Consensus by committee BA achieves scalability bychoosing a committeea small

Consensus by committee ba achieves scalability

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Consensus by committee. BA achieves scalability by choosing a committee—a small set of representatives ran- domly selected from the total set of users—to run each step of its protocol. All other users observe the protocol mes- sages, which allows them to learn the agreed-upon block. BA chooses committee members randomly among all users based on the users’ weights. This allows Algorand to ensure that a sufficient fraction of committee members are honest. However, relying on a committee creates the possibility of targeted attacks against the chosen committee members. Cryptographic sortition. To prevent an adversary from targeting committee members, BA selects committee mem- bers in a private and non-interactive way. This means that every user in the system can independently determine if they are chosen to be on the committee, by computing a func- tion (a VRF [ 39 ]) of their private key and public information from the blockchain. If the function indicates that the user is chosen, it returns a short string that proves this user’s committee membership to other users, which the user can include in his network messages. Since membership selec- tion is non-interactive, an adversary does not know which user to target until that user starts participating in BA . Participant replacement. Finally, an adversary may tar- get a committee member once that member sends a message in BA . BA mitigates this attack by requiring committee members to speak just once. Thus, once a committee member sends his message (exposing his identity to an adversary), the committee member becomes irrelevant to BA . BA achieves this property by avoiding any private state (except for the user’s private key), which makes all users equally capable of participating, and by electing new committee members for each step of the Byzantine agreement protocol. We implement a prototype of Algorand and BA , and use it to empirically evaluate Algorand’s performance. Experi- mental results running on 1,000 Amazon EC2 VMs demon- strate that Algorand can confirm a 1 MByte block of transac- tions in 22 seconds with 50,000 users, that Algorand’s la- tency remains nearly constant when scaling to half a million users, that Algorand achieves 125 × the transaction through- put of Bitcoin, and that Algorand achieves acceptable latency even in the presence of actively malicious users. 2 RELATED WORK Proof-of-work. Bitcoin [ 42 ], the predominant cryptocur- rency, uses proof-of-work to ensure that everyone agrees on the set of approved transactions; this approach is of- ten called “Nakamoto consensus.” Bitcoin must balance the length of time to compute a new block with the possibil- ity of wasted work [ 42 ], and sets parameters to generate a new block every 10 minutes on average. Nonetheless, due to the possibility of forks, it is widely suggested that users wait for the blockchain to grow by at least six blocks be- fore considering their transaction to be confirmed [7]. This means transactions in Bitcoin take on the order of an hour to be confirmed. Many follow-on cryptocurrencies adopt Bitcoin’s proof-of-work approach and inherit its limitations.
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  • Spring '19
  • NA
  • hash function, Cryptographic hash function, Algorand

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