Version 1 . 01 The Core of Cartesi

Cartesi is a layer-2 platform for the development and deployment of scalable decentralized applications. Cartesi DApps are composed of both blockchain and off-chain components. Off-chain components run inside Cartesi Nodes that represent the interests of each DApp user. Cartesi Nodes provide DApp developers with reproducible Cartesi Machines, where large scale verifiable computations can be run. These verifiable computations are easily integrated into smart contracts by powerful primitives that provide strong conflictresolution guarantees. More precisely, any dispute arising over the result of computations run inside Cartesi Machines can be fairly adjudicated at negligible cost on the blockchain. Cartesi Nodes also allow DApp developers to run native code. Native computations can leverage the node’s full processing power, including any available GPUs. Whether performed natively by the node or inside Cartesi Machines, off-chain components run under a complete Linux operating system that provides the full ecosystem required by complex computations. Cartesi enables DApp developers to use all the programming languages, tools, libraries, software, and services they are already familiar with. By moving most of the complex logic of their DApps to portable off-chain components, developers are freed from the limitations and idiosyncrasies imposed by blockchains. In this way, Cartesi empowers developers to select the best run-time environment in which to host each part of their DApps.

[1]  Donald R. Morrison,et al.  PATRICIA—Practical Algorithm To Retrieve Information Coded in Alphanumeric , 1968, J. ACM.

[2]  Ralph C. Merkle,et al.  Secrecy, authentication, and public key systems , 1979 .

[3]  Manuel Blum,et al.  Non-interactive zero-knowledge and its applications , 1988, STOC '88.

[4]  Ronald L. Rivest,et al.  Time-lock Puzzles and Timed-release Crypto , 1996 .

[5]  Bryan Pfaffenberger,et al.  Linux , 2002, Encyclopedia of Information Systems.

[6]  U. Feige,et al.  Making Games Short , 2006 .

[7]  D. Keppel,et al.  Fast Microcode Interpretation with Transactional Commit/Abort , 2011 .

[8]  Ran Canetti,et al.  Practical delegation of computation using multiple servers , 2011, CCS '11.

[9]  Nir Bitansky,et al.  From extractable collision resistance to succinct non-interactive arguments of knowledge, and back again , 2012, ITCS '12.

[10]  Craig Gentry,et al.  Pinocchio: Nearly Practical Verifiable Computation , 2013, IEEE Symposium on Security and Privacy.

[11]  Nicolas van Saberhagen.  CryptoNote v 2.0 , 2013 .

[12]  Matthew Green,et al.  Zerocoin: Anonymous Distributed E-Cash from Bitcoin , 2013, 2013 IEEE Symposium on Security and Privacy.

[13]  Å. Cajander,et al.  Project Home , 2014 .

[14]  Eli Ben-Sasson,et al.  Succinct Non-Interactive Zero Knowledge for a von Neumann Architecture , 2014, USENIX Security Symposium.

[15]  Yunsup Lee,et al.  The RISC-V Instruction Set Manual , 2014 .

[16]  Daniel Davis Wood,et al.  ETHEREUM: A SECURE DECENTRALISED GENERALISED TRANSACTION LEDGER , 2014 .

[17]  Morris J. Dworkin,et al.  SHA-3 Standard: Permutation-Based Hash and Extendable-Output Functions , 2015 .

[18]  Rüdiger Kapitza,et al.  AsyncShock: Exploiting Synchronisation Bugs in Intel SGX Enclaves , 2016, ESORICS.

[19]  Srdjan Capkun,et al.  Software Grand Exposure: SGX Cache Attacks Are Practical , 2017, WOOT.

[20]  Gorka Irazoqui Apecechea,et al.  CacheZoom: How SGX Amplifies The Power of Cache Attacks , 2017, CHES.

[21]  Marcus Peinado,et al.  Inferring Fine-grained Control Flow Inside SGX Enclaves with Branch Shadowing , 2016, USENIX Security Symposium.

[22]  Dawn Xiaodong Song,et al.  Ekiden: A Platform for Confidentiality-Preserving, Trustworthy, and Performant Smart Contract Execution , 2018, ArXiv.

[23]  Eli Ben-Sasson,et al.  Scalable, transparent, and post-quantum secure computational integrity , 2018, IACR Cryptol. ePrint Arch..

[24]  Jason Teutsch,et al.  A scalable verification solution for blockchains , 2019, ArXiv.