Sybil Attacks Against Mobile Users

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"Sybil Attacks Against Mobile Users: Friends and Foes to the Rescue". Presentation at INFOCOM 2010 of this paper
http://eprints.ucl.ac.uk/18812/1/18812.pdf

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  • U use EBAY. In my research
  • People in a train, with their phones, willing to share pics/videos That is because…
  • Fast!!!
  • [slow down] one the way back home they are willing to share pic/videos
  • [pause]
  • Too much content around. My phone doesn’t know from whom to download pixcs/videos One of the solutions is the proposal of my phd
  • For the last 3 years I’ve been thinking how to do that Thumbs up/ down -> ratings -> to aututomatically select reputable people And, for 3 years, I;’ve been thinking about just 2 things….
  • How to store And how to use Period. That’s what I was doing all day long for 3 years My dayhob paid by you guys was to dayfream and come up with ideas on how … My goal: [hand] is to presents two papers.
  • [pause] Le’ts start with the first problem
  • Sybil Attacks Against Mobile Users

    1. 1. _ _
    2. 2. I did my PhD @
    3. 3. U niversity C ollege L ondon
    4. 4. <PhD>
    5. 5. Ratings on ...
    6. 6. Ratings on phones
    7. 7. Why ratings on mobiles?
    8. 8. Situation : People exchange digital content
    9. 9. People
    10. 13. The problem is ...
    11. 14. drowning user (content overload) help! who will come to the rescue?
    12. 15. Proposal: Accept content only from reputable people
    13. 16. Use Store
    14. 17. Use Store MobiRate [Ubicomp08]
    15. 18. Use Store LDTP [ICDM07] MobiRate [Ubicomp08]
    16. 19. MobID
    17. 20. Collaborative applications: track trustworthiness of IDs
    18. 21. one misbehaves & creates bogus identities (goes untraceable)
    19. 22. Traditional Solutions
    20. 23. pki
    21. 24. p2p socnet fast mixing & no churn
    22. 25. 1. u’ve got friends: honest & key-enabled! 2. u don’t move randomly 3. homophily: P(honest  honest)=HIGH assumptions
    23. 26. “ A meets B” @A: 1. B &co. into its network 2. rank B 3. accept/reject B
    24. 31. device keeps 2 nets & reasons on them
    25. 33. 1. B &co. into networks 2. 2 ranks for B 3. accept/reject B 4. update networks` “ A meets B”
    26. 34. GoodRank BadRank B C D E F G L M N O P
    27. 35. GoodRank BadRank B C D E F G L M N O P
    28. 36. Does it work?
    29. 42. issue 1: social exclusion
    30. 43. MobID + FriendSensing
    31. 44. FriendSensing ((.))
    32. 46. Keep Bluetooth on (record who is around)
    33. 47. Upload records
    34. 48. People you may know
    35. 49. People You May Know Forrest Gump Bambie Barack Obama Add to Friends Add to Friends Add to Friends
    36. 50. MobID + FriendSensing
    37. 51. If you are looking for Kinky boots issue 2
    38. 52. whether you are …
    39. 53. a woman…
    40. 54. or a man a woman…
    41. 55. Thorny problem:
    42. 56. … or a woman… How to keep it secret

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