10 research outputs found
Compression from Collisions, or Why CRHF Combiners Have a Long Output
A black-box combiner for collision resistant hash functions (CRHF)
is a construction which given black-box access to two hash functions is
collision resistant if at least one of the components is
collision resistant.
In this paper we prove a lower bound on the output length of black-box
combiners for CRHFs. The bound we prove is basically tight as it is
achieved by a recent construction of Canetti et al [CRYPTO'07]. The
best previously known lower bounds only ruled out a very restricted
class of combiners having a very strong security reduction: the
reduction was required to output collisions for both underlying
candidate hash-functions given a single collision for the combiner
(Canetti et al [CRYPTO'07] building on Boneh and Boyen [CRYPTO'06] and
Pietrzak [EUROCRYPT'07]).
Our proof uses a lemma similar to the elegant ``reconstruction lemma''
of Gennaro and Trevisan [FOCS'00], which states that any function
which is not one-way is compressible (and thus uniformly random
function must be one-way). In a similar vein we show that a function
which is not collision resistant is compressible. We also borrow
ideas from recent work by Haitner et al. [FOCS'07], who show that one
can prove the reconstruction lemma even relative to some very powerful
oracles (in our case this will be an exponential time
collision-finding oracle)
Leakage-Resilient Cryptography
We construct a stream-cipher SC whose \emph{implementation} is secure even if arbitrary (adversely chosen) information on the internal state of SC is leaked during computation. This captures \emph{all} possible side-channel attacks on SC where the amount of information leaked in a given period is bounded, but overall cankbe arbitrary large, in particular much larger than the internalkstate of SC. The only other assumption we make on the \emph{implementation} of SC is that only data that is accessedkduring computation leaks information. The construction can be based on any pseudorandom generator, and the only computational assumption we make is that this PRG is secure against non-uniform adversaries in the classical sense (i.e. when there are no side-channels).
The stream-cipher SC generates its output in chunks , and arbitrary but bounded information leakage is modeled by allowing the adversary to adaptively chose a function before is computed, she then gets where is the internal state of \SC that is accessed during the computation of . One notion of security we prove for \SC is that is indistinguishable from random when given , and also the complete internal state of SC after has been computed (i.e. our cipher is forward-secure).
The construction is based on alternating extraction (previously used in the intrusion-resilient secret-sharing scheme from FOCS'07). We move this concept to the computational setting by proving a lemma that states that the output of any PRG has high HILL pseudoentropy (i.e. is indistinguishable from some distribution with high min-entropy) even if arbitrary information about the seed is leaked. The amount of leakage \leak that we can tolerate in each step depends on the strength of the underlying PRG, it is at least logarithmic, but can be as large as a constant fraction of the internal state of SC if the PRG is exponentially hard
Hide & Seek: Privacy-preserving rebalancing onΒ payment channel networks
Payment channels effectively move the transaction load off-chain thereby successfully addressing the inherent scalability problem most cryptocurrencies face. A major drawback of payment channels is the need to βtop upβ funds on-chain when a channel is depleted. Rebalancing was proposed to alleviate this issue, where parties with depleting channels move their funds along a cycle to replenish their channels off-chain. Protocols for rebalancing so far either introduce local solutions or compromise privacy. In this work, we present an opt-in rebalancing protocol that is both private and globally optimal, meaning our protocol maximizes the total amount of rebalanced funds. We study rebalancing from the framework of linear programming. To obtain full privacy guarantees, we leverage multi-party computation in solving the linear program, which is executed by selected participants to maintain efficiency. Finally, we efficiently decompose the rebalancing solution into incentive-compatible cycles which conserve user balances when executed atomically
Wiser: Increasing throughput in Payment Channel Networks with transaction aggregation
Payment channel networks (PCNs) are one of the most prominent solutions to the limited transaction throughput of blockchains. Nevertheless, PCNs suffer themselves from a throughput limitation due to the capital constraints of their channels. A similar dependence on high capital is also found in inter-bank payment settlements, where the so-called netting technique is used to mitigate liquidity demands.
In this work, we alleviate this limitation by introducing the notion of transaction aggregation: instead of executing transactions sequentially through a PCN, we enable senders to aggregate multiple transactions and execute them simultaneously to benefit from several amounts that may "cancel out". Two direct advantages of our proposal is the decrease in intermediary fees paid by senders as well as the obfuscation of the transaction data from the intermediaries.
We formulate the transaction aggregation as a computational problem, a generalization of the Bank Clearing Problem. We present a generic framework for the transaction aggregation execution, and thereafter we propose Wiser as an implementation of this framework in a specific hub-based setting. To overcome the NP-hardness of the transaction aggregation problem, in Wiser we propose a fixed-parameter linear algorithm for a special case of transaction aggregation as well as the Bank Clearing Problem. Wiser can also be seen as a modern variant of the Hawala money transfer system, as well as a decentralized implementation of the overseas remittance service of Wise