|COOKIES: By using this website you agree that we can place Google Analytics Cookies on your device for performance monitoring.|
Detecting Sybil attacks and recommending social contacts from proximity records
If you have a question about this talk, please contact Eiko Yoneki.
I’ll present two algorithms called MobID1 and FriendSensing2. Using short-range technologies (e.g., Bluetooth) on their mobile phones, users keep track of other phones in their proximity. Upon proximity records, MobID identifies Sybil attackers in a decentralized way, and FriendSensing recommends social contacts:
- The idea behind MobID is that a device manages two small networks in which it stores information about the devices it meets: its network of friends contains honest devices, and its network of foes contains suspicious devices. By reasoning on these two networks, the device is then able to determine whether an unknown individual is carrying out a Sybil attack or not.
- FriendSensing processes proximity records using a variety of algorithms that are based on social network theories of geographical proximity and of link prediction. It then returns a personalized and automatically generated list of people the user may know. We’ll see how both algorithms perform against real mobility and social network data.
 Sybil Attacks Against Mobile Users: Friends and Foes to the Rescue. Infocom ‘10
 FriendSensing: Recommending Friends Using Mobile Phones. RecSys ‘09
This talk is part of the Computer Laboratory Systems Research Group Seminar series.
This talk is included in these lists:
Note that ex-directory lists are not shown.
Other listsINTP Forum DAK Group Meetings BCS East Anglia
Other talksThe role of macrophages in tumour progression and metastasis Sparking the Inferno with "the Girl on Fire": Uncovering the Conservative Underpinnings of the YA Dystopian Heroine Growth spurting baby galaxies Underground laboratories for geological disposal research Sustainable cities in an uncertain future An Enlightenment tradition of characterising and caricaturing science and scientists: why words (and nerds) matter.