Iowa State University Department of Computer Science Software 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

Iowa State University Department of Computer Science Software Engineering Laboratory The Problem How to find out the positions of fixed wireless nodes?

Iowa State University Department of Computer Science Software 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?

Iowa State University Department of Computer Science Software Engineering Laboratory Naïve Solution 2 Directive sender If I don't’ have enough money to buy directive sensors?

Iowa State University Department of Computer Science Software Engineering Laboratory Problem How to compromising location privacy in wireless networks using sensors with Limited Information ?

Iowa State University Department of Computer Science Software Engineering Laboratory Solution Step 1. Deploy sensors (spies) among wireless nodes to eavesdrop data –We know the position of deployed sensors Nodes Nodes + Sensors

Iowa State University Department of Computer Science Software 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 seconds. I got 13 packets during the next 10 seconds. Control center

Iowa State University Department of Computer Science Software Engineering Laboratory Solution Step 2. Use Principal Component Analysis (PCA) to estimate node numbers in this area

Iowa State University Department of Computer Science Software Engineering Laboratory Principal Component Analysis (PCA) An important statistics technique 511 grade 531 grade Mike IQ 511 grade 531 grade The first (principal) component The second component

Iowa State University Department of Computer Science Software Engineering Laboratory Principal Component Analysis (PCA) This skill can be applied to 3 or more dimensional data

Iowa State University Department of Computer Science Software 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 [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)

Iowa State University Department of Computer Science Software 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 !!

Iowa State University Department of Computer Science Software 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

Iowa State University Department of Computer Science Software 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.

Iowa State University Department of Computer Science Software 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 1 Node A Node B

Iowa State University Department of Computer Science Software Engineering Laboratory What can we do with BSS? Trick: We cut the whole area into many overlapped blocks 1

Iowa State University Department of Computer Science Software Engineering Laboratory What can we do with BSS? Trick: We cut the whole area into many overlapped blocks 2

Iowa State University Department of Computer Science Software Engineering Laboratory What can we do with BSS? Trick: We cut the whole area into many overlapped blocks 3

Iowa State University Department of Computer Science Software Engineering Laboratory What can we do with BSS? Trick: We cut the whole area into many overlapped blocks 4

Iowa State University Department of Computer Science Software Engineering Laboratory What can we do with BSS? Trick: We cut the whole area into many overlapped blocks This square belongs to 4 blocks

Iowa State University Department of Computer Science Software Engineering Laboratory What can we do with BSS? For each block, we apply BSS to get many separated signals [How are you]

Iowa State University Department of Computer Science Software 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}

Iowa State University Department of Computer Science Software 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]

Iowa State University Department of Computer Science Software 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]

Iowa State University Department of Computer Science Software 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

Iowa State University Department of Computer Science Software Engineering Laboratory What can we do with BSS? By analyzing the overlap of signals, we can estimate the position of them. [How are you]

Iowa State University Department of Computer Science Software 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

Iowa State University Department of Computer Science Software 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

Iowa State University Department of Computer Science Software Engineering Laboratory Q & A