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Lightweight Trust Propagation for Mobile Reputation Systems

This research explores a new approach for propagating trust in mobile reputation systems to combat content overload and accept content only from reputable sources. The proposed method involves building a trust graph and defining a function that rates the trust relationships between nodes.

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Lightweight Trust Propagation for Mobile Reputation Systems

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  1. Lightweight DistributedTrust Propagation(daniele quercia & stephen hailes & licia capra) UCL

  2. What I do...

  3. Research @ ...

  4. What I research...

  5. Reputation Systems for Mobiles

  6. Daniele Quercia Situation: People exchange digital content

  7. Daniele Quercia Problem: Content overload

  8. Daniele Quercia Proposal:Accept content onlyfrom reputable people

  9. Daniele Quercia Take two devices… A B

  10. Daniele Quercia Shall I accept content from B? A B

  11. Daniele Quercia A should set its initial trust for B A B

  12. Daniele Quercia A should set its initial trust for B A B Yes, but how?

  13. Daniele Quercia • Traditional way: • Trust propagation C ? A B

  14. Daniele Quercia • That way works on the Web and has been tested on “binary” ratings

  15. Daniele Quercia • If that way is tested on • 3-level ratings

  16. Conclusion:A needs a new way for propagating its trust in B

  17. Conclusion:A needs a new way for propagating its trust in B But which way?

  18. Our proposal

  19. Daniele Quercia AB AC CB C 1 2 ? A B

  20. Daniele Quercia AB AC CB 1 2 Put trust relationships in a new graph & label graph nodes ? C 1 2 ? A B

  21. Daniele Quercia AB AC CB 1 2 Define a “good” function that rates AB Put trust relationships in a new graph & label graph nodes ? C 1 f 2 ? A B

  22. Daniele Quercia AB AC CB 1 2 find_f build_graph(trust_relationships, AB) ? C 1 f 2 ? A B

  23. <build_graph>

  24. ? A B 1 A  B 1 0.5 1 2 3 ? ? 2 D C M M 1 2 3

  25. ? A B 1 A  B 1 0.5 1 2 3 ? ? 2 D C M M 1 2 3 What are those ?

  26. Remember, we’ll define f We will see that frates neighbouring nodes alike It’s a neighbour of AB; therefore, it rates as AB does ?

  27. Remember, we’ll define f We will see that frates neighbouring nodes alike It’s a neighbour of AB; therefore, it rates as AB does ? Find relationships that rate as AB does

  28. Remember, we’ll define f We will see that frates neighbouring nodes alike It’s a neighbour of AB; therefore, it rates as AB does ?

  29. 2 Types of those relationships

  30. 1. The relationships with same rater (A) A B 1 2 3 2 D C 1 As long as B and Dbehave alike

  31. 2. The relationships with same rated node (B) A B 1 2 3 2 D C 1 As long as A and Crate alike

  32. OK, 2 Types

  33. Taking those relationships, one comes up with …

  34. …a graph! A  C 1 A  B 0.5 1 A  D C  B M M 2 3

  35. </build_graph>

  36. <find_f>

  37. A  C 1 A  B 0.5 1 A  D C  B M M 2 3

  38. Take f that returns • the ratings already there ( ) • & similar ratings for neighbouring nodes A  C 1 A  B 0.5 1 A  D C  B M M 2 3 2 3

  39. More formally, …

  40. We find f that minimizes that loss!

  41. </find_f>

  42. Daniele Quercia AB AC CB 1 2 find_f build_graph ? C 1 f 2 ? A B

  43. Does it work? Useful, Robust, Fast, “Light”?

  44. Daniele Quercia • Useful? Tested on real data • (Advogato: > 55K user ratings)

  45. Daniele Quercia • Useful? Tested on real data • (Advogato: > 55K user ratings)

  46. Daniele Quercia Robust?

  47. Daniele Quercia Robust?

  48. Daniele Quercia Fast and “Light”?

  49. Daniele Quercia Fast and “Light”? • For propagating AB • (worst case) • Transmit 30KB • & run for 2.8ms

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