Secure, Confidential Blockchains Providing High Throughput and Low Latency
One of the core promises of blockchain technology is that of enabling trustworthy data dissemination in a trustless environment. What current blockchain systems deliver, however, is slow dissemination of public data, rendering blockchain technology unusable in settings where latency, transaction capacity, or data confidentiality are important. In this thesis we focus on providing solutions on two of the most pressing problems blockchain technology currently faces: scalability and data confidentiality.
To address the scalability issue, we present OMNILEDGER, a novel scale-out distributed ledger that preserves long-term security under permissionless operation. It ensures security and correctness by using a bias-resistant public-randomness protocol for choosing large, statistically representative shards that process transactions, and by introducing an efficient cross-shard commit protocol that atomically handles transactions affecting multiple shards.
To enable secure sharing of confidential data we present CALYPSO, the first fully decentralized, auditable access-control framework for secure blockchain-based data sharing which builds upon two abstractions. First, on-chain secrets enable collective management of (verifiably shared) secrets under a Byzantine adversary where an access-control blockchain enforces user-specific access rules and a secret-management cothority administers encrypted data. Second, skipchain-based identity and access management enables efficient administration of dynamic, sovereign identities and access policies and, in particular, permits clients to maintain long-term relationships with respect to evolving user identities thanks to the trust-delegating forward links of skipchains.
In order to build OMNILEDGER and CALYPSO, we first build a set of tools for efficient decentralization, which are presented in Part II of this dissertation. These tools can be used in decentralized and distributed systems to achieve (1) scalable consensus (BYZCOIN), (2) bias- resistant distributed randomness creations (RANDHOUND), and (3) relationship-keeping between independently updating communication endpoints (SKIPCHAINIAC). Although we use this tools in the scope off this thesis, they can be (and already have been) used in a far wider scope.
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