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Provable Unlinkability Against Traffic Analysis Ron Berman Joint work with Amos Fiat and Amnon Ta-Shma School of Computer Science, Tel-Aviv University.

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Presentation on theme: "Provable Unlinkability Against Traffic Analysis Ron Berman Joint work with Amos Fiat and Amnon Ta-Shma School of Computer Science, Tel-Aviv University."— Presentation transcript:

1 Provable Unlinkability Against Traffic Analysis Ron Berman Joint work with Amos Fiat and Amnon Ta-Shma School of Computer Science, Tel-Aviv University

2 Outline Is it interesting? Our contribution. Problem definition. What is unlinkability? Related work. The protocol. Proof sketch. Prior information. Application: Donor Anonymity.

3 Is it interesting? A tremendous amount of work on the subject. Many practical systems, protocols and solutions. Relevant today in the context of peer to peer data exchange.

4 Our Contribution A set of simple equivalent measurements for unlinkability. Rigorous analysis and proof using information theory. Solution (and proof) for prior knowledge.

5 Problem definition N nodes in a complete network graph. Synchronous network with bounds on message travel times. A public key infrastructure (PKI) is widely available. Given senders S={s 1 …s M } and receivers R={r 1 …r M } of messages, we would like the matching Π:S R to remain unknown to an adversary. At least some of the links are honest.

6 Problem definition Chaum (1981) had shown that using onion-routing, one can assume that the adversary is restricted to traffic analysis. The unlinkability properties hadnt been proven, and the original protocol is actually insecure. We heavily rely on Chaums ideas, with some limitations to the adversary.

7 What is unlinkability? Π - actual permutation that took place during communication. C - information the adversary has. 0/1 matrix, with 1 indicating a communication line being used Mutual information - I(X:Y) =H(X) + H(Y) - H(X,Y) How much info does one RV convey on another. All definitions are equivalent.

8 Chaumian-MIX –Unproven security. –Requires dummy traffic. –Not efficient. Dining Cryptographers –Proven security. –Not efficient (all players must play each round). –Requires shared randomness. –Requires broadcast. Related Work

9 Crowds –Proven weak security. Busses –Proven security. –Not efficient. Related Work AMPC –Proven weak security. –Not efficient. RS93 –Proven security. –Not efficient. –Requires secure computation.

10 The Protocol Forward: Alice chooses v 1 …v t-1 and sets v 0 =Alice, v T =Bob. Alice randomly chooses r 1 …r T return keys. Each onion layer i contains: –Address of next node en route (v i+1 ). –Return key r i saved by node i. –Unique identifier z i. –Encrypted onion part sent to v i+1. Message return is done in a similar way to Chaums.

11 Example R1R 2R2R 3R3R 4R4R 5R5R Our Protocol

12 Using the following chain rule, we can analyze the route of each player by itself: I(П:C)= I(П(1):C)+ I(П(2):C|П(1))+…α(N) The trick is to bound the amount of information the adversary has on each player. Proof Sketch

13 We would like to show that the communications pattern contains a lot of honest crossovers: And that these crossovers hide enough information Proof Sketch

14 We show how to find an embedding of a structure of crossovers in the actual communications pattern. We call this structure of crossovers - obscurant networks. Proof Sketch

15 Example embedding Proof Sketch

16 Obscurant Networks Network – layered directed circuit with same number of vertices on each layer. Crossover Network – Each vertex has in- degree and out-degree one or two. O i – The probability distribution of output when a pebble is put on starting vertex i. Proof Sketch 0.5 1

17 A network is ε-obscurant if |O i -U M |ε. Example: The butterfly network is 0- obscurant. The problem: what happens when log 2 (M) is not integer. We use two basic components: Proof Sketch B4B4 P4P4

18 Example Network Proof Sketch InitRepeat t=log(M)+log(ε -1 ) times Z=4 M=5 k=M-Z=1

19 Making sure we find an embedding Lemma [Alo01]: Let G=(V,E) be a graph and assume: then: Meaning: We have a probability of finding all-honest crossovers. Proof Sketch

20 Using the following chain rule, we can analyze the route of each player by itself: I(П:C)= I(П(1):C)+ I(П(2):C|П(1))+…α(N) The trick is to bound the amount of information the adversary has on each player. Proof Sketch

21 Prior Information Link each vertex v i (t) with v i (T-t), and reveal all data to the adversary if either one is adaptive. Effectively we have created a folding of the network: Proof Sketch

22 We receive the same game, with T/2 steps and f 2 probability of honest link. We show that: I(П (T) :C=(C 1,C 2 )) I(П (T/2) :C 1,C 2 ): Proof Sketch

23 Conclusion Theorem Assume our protocol runs in a network with N nodes, N(N-1)/2 communication links, some constant fraction of which are honest, then the protocol is α(n)- unlinkable when T(log(N)log 2 (N/α(n)).

24 Future Work Incomplete network graph. Malicious behavior. Multi-shot games. Dynamic network topology changes.

25 Applications More realistic approach – a link is honest some of the time. Donor privacy – the ability to donate items and answer requests, without being identified.

26 Questions?


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