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Robin Vassantlal

Publications and source records attributed to Robin Vassantlal.

3 recordsLinked to original sources

MVP-ORAM: a Wait-free Concurrent ORAM for Confidential BFT Storage

It is well known that encryption alone is not enough to protect data privacy. Access patterns, revealed when operations are performed, can also be leveraged in inference attacks. Oblivious RAM (ORAM) hides access patterns by making client requests oblivious. However, existing protocols are still limited in supporting concurrent clients and Byzantine fault tolerance (BFT). We present MVP-ORAM, the first wait-free ORAM protocol that supports concurrent fail-prone clients. In contrast to previous works, MVP-ORAM avoids using trusted proxies, which require additional security assumptions, and concurrency control mechanisms based on inter-client communication or distributed locks, which limit overall throughput and the capability of tolerating faulty clients. Instead, MVP-ORAM enables clients to perform concurrent requests and merge conflicting updates as they happen, satisfying wait-freedom, i.e., clients make progress independently of the performance or failures of other clients. Since wait and collision freedom are fundamentally contradictory goals that cannot be achieved simultaneously in an asynchronous concurrent ORAM service, we define a weaker notion of obliviousness that depends on the application workload and number of concurrent clients, and prove MVP-ORAM is secure in practical scenarios where clients perform skewed block accesses. By being wait-free, MVP-ORAM can be seamlessly integrated into existing confidential BFT data stores, creating the first BFT ORAM construction. We implement MVP-ORAM on top of a confidential BFT data store and show our prototype can process hundreds of 4KB accesses per second in modern clouds.

cs.CR

Knowledge Connectivity Requirements for Solving BFT Consensus with Unknown Participants and Fault Threshold (Extended Version)

Consensus stands as a fundamental building block for constructing reliable and fault-tolerant distributed services. The increasing demand for high-performance and scalable blockchain protocols has brought attention to solving consensus in scenarios where each participant joins the system knowing only a subset of participants. In such scenarios, the participants' initial knowledge about the existence of other participants can collectively be represented by a directed graph known as knowledge connectivity graph. The Byzantine Fault Tolerant Consensus with Unknown Participants (BFT-CUP) problem aims to solve consensus in those scenarios by identifying the necessary and sufficient conditions that the knowledge connectivity graphs must satisfy when a fault threshold is provided to all participants. This work extends BFT-CUP by eliminating the requirement to provide the fault threshold to the participants. We indeed address the problem of solving BFT consensus in settings where each participant initially knows a subset of participants, and although a fault threshold exists, no participant is provided with this information -- referred to as BFT Consensus with Unknown Participants and Fault Threshold (BFT-CUPFT). With this aim, we first demonstrate that the conditions for knowledge connectivity graphs identified by BFT-CUP are insufficient to solve BFT-CUPFT. Accordingly, we introduce a new type of knowledge connectivity graphs by determining the necessary and sufficient conditions they must satisfy to solve BFT-CUPFT. Furthermore, we design a protocol for solving BFT-CUPFT.

cs.DC

On the Minimal Knowledge Required for Solving Stellar Consensus

Byzantine Consensus is fundamental for building consistent and fault-tolerant distributed systems. In traditional quorum-based consensus protocols, quorums are defined using globally known assumptions shared among all participants. Motivated by decentralized applications on open networks, the Stellar blockchain relaxes these global assumptions by allowing each participant to define its quorums using local information. A similar model called Consensus with Unknown Participants (CUP) studies the minimal knowledge required to solve consensus in ad-hoc networks where each participant knows only a subset of other participants of the system. We prove that Stellar cannot solve consensus using the initial knowledge provided to participants in the CUP model, even though CUP can. We propose an oracle called sink detector that augments this knowledge, enabling Stellar participants to solve consensus.

cs.DC