Download - Compromising Location Privacy in Wireless Networks Using Sensors with Limited Information
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Iowa State University Department of Computer ScienceSoftware Engineering Laboratory
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
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Iowa State University Department of Computer ScienceSoftware Engineering Laboratory
The Problem
• How to find out the positions of fixed wireless nodes?
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Iowa State University Department of Computer ScienceSoftware Engineering Laboratory
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?
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Iowa State University Department of Computer ScienceSoftware Engineering Laboratory
Naïve Solution 2
• Directive sender
If I don't’ have enough money to buy directive
sensors?
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Iowa State University Department of Computer ScienceSoftware Engineering Laboratory
Problem
• How to compromising location privacy
in wireless networks using sensors with Limited Information ?
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Iowa State University Department of Computer ScienceSoftware Engineering Laboratory
Solution
• Step 1. Deploy sensors (spies) among wireless nodes to eavesdrop data– We know the position of deployed sensors
Nodes Nodes + Sensors
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Iowa State University Department of Computer ScienceSoftware Engineering Laboratory
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
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Iowa State University Department of Computer ScienceSoftware Engineering Laboratory
Solution
• Step 2. Use Principal Component Analysis (PCA) to estimate node numbers in this area
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Iowa State University Department of Computer ScienceSoftware Engineering Laboratory
Principal Component Analysis (PCA)
• An important statistics technique
511 grade
531 gradeMike
IQ
511 grade
531 grade
The first (principal) component
The second component
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Iowa State University Department of Computer ScienceSoftware Engineering Laboratory
Principal Component Analysis (PCA)
• This skill can be applied to 3 or more dimensional data
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Iowa State University Department of Computer ScienceSoftware Engineering Laboratory
What can we do with PCA?
• Suppose we draw a point for a time period...
Packet # of Sensor 1
[x,x,13,x,x,…]
Packet # of Sensor 2
Packet # of Sensor 3
138
6
[x,x,8,x,x,…]
[x,x,6,x,x,…]
The red point represents the 3rd time period’s data.
Its coordinate is(13,8,6)
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Iowa State University Department of Computer ScienceSoftware Engineering Laboratory
What can we do with PCA?
• Draw all points– Is there any hidden factor behind these data?
There are 2 wireless nodes in
this area !!
Yes! There are 2 hidden factors which greatly affect the data !!
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Iowa State University Department of Computer ScienceSoftware Engineering Laboratory
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
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Iowa State University Department of Computer ScienceSoftware Engineering Laboratory
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.
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Iowa State University Department of Computer ScienceSoftware Engineering Laboratory
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 1Node A Node B
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Iowa State University Department of Computer ScienceSoftware Engineering Laboratory
What can we do with BSS?
• Trick: We cut the whole area into many overlapped blocks
1
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Iowa State University Department of Computer ScienceSoftware Engineering Laboratory
What can we do with BSS?
• Trick: We cut the whole area into many overlapped blocks
2
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Iowa State University Department of Computer ScienceSoftware Engineering Laboratory
What can we do with BSS?
• Trick: We cut the whole area into many overlapped blocks
3
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Iowa State University Department of Computer ScienceSoftware Engineering Laboratory
What can we do with BSS?
• Trick: We cut the whole area into many overlapped blocks
4
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Iowa State University Department of Computer ScienceSoftware Engineering Laboratory
What can we do with BSS?
• Trick: We cut the whole area into many overlapped blocks
This square belongs to 4 blocks
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Iowa State University Department of Computer ScienceSoftware Engineering Laboratory
What can we do with BSS?
• For each block, we apply BSS to get many separated signals
[How are you]
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Iowa State University Department of Computer ScienceSoftware Engineering Laboratory
What can we do with BSS?
• For each block, we apply BSS to get many separated signals
[How are you][How or you]
{Cab sin}
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Iowa State University Department of Computer ScienceSoftware Engineering Laboratory
What can we do with BSS?
• For each block, we apply BSS to get many separated signals
[How are you][How or you]
{Cab sin}
[How are youth]
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Iowa State University Department of Computer ScienceSoftware Engineering Laboratory
What can we do with BSS?
• For each block, we apply BSS to get many separated signals
[How are you][How or you]
{Cab sin}
[How are youth] [haha you]
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Iowa State University Department of Computer ScienceSoftware Engineering Laboratory
What can we do with BSS?
• Cluster the separated signals together based on similarity
[How are you][How or you]
{Cab sin}
[How are youth] [haha you]
noise, ignore
Cluster 1
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Iowa State University Department of Computer ScienceSoftware Engineering Laboratory
What can we do with BSS?
• By analyzing the overlap of signals, we can estimate the position of them.
[How are you]
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Iowa State University Department of Computer ScienceSoftware Engineering Laboratory
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
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Iowa State University Department of Computer ScienceSoftware Engineering Laboratory
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
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Iowa State University Department of Computer ScienceSoftware Engineering Laboratory
Q & A