Mobile phones for content payment authentication Mobile devices are ID: 830228

sybil waze devices users waze sybil users devices 2016 user gps location fake real apr track create https mobile

Share:

Link:

Embed:

Download Presentation from below link

Download The PPT/PDF document "Defending against Sybil Devices in Crowd..." is the property of its rightful owner. Permission is granted to download and print the materials on this web site for personal, non-commercial use only, and to display it on your personal computer provided you do not modify the materials and that you retain all copyright notices contained in the materials. By downloading content from our website, you accept the terms of this agreement.


Presentation Transcript

Slide1

Defending against Sybil Devices in Crowdsourced Mapping Services

Gang Wang, Bolun Wang, Tianyi Wang, Ana Nika, Haitao Zheng, Ben Y. ZhaoUC Santa Barbarabolunwang@cs.ucsb.edu

Slide2

Mobile = Life

Mobile phones for content, payment, authenticationMobile devices are virtual representations of ourselves.1

=

Slide3

But Is This a Safe Assumption?

App User = real phone + real person?2

Slide4

Can We “Authenticate” Devices?

Register via email accountRequire CAPTCHAs2FA via phone numberValidate IMEI number

Create fake email

account

Out-source to third party

Temporary SMS

services

Spoofed

IMEI

3

Slide5

In This Talk

Sybil device problemSoftware scripts emulating as real devicesAllowing a single user to control many devicesIn the context of Waze (popular navigation app)Techniques generating Sybil devicesAttacks on Waze: injecting fake events, user location trackingDefense against Sybil devicesThe story between us and WazeBroader implications

4

Not in paper

Slide6

Key Features

5User reported events

Accidents, construction, police cars, etc.

Alert user of nearby events

Social features

See nearby users on the map

Say “hi” and message nearby users

50M active users

Real-time traffic update using millions of users’ locations

Slide7

Sybil Devices in Waze

Sybil devices have significant impact on WazeInject fake data, retrieve sensitive informationExisting work: mobile emulatorsTwo Israeli students used emulators to created fake traffic jams in 2014

Not scalable

: ~10 emulators per PC

Virtualize devices using scripts

Scalable

: 1,000 – 10,000 Sybil devices per server

Overwhelm normal users’ data

Launch special large scale attacks

6

Slide8

Create Sybil Devices using Script

IntuitionGoal: emulate a full mobile clientServer communicates with client via limited APIsMimic API calls to replace full client7

Waze Client

Waze Server

HTTPS

HTTPS Proxy

HTTPS

HTTPS

Controlled by us

Plaintext

traffic

We can create 10,000 Sybil devices on a single PC

Slide9

Attack #1: Polluting Waze Database

Fake road-side events.Any type of event at any locationPotentially affect 1+billion Google Maps usersFake traffic hotspotsSimulate cars driving slowly

Large groups of Sybil

devices

to overwhelm

normal users’

data

8

Before

After

Users are re-routed

Slide10

Attack #2: User

Location TrackingFollow (stalk) any Waze user in real-timeWaze marks nearby users on the mapPinpoint to

exact GPS location

Specific hotels, gas stations, etc.

Remain

invisible

Move in and out quickly

Track users

in the background

Waze uploads GPS in the background

Track users across days

Use creation time as GUID

9

Slide11

A Tracking Example

10

Slide12

Tracking Experiments

11

GPS Captured

GPS Missed

Extremely dense user population

Fast moving target user

Tracking attack is

effective and practical

LA downtown

Highway 101

Slide13

The Story of Us and Waze

12

Slide14

Conversation with Waze

13Time

Notify Waze and Google

Nov. 14 2014

1

st

code change: remove background GPS upload

Oct. 18 2015

Pitch work to Fusion

Fusion report on tracking

Media attention

Public PR release

2

nd

code change: disable social function

More news coverage

Apr. 16 2016

Apr. 26 2016

Apr. 27 2016

May. 11 2016

Work with Waze

+21 more

+16 more

Slide15

Waze’s

Security Measures14Time

Disable social feature in versions <= 3.5

Use special encoding for app-to-server APIs

Crack encoding within a day

Validate via experiments

Remove username

Scramble creation time

Require SMS verification to see identifiable information

Use temporary SMS services to pass verification

Validate via experiments

Apr. 27 2016

Apr. 29 2016

May 17 2016

May 23 2016

Remove background GPS upload

Hide start/end location

Hide GPS when not moving

Oct. 18 2015

Track active users

May 11 2016

Start collaboration

Yes, we can still track Waze users

Much less location information being shared

Slide16

Broad Implications on Other Apps

Sybil device problem is not specific to WazeE.g. Foursquare, Yelp, Uber, Lyft, Tinder

,

Whisper

We reverse engineer their APIs, and create light-weight clients using scripts

Tinder/Whisper

Locate (

triangulate) users

Uber

/

Lyft

Track driversFake rides

15

Slide17

Today

Good defense: Yik YakUse HMAC[1] to ensure message integrityEmbed key in codeRequire decompiling codeMarket for selling attack toolsPlugin apps for Didi

in China

Spoof location

Filter orders

Snatch orders

16

[1] HMAC: Hash-based Message Authentication Code

Slide18

17

Thank you!Questions?