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replaced with resilient content addresses; inefficient monolithic services replaced with peer-to-peer algorithmic Bitcoin, Ethereum, and other blockchain networks have proven the utility of decentralized These public ledgers process sophisticated smart contract applications and transact crypto-assets worth tens of billions of dollars. These systems are the first instances of internetwide Open Services, where participants form a decentralized network providing useful services for pay, with no central management or trusted parties. IPFS has proven the utility of content-addressing by decentralizing the web itself, serving billions of files used across a global peer-to-peer network. data from silos, survives network partitions, works offline, routes around censorship, and gives permanence to digital information. Filecoin is a decentralized storage network that turns cloud storage into an algorithmic market. market runs on a blockchain with a native protocol token (also called “Filecoin”), which miners earn by providing storage to clients. Conversely, clients spend Filecoin hiring miners to store or distribute As with Bitcoin, Filecoin miners compete to mine blocks with sizable rewards, but Filecoin mining power is proportional to active storage, which directly provides a useful service to clients (unlike Bitcoin mining, whose usefulness is limited to maintaining blockchain consensus). This creates a powerful incentive for miners to amass as much storage as they can, and rent it out to clients. The protocol weaves these amassed resources into a self-healing storage network that anybody in the world can rely on. network achieves robustness by replicating and dispersing content, while automatically detecting and repairing replica failures. Clients can select replication parameters to protect against different threat The protocol’s cloud storage network also provides security, as content is encrypted end-to-end at the client, while storage providers do not have access to decryption keys. Filecoin works as an incentive layer on top of IPFS [1], which can provide storage infrastructure for any data. It is especially useful for decentralizing data, building and running distributed applications, and implementing smart contracts. (a) Introduces the Filecoin Network, gives an overview of the protocol, and walks through several components in detail. (b) Formalizes decentralized storage network (DSN) schemes and their properties, then constructs Filecoin as a DSN. © Introduces a novel class of proof-of-storage schemes called proof-of-replication, which allows proving that any replica of data is stored in physically independent storage. (d) Introduces a novel useful-work consensus based on sequential proofs-of-replication and storage as a measure of power. (e) Formalizes verifiable markets and constructs two markets, a Storage Market and a Retrieval Market, which govern how data is written to and read from Filecoin, respectively. (f) Discusses use cases, connections to other systems, and how to use the protocol. Note: Filecoin is a work in progress. Active research is under way, and new versions of this paper will appear at https://filecoin.io. For comments and suggestions, contact us at [email protected] Filecoin is a protocol token whose blockchain runs on a novel proof, called Proof-of-Spacetime, where blocks are created by miners that are storing data. Filecoin protocol provides a data storage and retrieval service via a network of independent storage providers that does not rely on a single coordinator, where: (1) clients pay to store and retrieve data, (2) Storage Miners earn tokens by offering storage (3) Retrieval Miners earn tokens by serving data. 1.1 Elementary Components The Filecoin protocol builds upon four novel components. Decentralized Storage Network (DSN): We provide an abstraction for network of independent storage providers to offer storage and retrieval services (in Section 2). Later, we present the Filecoin protocol as an incentivized, auditable and verifiable DSN construction (in Section 4). Novel Proofs-of-Storage: We present two novel Proofs-of-Storage (in Section 3): (1) Proof-ofReplication allows storage providers to prove that data has been replicated to its own uniquely dedicated Enforcing unique physical copies enables a verifier to check that a prover is not deduplicating multiple copies of the data into the same storage space; (2) Proof-of-Spacetime allows storage providers to prove they have stored some data throughout a specified amount of time. Verifiable Markets: We model storage requests and retrieval requests as orders in two decentralized verifiable markets operated by the Filecoin network (in Section 5). Verifiable markets ensure that payments are performed when a service has been correctly provided. We present the Storage Market and the Retrieval Market where miners and clients can respectively submit storage and retrieval orders. Useful Proof-of-Work: We show how to construct a useful Proof-of-Work based on Proof-ofSpacetime that can be used in consensus protocols. Miners do not need to spend wasteful computation to mine blocks, but instead must store data in the network. • The Filecoin protocol is a Decentralized Storage Network construction built on a blockchain and with a native token. Clients spend tokens for storing and retrieving data and miners earn tokens by storing and serving data. • The Filecoin DSN handle storage and retrieval requests respectively via two verifiable markets: the Storage Market and the Retrieval Market. Clients and miners set the prices for the services requested and offered and submit their orders to the markets. • The markets are operated by the Filecoin network which employs Proof-of-Spacetime and Proof-ofReplication to guarantee that miners have correctly stored the data they committed to store. • Finally, miners can participate in the creations of new blocks for the underlining blockchain. influence of a miner over the next block is proportional to the amount of their storage currently in use in the network. A sketch of the Filecoin protocol, using nomenclature defined later within the paper, is shown in Figure 1 accompanied with an illustration in Figure 2. The remainder of this paper is organized as follows. We present our definition of and requirements for a theoretical DSNscheme in Section 2. In Section 3 we motivate, define, and present our Proof-of-Replication and Proof-of-Spacetime protocols, used within Filecoin to cryptographically verify that data is continuously stored in accordance with deals made. Section 4 describes the concrete instantiation of the Filecoin DSN, describing data structures, protocols, and the interactions between participants. Section 5 defines and describes the concept of Verifiable Markets, as well as their implementations, the Storage Market and Retrieval Section 6 motivates and describes the use of the Proof-of-Spacetime protocol for demonstrating and evaluating a miner’s contribution to the network, which is necessary to extend the blockchain and assign the block reward. Section 7 provides a brief description of Smart Contracts within the Filecoin We conclude with a discussion of future work in Section 8 We introduce the notion of a Decentralized Storage Network (DSN) scheme. DSNs aggregate storage offered by multiple independent storage providers and self-coordinate to provide data storage and data retrieval to Coordination is decentralized and does not require trusted parties: the secure operation of theses systems is achieved through protocols that coordinate and verify operations carried out by individual parties.

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DSNs can employ different strategies for coordination, including Byzantine Agreement, gossip protocols, or

CRDTs, depending on the requirements of the system. Later, in Section 4, we provide a construction for the Filecoin DSN. A DSN scheme Π is a tuple of protocols run by storage providers and clients: (Put, Get, Manage) • Put(data) → key: Clients execute the Put protocol to store data under a unique identifier key. • Get(key) → data: Clients execute the Get protocol to retrieve data that is currently stored using key. • Manage(): The network of participants coordinates via the Manage protocol to: control the available storage, audit the service offered by providers and repair possible faults. The Manage protocol is run by storage providers often in conjunction with clients or a network of auditors1 A DSN scheme Π must guarantee data integrity and retrievability as well as tolerate management and storage faults defined in the following sections. 2.1 Fault tolerance 2.1.1 Management faults We define management faults to be byzantine faults caused by participants in the Manage protocol. scheme relies on the fault tolerance of its underlining Manage protocol. Violations on the faults tolerance assumptions for management faults can compromise liveness and safety of the system. For example, consider a DSN scheme Π, where the Manage protocol requires Byzantine Agreement (BA) to audit storage providers. In such protocol, the network receives proofs of storage from storage providers and runs BA to agree on the validity of these proofs. If the BA tolerates up to f faults out of n total nodes, then our DSN can tolerate f < n/2 faulty nodes. On violations of these assumptions, audits can be 2.1.2 Storage faults We define storage faults to be byzantine faults that prevent clients from retrieving the data: i.e. Miners lose their pieces, Retrieval Miners stop serving pieces. A successful Put execution is (f, m)-tolerant if it results in its input data being stored in m independent storage providers (out of n total) and it can tolerate up to f byzantine providers. The parameters f and m depend on protocol implementation; protocol designers can fix f and m or leave the choice to the user, extending Put(data) into Put(data, f, m). execution on stored data is successful if there are fewer than f faulty storage providers. For example, consider a simple scheme, where the Put protocol is designed such that each storage provider stores all of the data. In this scheme m = n and f = m − 1. Is it always f = m − 1? No, some schemes can be designed using erasure coding, where each storage providers store a special portion of the data, such that x out of m storage providers are required to retrieve the data; in this case f = m − x. We describe the two required properties for a DSN scheme and then present additional properties required by the Filecoin DSN. In the case where the Manage protocol relies on a blockchain, we consider the miners as auditors, since they verify and coordinate storage providers 2.2.1 Data Integrity This property requires that no bounded adversary A can convince clients to accept altered or falsified data at the end of a Get execution. A DSN scheme Π provides data integrity if: for any successful Put execution for some data d under key k, there is no computationally-bounded adversary A that can convince a client to accept d 0 6= d at the end of a Get execution for identifier k. This property captures the requirement that, given our fault-tolerance assumptions of Π, if some data has been successfully stored in Π and storage providers continue to follow the protocol, then clients can eventually retrieve the data. A DSN scheme Π provides retrievability if: for any successful Put execution for data under key, there exists a successful Get execution for key for which a client retrieves data. 2.2.3 Other Properties DSNs can provide other properties specific to their application. We define three key properties required by the Filecoin DSN: public verifiability, auditability, and incentive-compatibility. A DSN scheme Π is publicly verifiable if: for each successful Put, the network of storage providers can generate a proof that the data is currently being stored. The Proof-of-Storage must convince any efficient verifier, which only knows key and does not have access to data. A DSN scheme Π is auditable, if it generates a verifiable trace of operation that can be checked in the future to confirm storage was indeed stored for the right duration of time. A DSN scheme Π is incentive-compatible, if: storage providers are rewarded for successfully offering storage and retrieval service, or penalized for misbehaving, such that the storage providers’ dominant strategy is to store data. In the Filecoin protocol, storage providers must convince their clients that they stored the data they were paid to store; in practice, storage providers will generate Proofs-of-Storage (PoS) that the blockchain network (or the clients themselves) verifies. In this section we motivate, present and outline implementations for the Proof-of-Replication (PoRep) and Proof-of-Spacetime (PoSt) schemes used in Filecoin. Proofs-of-Storage (PoS) schemes such as Provable Data Possession (PDP) [2] and Proof-of-Retrievability (PoR) [3, 4] schemes allow a user (i.e. the verifier V) who outsources data D to a server (i.e. the prover P) to repeatedly check if the server is still storing D. The user can verify the integrity of the data outsourced to a server in a very efficient way, more efficiently than downloading the data. The server generates probabilistic proofs of possession by sampling a random set of blocks and transmits a small constant amount of data in a challenge/response protocol with the user. PDP and PoR schemes only guarantee that a prover had possession of some data at the time of the challenge/response. In Filecoin, we need stronger guarantees to prevent three types of attacks that malicious miners could exploit to get rewarded for storage they are not providing: Sybil attack, outsourcing attacks, • Sybil Attacks: Malicious miners could pretend to store (and get paid for) more copies than the ones physically stored by creating multiple Sybil identities, but storing the data only once. • Outsourcing Attacks: Malicious miners could commit to store more data than the amount they can physically store, relying on quickly fetching data from other storage providers. • Generation Attacks: Malicious miners could claim to be storing a large amount of data which they are instead efficiently generating on-demand using a small program. If the program is smaller than the purportedly stored data, this inflates the malicious miner’s likelihood of winning a block reward in Filecoin, which is proportional to the miner’s storage currently in use. Proof-of-Replication (PoRep) is a novel Proof-of-Storage which allows a server (i.e. the prover P) to convince a user (i.e. the verifier V) that some data D has been replicated to its own uniquely dedicated physical Our scheme is an interactive protocol, where the prover P: (a) commits to store n distinct replicas (physically independent copies) of some data D, and then (b) convinces the verifier V, that P is indeed storing each of the replicas via a challenge/response protocol. To the best of our knowledge, PoRep improves on PoR and PDP schemes, preventing Sybil Attacks, Outsourcing Attacks, and Generation Attacks. For a formal definition, a description of its properties, and an in-depth study of Proof-of-Replication, we refer the reader to [5].

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(Proof-of-Replication) A PoRep scheme enables an efficient prover P to convince a verifier

V that P is storing a replica R, a physical independent copy of some data D, unique to P. A PoRep protocol is characterized by a tuple of polynomial-time algorithms: (Setup, Prove, Verify) , D) → R, SP , SV , where SP and SV are scheme-specific setup variables for P and V, λ is a security parameter. PoRep.Setup is used to generate a replica R, and give P and V the necessary information to run PoRep.Prove and PoRep.Verify. Some schemes may require the prover or interaction with a third party to compute PoRep.Setup. • PoRep.Prove(SP , R, c) → π , where c is a random challenge issued by a verifier V, and π is a proof that a prover has access to R a specific replica of D. PoRep.Prove is run by P to produce a π • PoRep.Verify(SV , c, πc ) → {0, 1}, which checks whether a proof is correct. PoRep.Verify is run by V and convinces V whether P has been storing R. Proof-of-Storage schemes allow a user to check if a storage provider is storing the outsourced data at the time of the challenge. How can we use PoS schemes to prove that some data was being stored throughout a period A natural answer to this question is to require the user to repeatedly (e.g. every minute) send challenges to the storage provider. However, the communication complexity required in each interaction can be the bottleneck in systems such as Filecoin, where storage providers are required to submit their proofs to the blockchain network. To address this question, we introduce a new proof, Proof-of-Spacetime, where a verifier can check if a prover is storing her/his outsourced data for a range of time. The intuition is to require the prover to (1) generate sequential Proofs-of-Storage (in our case Proof-of-Replication), as a way to determine time (2) recursively compose the executions to generate a short proof. (Proof-of-Spacetime) A PoSt scheme enables an efficient prover P to convince a verifier V that P is storing some data D for some time t. A PoSt is characterized by a tuple of polynomial-time , D) → SP , SV , where SP and SV are scheme-specific setup variables for P and V, λ is a PoSt.Setup is used to give P and V the necessary information to run PoSt.Prove Some schemes may require the prover or interaction with a third party to compute • PoSt.Prove(SP , D, c, t) → π that a prover has access to D for some time t. PoSt.Prove is run by P to produce a π • PoSt.Verify(SV , c, t, πc PoSt.Verify is run by V and convinces V whether P has been storing D for some time t. 3.4 Practical PoRep and PoSt We are interested in practical PoRep and PoSt constructions that can be deployed in existing systems and do not rely on trusted parties or hardware. We give a construction for PoRep (see Seal-based Proof-of-Replication in [5]) that requires a very slow sequential computation Seal to be performed during Setup to generate a The protocol sketches for PoRep and PoSt are presented in Figure 4 and the underlying mechanism of the proving step in PoSt is illustrated in Figure 3. 3.4.1 Cryptographic building blocks We use a collision resistant hash function CRH : {0, 1} ∗ → {0, 1} also use a collision resistant hash function MerkleCRH, which divides a string in multiple parts, construct a binary tree and recursively apply CRH and outputs the root. Our practical implementations of PoRep and PoSt rely on zero-knowledge Succinct Noninteractive ARguments of Knowledge (zk-SNARKs) [6, 7, 8]. Because zk-SNARKs are succinct, proofs are very short and easy to verify. More formally, let L be an NP language and C be a decision circuit for L. A trusted party conducts a one-time setup phase that results in two public keys: a proving key pk and a verification key vk. The proving key pk enables any (untrusted) prover to generate a proof π attesting that x ∈ L for an instance x of her choice. The non-interactive proof π is both zero-knowledge and proof-ofknowledge. Anyone can use the verification key vk to verify the proof π; in particular zk-SNARK proofs are publicly verifiable: anyone can verify π, without interacting with the prover that generated π. The proof π has constant size and can be verified in time that is linear in |x|. A zk-SNARK for circuit satisfiability is a triple of polynomial-time algorithms (KeyGen, Prove, Verify) , C) → (pk, vk). On input security parameter λ and a circuit C, KeyGen probabilistically samples pk and vk. Both keys are published as public parameters and can be used to prove/verify membership in LC . • Prove(pk, x, w) → π. On input pk and input x and witness for the NP-statement w, the prover Prove outputs a non-interactive proof π for the statement x ∈ LC . • Verify(vk, x, π) → {0, 1}. On input vk, an input x, and a proof π, the verifier Verify outputs 1 if x ∈ LC . We refer the interested reader to [6, 7, 8] for formal presentation and implementation of zk-SNARK systems. Generally these systems require the KeyGen operation to be run by a trusted party; novel work on Scalable Computational Integrity and Privacy (SCIP) systems [9] shows a promising direction to avoid this initial step, hence the above trust assumption. 3.4.2 Seal operation The role of the Seal operation is to (1) force replicas to be physically independent copies by requiring provers to store a pseudo-random permutation of D unique to their public key, such that committing to store n replicas results in dedicating disk space for n independent replicas (hence n times the storage size of a replica) and (2) to force the generation of the replica during PoRep.Setup to take substantially longer than the time expected for responding to a challenge. For a more formal definition of the Seal operation see [5]. The above operation can be realized with Sealτ AES−256, and τ such that Sealτ AES−256 takes 10-100x longer than the honest challenge-prove-verify sequence. Note that it is important to choose τ such that running Sealτ is distinguishably more expensive than running Prove with random access to R [1] Juan Benet. IPFS - Content Addressed, Versioned, P2P File System. [2] Giuseppe Ateniese, Randal Burns, Reza Curtmola, Joseph Herring, Lea Kissner, Zachary Peterson, and Provable data possession at untrusted stores. In Proceedings of the 14th ACM conference on Computer and communications security, pages 598–609. [3] Ari Juels and Burton S Kaliski Jr. Pors: Proofs of retrievability for large files. In Proceedings of the 14th ACM conference on Computer and communications security, pages 584–597. [4] Hovav Shacham and Brent Waters. Compact proofs of retrievability.

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In International Conference on

the Theory and Application of Cryptology and Information Security, pages 90–107. [5] Protocol Labs. Technical Report: Proof-of-Replication. [6] Rosario Gennaro, Craig Gentry, Bryan Parno, and Mariana Raykova. Quadratic span programs and succinct nizks without pcps. In Annual International Conference on the Theory and Applications of Cryptographic Techniques, pages 626–645. [7] Nir Bitansky, Alessandro Chiesa, and Yuval Ishai. Succinct non-interactive arguments via linear interactive [8] Eli Ben-Sasson, Alessandro Chiesa, Daniel Genkin, Eran Tromer, and Madars Virza. Snarks for c: Verifying program executions succinctly and in zero knowledge. In Advances in Cryptology–CRYPTO 2013, pages 90–108. [9] Eli Ben-Sasson, Iddo Bentov, Alessandro Chiesa, Ariel Gabizon, Daniel Genkin, Matan Hamilis, Evgenya Pergament, Michael Riabzev, Mark Silberstein, Eran Tromer, et al. with a public random string from quasi-linear pcps. In Annual International Conference on the Theory and Applications of Cryptographic Techniques, pages 551–579. [10] Henning Pagnia and Felix C G¨artner. On the impossibility of fair exchange without a trusted third party. Technical report, Technical Report TUD-BS-1999-02, Darmstadt University of Technology, Department of Computer Science, Darmstadt, Germany, 1999. [11] Joseph Poon and Thaddeus Dryja. The bitcoin lightning network: Scalable off-chain instant payments. [12] Andrew Miller, Iddo Bentov, Ranjit Kumaresan, and Patrick McCorry. Sprites: Payment channels that go faster than lightning. arXiv preprint arXiv:1702.05812, 2017. [13] Protocol Labs. Technical Report: Power Fault Tolerance. [14] Protocol Labs. Technical Report: Expected Consensus. [15] Iddo Bentov, Charles Lee, Alex Mizrahi, and Meni Rosenfeld. Proof of activity: Extending bitcoin’s proof of work via proof of stake [extended abstract] y. ACM SIGMETRICS Performance Evaluation Review, 42(3):34–37, 2014. [16] Iddo Bentov, Rafael Pass, and Elaine Shi. Snow white: Provably secure proofs of stake. [17] Silvio Micali. Algorand: The efficient and democratic ledger. arXiv preprint arXiv:1607.01341, 2016. [18] Vitalik Buterin. Ethereum , April 2014. [19] Satoshi Nakamoto. Bitcoin: A peer-to-peer electronic cash system, 2008. [20] Eli Ben Sasson, Alessandro Chiesa, Christina Garman, Matthew Green, Ian Miers, Eran Tromer, and Zerocash: Decentralized anonymous payments from bitcoin. In Security and Privacy (SP), 2014 IEEE Symposium on, pages 459–474. The partnership will seek to deliver on a decentralized transaction platform combining the ledgerless ease and scalability of cash payment systems with a flexible ledger-based technology. The platform will aim to enhance and incorporate the features of existing financial payment systems. The Toda-Algorand platform is designed to have a throughput of over three million confirmed transactions per second (TPS) and can serve over four billion users securely. (The Toda Protocol is in the process of pursuing ITU-T standards TODA-T for on-device global communication deployments beneath the OS on the same level as TCP/IP.) The Toda-Algorand synergy will provide online transaction systems without infrastructure investments and without transaction fees. The platform will support real-time transactions and linear scalability on ledgerless transactions. The efficiency and scalability of this platform is due to its core decentralized and distributed architecture. No miners, no databases, no server, therefore no leakage of cost outside of actually running the system itself. This blockchain architecture is unstoppable. I watched this episode couple of days ago, and read Algorand paper a month ago. It is truly brilliant! There are lots of things to like about Algorand: It is a true proof is stake, because everyone with some amount of tokens can participate. It is censorship resistant, because the signatories of blocks are not revealed until they have already signed. They would also normally move their stake to a fresh address, in case adversary decided to corrupt them after signing. The speed of block creation is only constrained by the speed of message propagation through the network, there is no artificial limits. If the networking technology keeps getting better, so will Algorand. There are no pairings involved, only digital signatures (though they need to be deterministic) and hashes. The paper mentiones that the author has applied for patents. The efficiency, security and true decentralization of the platform ensures self regulated secure financial system that can be instrumental in the acceleration towards prosperity. “Preserving wealth in local areas using near zero transaction fees can help boost their economy and accelerate towards prosperity,” said Algorand author and Turing Award winner Silvio Micali. Toda-Algorand, a joint venture between Todacorp and Algorand was announced last month in Palo Alto. It is starting to thrive and attracts businesses, governments and entrepreneurs to power their emerging market. The platform solves the scalability, efficiency, true decentralization while providing a phenomenal business model. The company has been self-funded to date. SOURCE TodaCorp Inc. Get Weekly ICO Updates Sign up for our newsletter and receive insider ICO news Please read the disclaimer and risk warning. This offer is based on information provided solely by the offeror and other publicly available information. The token sale or exchange event is entirely unrelated to ICOholder and ICOholder has no involvement in it (including any technical support or promotion). Token sales listed from persons that ICOholder has no relationship with are shown only to help customers keep track of the activity taking place within the overall token sector. This information is not intended to amount to advice on which you should rely. You must obtain professional or specialist advice or carry out your own due diligence before taking, or refraining from, any action on the basis of the content on our site. The distributed ledger blockchain protocol Algorand, coauthored by Massachusetts Institute of Technology professor Silvio Micali, announced today the project has raised $4 million in seed funding. The Algorand protocol is an open-source implementation of a blockchain, a distributed ledger technology that can be used to secure transactions and information in a tamper-proof manner. The protocol expands on the same technology that underlies the digital currency bitcoin, but aims to address scaling challenges through efficient and fast consensus between network nodes. A CB Insights report from October estimated that venture funding for blockchain exceeded $1.2 billion in 2017, with an additional $2 billion from initial coin offerings. In fact, although the team said it’s “cryptographically committed” to its roadmap, it’s difficult to tell what that means. The roadmap page contains a series of three items with accompanying hexadecimal cryptographic hashes but no explanation of what that means or why it’s meaningful to the protocol. The Algorand white paper is available for developers and potential users to better understand the protocol. And Micali has also spoken at blockchain and crpytography events describing the protocol’s potential, linked on Algorand’s website. … We’d like to tell you about our mission and how you can help us fulfill it. SiliconANGLE Media Inc.’s business model is based on the intrinsic value of the content, not advertising. Keeping the quality high requires the support of sponsors who are aligned with our vision of ad-free journalism content. To protect them from attackers, the identities of these users are hidden until the block is confirmed. The size of this group remains constant as the network grows. Any currency representing a significant fraction of the world’s money will be attacked at the user level, the protocol level, and the network level. Algorand remains secure in the face of attacks. Confirming transactions with Algorand does not require solving cryptographic puzzles. The consensus protocol is both computationally and energy efficient, which keeps transaction costs low. With no heavy lifting, even small players can transact. Algorand  transactions are confirmed instantly, and transferred money is immediately available. Algorand is fully decentralized. Every decision is reached by consensus and represents the will of the majority. All transactions are created and treated equally, regardless of size. Algorand is guaranteed to work securely if the majority of the money in the system is owned by honest users. A user in Algorand does not need to put any fraction of his money at stake. A user’s money always remains in her hands, ready to be spent how she wishes. Please enter the e-mail that you registered your account with, and we will send your username to that address.

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Algorand is a scalable, secure and decentralized digital currency and transactions platform. 05:08 29 May Algorand is a truly democratic and efficient way to implement a public ledger. Unlike prior implementations based on proof of work, it requires a negligible amount of computation, and generates a tran 100%weight Experts are independently and voluntarily contributing to the community. If no expert has rated the ICO, only ICO analyzer’s results are used. Always research before investing as these ratings should not be taken as an investing guide of any kind.Ratings and ICO analyzer results are being updated (re-calculated) every few hours. MIT’s Ford Professor of Engineering and one of the world’s top cryptographers Silvio Micali recently published a paper called ALGORAND The Efficient and Democratic Ledger… KYC passing required No | Restriction for countries No br> Blockchain payments platform Algorand has raised $4 million in seed funding. The funding support came from Pillar and Union Square Ventures. Algorand intends to use the money to develop its technology and expand its 10-person team. Founded by MIT professor and Turing Award winner Silvio Micali, Algorand is a scalable and decentralized cryptocurrency and transactions platform based on Byzantine Agreement (BA) protocol. It addresses blockchain’s scaling challenges through rapid and efficient user consensus, enabling even the smallest transactions, regardless of volume or number of users. Algorand ensures that users never have divergent views of confirmed transactions, even if some of the users are malicious and the network is temporarily partitioned. In contrast, existing cryptocurrencies allow for temporary forks and therefore require a long time, on the order of an hour, to confirm transactions with high confidence. The company anticipates launching the platform within the year. “Algorand is a sophisticated approach to addressing existing blockchain challenges – scale, settlement times, and cost. The company has the potential to fulfill the promise of a truly decentralized world.” The figurehead for Algorand is Silvio Micali, winner of the 2012 ACM Turing Award. When Micali saw Bitcoin, he thought it could be improved — Algorand is the result of that quest. I found Micali’s recent ACM lecture on Algorand (available on YouTube) very helpful as background to this paper. The core of Algorand is a new Byzantine agreement protocol called BA★. Participants in BA★ are randomly selected based on a proof-of-stake mechanism that relies on cryptographic sortition. The safety guarantee says that if one honest user accepts transaction A, then any future transactions accepted by other honest users will appear in a log that already contains A. I.e., an adversary cannot manipulate the network at large scale. There is no distinction between miners and users, all Algorand users are created equally and communicate through a gossip protocol. Messages are signed using the private key of the sender, and peer selection is weighted based on how much money a peer has. The gossip protocol is used by users to submit new transactions, and every user collects a block of pending transactions that they hear about. In each round a set of users are chosen at random (in a fully decentralised way using cryptographic sortition) to propose a block. Selected users propose their block together with their priority and proof using the gossip protocol. To reach consensus on a proposed block, Algorand uses the BA★ agreement protocol. BA★ executes in steps, communicates over the same gossip protocol, and produces a new agreed-upon block. BA★ can produce two kinds of consensus: final consensus and tentative consensus. If one user reaches final consensus, this means that any other user that reaches final or tentative consensus in the same round must agree on the same block value. Unlike many proof-of-stake schemes though, malicious leaders cannot create forks in the network. The randomness in the sortition algorithm comes from a publicly known random seed. The seed for the genesis block is decided using distributed random number generation. The seed for a subsequent round is determined using verifiable random functions (VRFs) in round and included in the proposed block. There’s a back-up procedure to derive a seed from the seed of the previous round that can be used in the event that a proposed block is rejected. The neat thing about sortition is that it requires no central coordination. Each user can run the sortition algorithm locally to determine whether or not they are a winner in this round. Each user has a public/private key-pair . Sortition is implemented using VRFs. Informally, on any input string , returns two values: a hash and a proof. The hash is a hashlen-bit-long value that is uniquely determined by and , but is indistinguishable from random to anyone that does not know . The proof enables anyone that knows to check that the hash indeed corresponds to , without having to know . In addition to the main blockchain rounds, each execution of the BA★ protocol also proceeds in a series of steps. The participants are selected at random for each of these steps using sortition. The expected number of users that sortition selects for the committee in each step is same () for each step but the last, when we require a higher number, . 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. The 11-step worst case occurs when a malicious highest-priority proposer colludes with a large fraction of committee participants (those chosen by sortition) at every step. As its output, if the highest-priority block proposer was honest, BA★ reaches final consensus, otherwise it may declare tentative consensus. Here’s the high-level procedure for BA★ as a whole: The four main procedures in this algorithm: Reduction, _Binary_BA★, CountVotes, and BlockOfHash are described next. In the first step, each committee member gossips their vote for the hash of the block passed to reduction by BA★. As we saw previously, is the expected number of users in the committee. is the fraction of the expected committee size () that defines the voting threshold. Binary agreement reaches consensus on either the hash that was passed to it, or the empty block. It looks like this: In the common case, it reaches consensus in the first step. In the interests of space, I’ll refer you to section 7.4 in the paper for the details. CountVotes stores incoming votes in a buffer indexed by round and step. As soon as one value has more that votes, that value is returned. For efficiency, BA★ votes for hashes of blocks, instead of entire block contents. An Algorand prototype was implemented in 5000 lines of C++ and deployed on EC2 using 1000 m4.2xlarge VMs, each with 8 cores and up to 1 Gbps network throughput. Experiments show that Algorand can confirm transactions in well under a minute, and scales well up to 500K users (the maximum in the test, not the limit of scalability). At its lowest latency and a 2MB block size, Algorand can commit around 327MB of transactions per hour (vs Bitcoins 6MB per hour). With 10MB blocks, Algorand commits around 750MB of transactions per hour, 125x the throughput of Bitcoin. CPU and network overheads are minimal (c.f., proof of work! ), with each Algorand process using about 6.5% of a core. Block storage can be sharded across users. In July of this year TodaCorp announced a partnership with Silvio Micali to develop Toda-Algorand, a joint venture combining the Toda protocol with Algorand. (Is there a paper describing the Toda protocol anywhere??). The question of (lack of) incentives in Algorand has been a subject of debate. Pillar Companies and Union Square Ventures are the investors in Boston-based Algorand’s seed funding round announced Thursday. It’s a relatively small amount of money being raised by a startup entering an increasingly crowded sector. But part of what makes Algorand worth watching is the people involved and the claims the venture is making. Algorand’s co-founder is Silvio Micali, an MIT computer engineering professor and cryptographer who has won the prestigious A.M. Turing Award. Micali (pictured above) co-authored the open-source software protocol underpinning the virtual currency and transactions system that Algorand plans to launch this year. (Ethereum is also reportedly working on a proof-of-stake-based blockchain system called Casper.) Algorand claims its system will be able to confirm transactions within seconds and keep transaction costs low. “Algorand is a sophisticated approach to addressing existing blockchain challenges—scale, settlement times, and cost,” said Pillar partner Jamie Goldstein in a prepared statement. Of course, Algorand will have to prove its technology works as advertised, and it’s too early to tell whether users will flock to it. The company said it will use the funding to develop its technology and expand its 10-person team. Jeff Engel is a senior editor at Xconomy. 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Pre-sale I round: 16 April - 13 May, min contribution 100$, tokens for sale 20% Pre-sale II round: 14 May -10 June, min contribution 50$, tokens for sale 20% Main ICO: 11 June - 08 July, no min contribution, tokens for sale 20% In fact – over a million years statistically. And the basis for his solution is taking a totally different tack in the process of building a block. He noted that the idea was first seeded to him by a friend but he added that many of the Magistracies in Florence were elected by lottery. He calls it cryptographic certation. And do this in a way that is not manipulatable by an adversary. No one selects the group – it’s selected by hash. And if that’s not enough he says you take a pseudo-random generator which is pre-specified and you elongate as much as you need to select the committee. The group decided the next block by a redesigned Byzantine Agreement where a leader is picked randomly from the group. If he’s a bad choice an agreement will not be able to be made. And everyone is forced to agree on nothing. With a bad leader, you just don’t get a block and if you have an empty block you get no money.

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That’s the game theory.

Since 1983 he has been on the MIT faculty, in Electrical Engineering and Computer Science Department, where he is Ford Professor of Engineering. Silvio’s research interests are cryptography, zero knowledge, pseudorandom generation, secure protocols, and mechanism design. Silvio is the recipient of the Turing Award (in computer science), of the Goedel Prize (in theoretical computer science) and the RSA prize (in cryptography). He is a member of the National Academy of Sciences, the National Academy of Engineering, and the American Academy of Arts and Sciences.