1. Group Key Distribution Chih-Hao Huang huang@cs.umn.edu

2. Paper List C.K.Wong et al: Secure Group Communications Using Key Graphs M.Waldvogel et al: the VersaKey Framework D.McGrew and A.T.Sherman: Key Establishment in Large Dynamic Groups Using One-way Function Trees

3. Introduction Secure group communication Pay-per-view video streaming Video On Demand (VOD) Secure teleconferencing Online games

4. Secure Group Communication Authorization Secure Multicasting Forward confidentiality (revocation) Backward confidentiality

5. Secure Group Multicasting u u2u2 u1u1

6. Our Assumptions Each node shares a Key Encryption Key with GC to encrypt TEK updates All nodes share a Traffic Encryption Key (TEK) to encrypt communication data. There is a Group Controller (GC) When membership changes, TEK needs to be updated

7. Traffic Encryption Key u A Group of Users E TEK (msg) u sends a message encrypted with TEK

8. Key Encryption Key u

9. u KEKs are used to encrypt TEK updates

10. An Easy Re-keying Scheme : Star-shaped Each user shares a secret KEK with GC When a user joins or leaves, GC sends each node a re-keying message encrypted with its own KEK

11. Star-shaped Re-keying Scheme : Join GC u u wants to join the group

12. Star-shaped: Join (Cont ’ d) GC u GC sends encrypted TEK to other nodes

13. Star-shaped: Leave GC u U tells GC that he’s leaving

14. Star-shaped: Leave (Cont ’ d) GC u GC sends encrypted TEK to other nodes

15. Analysis of Star- shaped Scheme Pros: Easy to implement Provides both forward and backward confidentiality Cons: Doesn't scale well ~ Θ(n) Oooooops!

16. Logical Key Hierarchy Proposed by C.K.Wong, M.Gouda, and S.S.Lam It provides both forward and backward confidentiality It scales well ~ Θ(logn)

17. LKH: Key Graphs u-nodes are real users k-nodes represent keys u knows k if there ’ s a path from u to k

18. LKH: Join u 9 is about to join the group

19. LKH: Leave u 9 is about to leave the group

20. Analysis of LKH Re-keying messages are sent in a top- down fashion Complexity depends on the tree height, Θ(logn) Some options may be used: user- oriented, key-oriented, and group- oriented re-keying

21. User, Key, or Group? User-oriented re-keying is nothing more than grouping re-keying messages by users ~ less but bigger messages Key-oriented re-keying is just grouping them by keys ~ more but smaller messages Group-oriented is putting all re-keying messages together to generate a big, fat message ~ only one gigantic message

22. An Improvement: LKH+ Proposed by M.Waldvogel et al in “ The VersaKey Framework ” They use a one-way function to update TEK when a ‘ join ’ happens

23. LKH+: Join When u 9 joins, u 1 ~ u 8 feed the KEK into a one-way hash function to do the update

24. Analysis of LKH+ GC doesn't need to send re-keying messages when a join happens When a join happens, every member can compute the new TEK locally The newly joined member cannot compute the old TEK ~ backward confidentiality

25. Centralized Flat Key Management Proposed by M.Waldvogel et al as well Another logical tree- based re-keying scheme It greatly reduces GC ’ s storage requirement

26. Flat Key Table TEK ID Bit #0 KEK 0.0KEK 0.1 ID Bit #1 KEK 1.0KEK 1.1 ID Bit #2 KEK 2.0KEK 2.1 ID Bit #3 KEK 3.0KEK 3.1 Bit’s Value=0Bit’s Value=1 GC maintains the following table

27. Flat Key Management TEK ID Bit #0 KEK 0.0KEK 0.1 ID Bit #1 KEK 1.0KEK 1.1 ID Bit #2 KEK 2.0KEK 2.1 ID Bit #3 KEK 3.0KEK 3.1 Bit’s Value=0Bit’s Value=1 Node 0110 knows highlighted KEKs

28. CFKM: Join Node #1101 is about to join the group

29. CFKM: Join GC first sends it the new TEK and highlighted KEKs TEK ID Bit #0 KEK 0.0KEK 0.1 ID Bit #1 KEK 1.0KEK 1.1 ID Bit #2 KEK 2.0KEK 2.1 ID Bit #3 KEK 3.0KEK 3.1 Bit’s Value=0Bit’s Value=1

30. CFKM: Join GC then encrypts new TEK with the complementary KEKs (the highlighted ones) TEK ID Bit #0 KEK 0.0KEK 0.1 ID Bit #1 KEK 1.0KEK 1.1 ID Bit #2 KEK 2.0KEK 2.1 ID Bit #3 KEK 3.0KEK 3.1 Bit’s Value=0Bit’s Value=1

31. CFKM: Join GC then broadcasts these message to everybody Since other nodes differ from it in at least 1 position, they can decrypt the re- keying message and get the updated TEK

32. CFKM: Leave Node 1010 is about to leave TEK ID Bit #0 KEK 0.0KEK 0.1 ID Bit #1 KEK 1.0KEK 1.1 ID Bit #2 KEK 2.0KEK 2.1 ID Bit #3 KEK 3.0KEK 3.1 Bit’s Value=0Bit’s Value=1

33. CFKM: Leave GC sends everybody a new TEK encrypted with complementary KEKs TEK ID Bit #0 KEK 0.0KEK 0.1 ID Bit #1 KEK 1.0KEK 1.1 ID Bit #2 KEK 2.0KEK 2.1 ID Bit #3 KEK 3.0KEK 3.1 Bit’s Value=0Bit’s Value=1

34. CFKM: Leave (Cont ’ d) Similarly, since other nodes differ from it in at least 1 position, they can decrypt the re-keying message and get the updated TEK Now, all KEKs known by the leaving node become invalid and need to be updated

35. CFKM: Leave (Cont ’ d) For each of the invalid KEKs, GC selects a new replacement encrypted with both the old KEK and the new TEK For those who are not supposed to know the replacement KEKs, they cannot decrypt the message as they don ’ t know the old value

36. CFKM: Leave (Cont ’ d) For each of the invalid KEKs, GC selects a new replacement encrypted with both the old KEK and the new TEK The evicted node cannot decrypt the message either, as it doesn't know the new TEK

37. CFKM: Pros and Cons Pros: It greatly reduces GC ’ s memory requirement ~ only one table needed It maintains the same logarithmic bound as LKH, LKH+ ~ it ’ s efficient Cons: Removal of multiple nodes

38. CFKM: Multiple Leaves Node 1001 and 0110 are leaving … TEK ID Bit #0 KEK 0.0KEK 0.1 ID Bit #1 KEK 1.0KEK 1.1 ID Bit #2 KEK 2.0KEK 2.1 ID Bit #3 KEK 3.0KEK 3.1 Bit’s Value=0Bit’s Value=1

39. One-way Function Trees Proposed by D.A.McGrew and A.T.Sherman Logical tree-based scheme as well Even it ’ s still of logarithmic bound, the coefficient is smaller than LKH

40. Structure of OFT f k left k right unblinded key gg f(g(k left ),g(k right )) G is one-way

41. Blinded & Unblinded Keys Unblinded Key: the value that hasn ’ t been passed though g Blinded Key: the value that has already been passed though g If you know the unblinded key, you can compute the blinded key The converse is not true

42. OFT Algorithm Each member knows the blinded keys which are siblings to its path to the root Each member knows its unblinded key Each member can then compute the key of the root, which is the TEK (root maintains only one key)

43. OFT Algorithm (Cont ’ d) Node u knows the blinded keys of all green nodes u

44. OFT: Join/Leave If a blinded key changes, its new value must be communicated to all members who store it For a join/leave operation, Θ(logn) nodes need to update the blinded keys, where n is the distance to the root

45. OFT: Join/Leave (Cont ’ d) If u wants to join, all green nodes must update blinded keys u

46. Analysis of OFT OFT has the same log-bound as LKH LKH ’ s leading coefficient is 2 (binary), since updates must be sent to both children along the path to the root OFT ’ s leading coefficient is 1, since updates has only to be sent to the sibling along the path to the root

47. Why OFT is better? If u wants to leave, then only the green nodes need to be updated The blue nodes can always compute the blinded key locally u

48. Conclusion Star-shaped: most na ï ve approach, no scalability LKH: the basic of everything, good performance and functionality LKH+: a slight improvement of LKH CFKM: reducing GC ’ s storage need OFT: best of all algorithms so far