Fixed servers are also problematic in terms of targeted at tacks that either

Fixed servers are also problematic in terms of

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Fixed servers are also problematic in terms of targeted at- tacks that either compromise the servers or disconnect them from the network. Algorand achieves better performance (confirming transactions in about a minute, reaching similar throughput) without having to choose a fixed set of servers ahead of time. Bitcoin-NG [ 26 ] suggests using the Nakamoto consensus to elect a leader, and then have that leader publish blocks of transactions, resulting in an order of magnitude of im- provement in latency of confirming transactions over Bitcoin. Hybrid consensus [ 31 , 33 , 43 ] refines the approach of using the Nakamoto consensus to periodically select a group of participants (e.g., every day), and runs a Byzantine agree- ment between selected participants to confirm transactions until new servers are selected. This allows improving perfor- mance over standard Nakamoto consensus (e.g., Bitcoin); for example, ByzCoin [ 33 ] provides a latency of about 35 sec- onds and a throughput of 230 KBytes/sec of data appended to the ledger with an 8 MByte block size and 1000 participants in the Byzantine agreement. Although Hybrid consensus makes the set of Byzantine servers dynamic, it opens up the possibility of forks, due to the use of proof-of-work consen- sus to agree on the set of servers; this problem cannot arise in Algorand. Pass and Shi’s paper [ 43 ] acknowledges that the Hybrid consensus design is secure only with respect to a “mildly adaptive” adversary that cannot compromise the selected servers within a day (the participant selection interval), and explicitly calls out the open problem of handling fully adap- tive adversaries. Algorand’s BA explicitly addresses this open problem by immediately replacing any chosen com- mittee members. As a result, Algorand is not susceptible to either targeted compromises or targeted DoS attacks. Stellar [ 37 ] takes an alternative approach to using Byzan- tine consensus in a cryptocurrency, where each user can trust quorums of other users, forming a trust hierarchy. Consis- tency is ensured as long as all transactions share at least one transitively trusted quorum of users, and sufficiently many of these users are honest. Algorand avoids this assumption, which means that users do not have to make complex trust decisions when configuring their client software. Proof of stake. Algorand assigns weights to users propor- tionally to the monetary value they have in the system, in- spired by proof-of-stake approaches, suggested as an alter- native or enhancement to proof-of-work [ 3 , 10 ]. There is a key difference, however, between Algorand using monetary value as weights and many proof-of-stake cryptocurrencies. In many proof-of-stake cryptocurrencies, a malicious leader (who assembles a new block) can create a fork in the network, but if caught (e.g., since two versions of the new block are signed with his key), the leader loses his money. The weights in Algorand, however, are only to ensure that the attacker cannot amplify his power by using pseudonyms; as long as the attacker controls less than 1/3 of the monetary value,
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  • Spring '19
  • NA
  • hash function, Cryptographic hash function, Algorand

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