Badri Nath Dept. of Computer Science/WINLAB Rutgers University Jointly with Wade Trappe, Yanyong Zhang WINLAB IAB meeting November, 2004

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1 Secure Localization Services Badri Nath Dept. of Computer Science/WINLAB Rutgers University Jointly with Wade Trappe, Yanyong Zhang WINLAB IAB meeting November, 24

2 Importance of localization Resource Allocation Location dependent Services Resource control Localization infrastructure Wireless/ Ad-hoc network

3 Importance of localization Resource allocation E.g., spectrum allocation Nodes in L1 use f1 Requests from floor2 should go to print2 L1 L2 Nodes in L2 use f2

4 Importance of localization Location dependent services Route to your nearest peer All items (assume have RFID tags) in Aisle1 is 1% off!!

5 Importance of localization Resource control Laptop cannot leave this building Secret.file can only be opened from this room Enforce location-dependent security policy

6 Secure Localization Security: Bad guys should not perturb your true location Am I really here? Are you really there? Security, Authentication Privacy: Bad guys should not know your true location I am not really here! Guess where I am! Marco

7 What is Localization? Goal: Determine the location of one or more wireless devices based on some form of measurements Useful measurements: Time of flight (TOA) Time difference of flight (TdOA) Energy of flight (DoA based on Signal Strength) Phase of flight (AoA = Angle of arrival from fixed stations) Perspective of flight (Visual Cues) Hop count to anchors: Correlated with distance Neighbor Location: Find regions

8 Use Neighbor Locations: Centroids Scenario: A set of anchor nodes with known locations are deployed as infrastructure for localization Wireless devices localize by calculating the centroid of the anchor points they hear: ( x1, y1) ( x 4, y4) x1 + x 2 + L + x n y1 + y 2 + L + y xˆ, ŷ) =, n n ( n ( x 2, y2) ( x3, y3) ( x5, y5)

9 Signal Strength Underlying Principle: Signal strength (RSSI) is a function of distance Use known landmark locations and RSSI-Distance relationship to setup a least squares problem or have a mappings that can determine location from potential signal strength readings from know anchors (access points). A1, S1; A2, S2; A3 S3 x,y

10 Localization :Hop-Count Methods DV-hop localization algorithm: Obtain the hop counts between a sensor node and several locators. L 1 A L 2 Translate hop counts to actual distance. L 3 Localize using triangulation. It is critical to obtain the correct hop counts between sensor nodes and every locator.

11 Attacks on Localization Most security and privacy issues for wireless networks are best addressed through cryptography and network security End of Day Analysis: Not all security issues can be addressed by cryptography! Non-cryptographic attacks on wireless localization: Adversaries may affect the measurements used to conduct localization Adversaries may physically pick up and move devices Adversaries may alter the physical medium (adjust propagation speed, introduce smoke, etc.) Adversaries can shorten routing path (hop count) Many, many more crazy attacks

12 Signal Strength Attack on Localization Signal strength wireless localization are susceptible to power-distance uncertainty relationships Adversary may: Alter transmit power of nodes Remove direct path by introducing obstacles Introduce absorbing or attenuating material Introduce ambient channel noise Power Received Transmit Power Uncertainty d 1 d 2 Location Uncertainty Distance

13 Defenses for Wireless Localization Multimodal Localization: Most localization techniques employ a single property Adversary only has to attack one-dimension!!! Defense Strategy: Make the adversary have to attack several properties simultaneously Example: Do signal strength measurements correspond to TOF measurements? Robust Statistical Methods: Defense Strategy: Ignore the wrong values introduced by adversaries Develop robust statistical estimation algorithms and data cleansing methods Interesting behavior: Its best for the adversary not to be too aggressive!

14 Least median squares Least squares Least median squares = + = N i i i i y x d y y x x y x ), ( ) ) ( ) ( ( min arg ) ˆ, ( ˆ ), ( ) ) ( ) ( arg min med( ) ˆ, ( ˆ i i i y x d y y x x y x + =

15 Attacks on Hop-Count Methods L hop_count (L->A) = 3 wormhole L hop_count (L->A) = 7 A A L hop_count (L->A) = 1 jammed area A

16 Spatial challenge-response What else do you see test? Each node asked to ping a random set of trusted nodes Estimate of hop count can eliminate false readings L A

17 Conclusion and Remarks Wireless localization algorithms are important to future location-based services Many strategies to cope with the effects of attacks on localization Multimodal Localization Robust Statistical Localization Spatial challenge-response

18 Future Secure localization offered as service Software, hardware, firmware support You are at I am at SLS inside

19 Related work New Field: Securing Wireless Localization Secure Verification of Location Claims, Sastry and Wagner Secure Positioning in Sensor Networks, S. Capkun and J.P. Hubaux SeRLoc: Secure range-independent localization for wireless networks, L. Lazos and R. Poovendran Securing Wireless Localization: Living with Bad Guys, Z. Li, Y. Zhang, W. Trappe and B. Nath (expanded version under submission)

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