PhyCloak: Obfuscating Sensing from Communication Signals

Recognition of human activities and gestures using preexisting WiFi signals has been shown to be feasible in recent studies. Given the pervasiveness of WiFi signals, this emerging sort of sensing poses a serious privacy threat. This paper is the first to counter the threat of unwanted or even malicious communication based sensing: it proposes a blackbox sensor obfuscation technique PhyCloak which distorts only the physical information in the communication signal that leaks privacy. The data in the communication signal is preserved and, in fact, the throughput of the link is increased with careful design. Moreover, the design allows coupling of the Phy-Cloak module with legitimate sensors, so that their sensing is preserved, while that of illegitimate sensors is obfuscated. The effectiveness of the design is validated via a prototype implementation on an SDR platform.

[1]  I. Bilik,et al.  Radar target classification using doppler signatures of human locomotion models , 2007, IEEE Transactions on Aerospace and Electronic Systems.

[2]  Ljubisa Stankovic,et al.  Analysis of radar micro-Doppler signatures from experimental helicopter and human data , 2007 .

[3]  Byung-Kwon Park,et al.  Arctangent Demodulation With DC Offset Compensation in Quadrature Doppler Radar Receiver Systems , 2007, IEEE Transactions on Microwave Theory and Techniques.

[4]  Hao Ling,et al.  Human activity classification based on micro-Doppler signatures using an artificial neural network , 2008, 2008 IEEE Antennas and Propagation Society International Symposium.

[5]  Ming-Chung Fang,et al.  Application of SVD noise-reduction technique to PCA based radar target recognition , 2008 .

[6]  J.A. Nanzer,et al.  Bayesian Classification of Humans and Vehicles Using Micro-Doppler Signals From a Scanning-Beam Radar , 2009, IEEE Microwave and Wireless Components Letters.

[7]  Youngwook Kim,et al.  Human Activity Classification Based on Micro-Doppler Signatures Using a Support Vector Machine , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[8]  Victor C. Chen,et al.  Analysis of radar human gait signatures , 2010 .

[9]  K.-C. Lee APPLICATION OF ICA TECHNIQUE TO PCA BASED RADAR TARGET RECOGNITION , 2010 .

[10]  Karl Woodbridge,et al.  Radar Micro-Doppler Signature Classification using Dynamic Time Warping , 2010, IEEE Transactions on Aerospace and Electronic Systems.

[11]  They can hear your heartbeats: non-invasive security for implantable medical devices , 2011, SIGCOMM.

[12]  Sachin Katti,et al.  Flashback: decoupled lightweight wireless control , 2012, SIGCOMM.

[13]  Shwetak N. Patel,et al.  Whole-home gesture recognition using wireless signals , 2013, MobiCom.

[14]  Fadel Adib,et al.  See through walls with WiFi! , 2013, SIGCOMM.

[15]  Ramarathnam Venkatesan,et al.  Dhwani: secure peer-to-peer acoustic NFC , 2013, SIGCOMM.

[16]  Sachin Katti,et al.  Full duplex radios , 2013, SIGCOMM.

[17]  Vinit Rajan Kizhakkel PULSED RADAR TARGET RECOGNITION BASED ON MICRO-DOPPLER SIGNATURES USING WAVELET ANALYSIS , 2013 .

[18]  Yasamin Mostofi,et al.  Cooperative Wireless-Based Obstacle/Object Mapping and See-Through Capabilities in Robotic Networks , 2013, IEEE Transactions on Mobile Computing.

[19]  Sachin Katti,et al.  FastForward , 2014, SIGCOMM.

[20]  Anish Arora,et al.  String Kernels for Complex Time-Series: Counting Targets from Sensed Movement , 2014, 2014 22nd International Conference on Pattern Recognition.

[21]  Jie Yang,et al.  E-eyes: device-free location-oriented activity identification using fine-grained WiFi signatures , 2014, MobiCom.

[22]  Yasamin Mostofi,et al.  An Integrated Framework for Obstacle Mapping With See-Through Capabilities Using Laser and Wireless Channel Measurements , 2014, IEEE Sensors Journal.

[23]  Anish Arora,et al.  A regression-based radar-mote system for people counting , 2014, 2014 IEEE International Conference on Pervasive Computing and Communications (PerCom).

[24]  Swarun Kumar,et al.  Accurate indoor localization with zero start-up cost , 2014, MobiCom.

[25]  Wei Wang,et al.  Keystroke Recognition Using WiFi Signals , 2015, MobiCom.

[26]  Bo Chen,et al.  Tracking Keystrokes Using Wireless Signals , 2015, MobiSys.

[27]  Ness B. Shroff,et al.  Scheduling in wireless networks with full-duplex cut-through transmission , 2015, 2015 IEEE Conference on Computer Communications (INFOCOM).

[28]  Bo Chen,et al.  FlexRadio: Fully Flexible Radios and Networks , 2015, NSDI.

[29]  Wei Wang,et al.  Understanding and Modeling of WiFi Signal Based Human Activity Recognition , 2015, MobiCom.

[30]  Ben Y. Zhao,et al.  Reusing 60GHz Radios for Mobile Radar Imaging , 2015, MobiCom.

[31]  Bo Chen,et al.  AirExpress: Enabling Seamless In-band Wireless Multi-hop Transmission , 2015, MobiCom.

[32]  Kaishun Wu,et al.  We Can Hear You with Wi-Fi! , 2014, IEEE Transactions on Mobile Computing.