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Attacking Residential Wireless Ubiquitous systems
* Residential wireless ubiquitous systems that track Activities of Daily Living are growing in number
o Elderly monitoring: University of Virginia’s ALARMNET, Harvard’s CodeBlue
o Home security / automation: 5 million X10 systems in the US
* We present a new wireless snooping attack that infers surprisingly detailed daily activities of residents such as Showering and Cooking in spite of encryption
o On existing and future systems around the world including possibly your home
* We present privacy preserving guidelines to protect your activity details from this attack
FATS Attack – Fingerprint And Timing-based Snoop attack
* Input: Series of (Timestamp,Fingerprint) pairs
* Wireless Fingerprinting
o Uses Physical Characteristics of transmissions to differentiate radio sources
o Demonstrated on WiFi radios, Bluetooth radios and the mica mote’s CC1000 radios
FATS Attack – Fingerprint And Timing-based Snoop attack
* Output: Activities of Daily Living (ADLs) inferred by FATS Inference Algorithm:
o Sleeping, Home Occupancy
o Bathroom and Kitchen Visits
o Bathroom Activities: Showering, Toileting, Washing
o Kitchen Activities: Cooking hot and cold food
* High level medical information inference possible
* HIPAA requires healthcare providers to protect this information
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