It is impossible for a user to wait exactly the correct amount for the first

# It is impossible for a user to wait exactly the

• Notes
• 18

This preview shows page 7 - 9 out of 18 pages.

It is impossible for a user to wait exactly the correct amount for the first two steps of the above scenario. Thus, Algorand estimates these quantities ( λ stepvar , the variance in how long it takes different users to finish the last step of BA , and λ priority , the time taken to gossip the priority and proof message), and waits for λ stepvar + λ priority time to identify the highest priority. §10 experimentally shows that these parameters are, conservatively, 5 seconds each. As mentioned above, Algorand would remain safe even if these estimates were inaccurate. Malicious proposers. Even if some block proposers are malicious, the worst-case scenario is that they trick different Algorand users into initializing BA with different blocks. This could in turn cause Algorand to reach consensus on an empty block, and possibly take additional steps in doing so. However, it turns out that even this scenario is relatively unlikely. In particular, if the adversary is not the highest pri- ority proposer in a round, then the highest priority proposer will gossip a consistent version of their block to all users. If the adversary is the highest priority proposer in a round, they can propose the empty block, and thus prevent any real transactions from being confirmed. However, this happens with probability of at most 1 h , by Algorand’s assumption that at least h > 2 / 3 of the weighted user are honest. 7 BA The execution of BA consists of two phases. In the first phase, BA reduces the problem of agreeing on a block to agreement on one of two options. In the second phase, BA reaches agreement on one of these options: either agreeing on a proposed block, or agreeing on an empty block. 7
Each phase consists of several interactive steps ; the first phase always takes two steps, and the second phase takes two steps if the highest-priority block proposer was honest (sent the same block to all users), and as we show in our analysis an expected 11 steps in the worst case of a malicious highest-priority proposer colluding with a large fraction of committee participants at every step. In each step, every committee member casts a vote for some value, and all users count the votes. Users that receive more than a threshold of votes for some value will vote for that value in the next step (if selected as a committee member). If the users do not receive enough votes for any value, they time out, and their choice of vote for the next step is determined by the step number. In the common case, when the network is strongly syn- chronous and the highest-priority block proposer was hon- est, BA reaches final consensus by using its final step to confirm that there cannot be any other agreed-upon block in the same round. Otherwise, BA may declare tentative consensus if it cannot confirm the absence of other blocks due to possible network asynchrony.

#### You've reached the end of your free preview.

Want to read all 18 pages?

• Spring '19
• NA
• hash function, Cryptographic hash function, Algorand

### What students are saying

• As a current student on this bumpy collegiate pathway, I stumbled upon Course Hero, where I can find study resources for nearly all my courses, get online help from tutors 24/7, and even share my old projects, papers, and lecture notes with other students.

Kiran Temple University Fox School of Business ‘17, Course Hero Intern

• I cannot even describe how much Course Hero helped me this summer. It’s truly become something I can always rely on and help me. In the end, I was not only able to survive summer classes, but I was able to thrive thanks to Course Hero.

Dana University of Pennsylvania ‘17, Course Hero Intern

• The ability to access any university’s resources through Course Hero proved invaluable in my case. I was behind on Tulane coursework and actually used UCLA’s materials to help me move forward and get everything together on time.

Jill Tulane University ‘16, Course Hero Intern