compromising location privacy in wireless networks using sensors with limited information n.
Download
Skip this Video
Loading SlideShow in 5 Seconds..
Compromising Location Privacy in Wireless Networks Using Sensors with Limited Information PowerPoint Presentation
Download Presentation
Compromising Location Privacy in Wireless Networks Using Sensors with Limited Information

Loading in 2 Seconds...

play fullscreen
1 / 29

Compromising Location Privacy in Wireless Networks Using Sensors with Limited Information - PowerPoint PPT Presentation


  • 135 Views
  • Uploaded on

Compromising Location Privacy in Wireless Networks Using Sensors with Limited Information. Author: Ye Zhu and Riccardo Bettati Department of computer science, Texas A&M University. Presenter: Kai-shin Lu. The Problem. How to find out the positions of fixed wireless nodes?.

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about 'Compromising Location Privacy in Wireless Networks Using Sensors with Limited Information' - dante-martinez


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
compromising location privacy in wireless networks using sensors with limited information

Compromising Location Privacyin Wireless Networks Using Sensors with Limited Information

Author: Ye Zhu and Riccardo Bettati

Department of computer science, Texas A&M University

Presenter: Kai-shin Lu

the problem
The Problem
  • How to find out the positions of fixed wireless nodes?
na ve solution 1
Naïve Solution 1
  • He tells me (eavesdrop)

I am in Atanosoff.

I want to order one pizza.

If I can protect my position information? (e.g. cloaking, encrypting)

If I don’t need any location service?

na ve solution 2
Naïve Solution 2
  • Directive sender

If I don't’ have enough money to buy directive sensors?

problem
Problem
  • How to compromising location privacy in wireless networks using sensors with Limited Information ?
solution
Solution
  • Step 1. Deploy sensors (spies) among wireless nodes to eavesdrop data
    • We know the position of deployed sensors

Nodes

Nodes + Sensors

solution1
Solution
  • Step 1. (Continue)
    • The sensors only collect the time series of packet counts
    • E.g. [100,200,13]

I got 100 packets during 0-10 seconds.

I got 200 packets during 11-20 seconds.

I got 13 packets during the next 10 seconds.

Control center

solution2
Solution
  • Step 2. Use Principal Component Analysis (PCA) to estimate node numbers in this area
principal component analysis pca

531 grade

511 grade

Principal Component Analysis (PCA)
  • An important statistics technique

The second component

531 grade

Mike

IQ

511 grade

The first (principal) component

principal component analysis pca1
Principal Component Analysis (PCA)
  • This skill can be applied to 3 or more dimensional data
what can we do with pca
What can we do with PCA?
  • Suppose we draw a point for a time period...

The red point represents the 3rd time period’s data.

Its coordinate is

(13,8,6)

[x,x,8,x,x,…]

Packet # of Sensor 2

6

13

8

Packet # of Sensor 1

[x,x,13,x,x,…]

Packet # of Sensor 3

[x,x,6,x,x,…]

what can we do with pca1
What can we do with PCA?
  • Draw all points
    • Is there any hidden factor behind these data?

Yes! There are 2 hidden factors which greatly affect the data !!

There are 2 wireless nodes in this area !!

solution3
Solution
  • Step 2. Use Principal Component Analysis (PCA) to estimate node numbers in this area
  • Step 3. Then use Blind Source Separation(BSS) to estimate the positions of nodes
blind source separation bss
Blind Source Separation (BSS)
  • BSS was originally developed to solve the cocktail party problem
    • Which can extract one person’s voice signal given a mixtures of voices at a cocktail party

Hi Mike, how are you doing today?

…So I went to HyVee yesterday.

nice property of bss
Nice property of BSS
  • Get unmixed singles from mixed signals
  • Suppose sensor 1 got : [5, 0, 1, 0, 1 ]
    • Apply BSS, we can get unmixed signals
      • One is [3,0,0,0,0] – which might come from Node A
      • One is [2,0,0,0,1] – which might come from Node B
      • One is [0,0,1,0,0] – which might be noise

Sensor 1

Node B

Node A

what can we do with bss
What can we do with BSS?
  • Trick: We cut the whole area into many overlapped blocks

1

what can we do with bss1
What can we do with BSS?
  • Trick: We cut the whole area into many overlapped blocks

2

what can we do with bss2
What can we do with BSS?
  • Trick: We cut the whole area into many overlapped blocks

3

what can we do with bss3
What can we do with BSS?
  • Trick: We cut the whole area into many overlapped blocks

4

what can we do with bss4
What can we do with BSS?
  • Trick: We cut the whole area into many overlapped blocks

This square belongs to 4 blocks

what can we do with bss5
What can we do with BSS?
  • For each block, we apply BSS to get many separated signals

[How are you]

what can we do with bss6
What can we do with BSS?
  • For each block, we apply BSS to get many separated signals

[How or you]

{Cab sin}

[How are you]

what can we do with bss7
What can we do with BSS?
  • For each block, we apply BSS to get many separated signals

[How or you]

{Cab sin}

[How are you]

[How are youth]

what can we do with bss8
What can we do with BSS?
  • For each block, we apply BSS to get many separated signals

[How or you]

{Cab sin}

[How are you]

[haha you]

[How are youth]

what can we do with bss9

Cluster 1

noise, ignore

What can we do with BSS?
  • Cluster the separated signals together based on similarity

[How or you]

{Cab sin}

[How are you]

[haha you]

[How are youth]

what can we do with bss10
What can we do with BSS?
  • By analyzing the overlap of signals, we can estimate the position of them.

[How are you]

solution summary
Solution summary
  • By PCA, we know that there are n nodes
  • Cut whole area into many overlapped blocks
  • Apply BSS in each block
    • Get many separated (unmixed) signals
  • Cluster them together based on similarity
  • Pick up n largest clusters
  • Use overlap analysis to estimate the positions of nodes
discuss
Discuss
  • Good:
    • If the nodes are fixed, then it provides a cheap way to get their positions even though the data are perfectly encrypted
  • Bad:
    • The nodes should be fixed
    • If nodes can manipulate signal power, the overlap analysis part will fail
    • It assume that the communications among sensors won’t affect normal data collecting