We consider the design of an international CBDC system, where users can transact within or across jurisdictions under central bank issued CBDC units. We present CrossCoin, a pair of an economic design and a blockchain protocol that incentivizes CBDC currency service providers and allocates them CBDC transactions for validation. The CrossCoin economy determines the ideal valuation of transaction validation for service providers under the Cournot regime. The CrossCoin blockchain protocol, an amendment to Streamlet, ensures that the system remains functional even when a minority of the set of enrolled jurisdictional authorities decide to opt out of the economy under exogenous incentives.

We present TenderWallet, a CBDC system that offers a balance of inclusive privacy-preserving access and complete regulatory compliance. Our proposed system provides a CBDC functionality that is responsive to user behaviour, and in case of non-compliance by the user while availing the CBDC service, compensates the indirect monetary loss induced to the nation state, through collateralization. The TenderWallet system is also hybrid, such that it dynamically works as one variant of two well established offline CBDC models, thereby reducing the computational overhead of the service. We detail the behaviour of the TenderWallet system, analyze its deployment characteristics, and argue that it is superior to other potential hybrid CBDC designs. We conclude by showing that TenderWallet is near optimal, while considering compensation to the state and low-compute privacy and transparency of users as the main requirements of a CBDC system.

Several nations across the world are contemplating optimal design choices for Central Bank Digital Currencies (CBDCs). We present LimboCoin, an analytical framework for an arbitrary token based CBDC protocol. LimboCoin, under practical state-of-the-art assumptions on secure system design and protocol incentivization, considers an adversarial behaviour to achieve denial-of-service on the CBDC’s associated system and token economy. LimboCoin outlines the quality of the CBDC system and economy resultant from the interaction of honest and adversarial users in the CBDC’s jurisdiction. Through LimboCoin, we show that in the worst case, the number of compromised CBDC wallets in operation can exceed the number of legitimate wallets in operation, within the CBDC’s jurisdiction. We also show that in the worst case, the value associated with victim token transactions that are denied service exceeds 90 percent of the value associated with token transactions that are in legitimate service.

Classical and contemporary distributed consensus protocols, may they be for binary agreement, state machine replication, or blockchain consensus, require all protocol participants in a peer-to-peer system to output (agree on) exactly the same information as part of the consensus payload. Although this model of consensus is extensively studied, and is useful for most consensus based decentralized applications, it falls short of defining correct distributed systems which mandate participant credential based privileged visibility into the consensus payload, through the consensus protocol itself. We introduce a new paradigm for permissioned blockchain consensus, called functional blockchain consensus. Functional blockchain consensus allows each blockchain protocol participant to output some distinct sub-information of the list of transactions, as a function of the credentials of the participant in the blockchain system, instead of outputting the entire list of transactions. We motivate a novel rational-fault adversary to compromise functional blockchain consensus, and present a blockchain protocol called SightsTeeple, that achieves functional blockchain consensus in the said fault model. Sight-steeple relies on a novel combination of standard blockchain consensus and functional encryption, among other primitives, to achieve its goal of correctness. Further, we outline the realization of novel decentralized applications through functional blockchain consensus.

Convolutional neural networks (CNNs) are a foun-dational model architecture utilized to perform a wide variety of visual tasks. On image classification tasks CNNs achieve high performance, however model accuracy degrades quickly when inputs are perturbed by distortions such as additive noise or blurring. This drop in performance partly arises from incorrect detection of local features by convolutional layers. In this work, we develop a neuroscience-inspired unsupervised Sleep Replay Consolidation (SRC) algorithm for improving convolutional fil-ter's robustness to perturbations. We demonstrate that sleep-based optimization improves the quality of convolutional layers by the selective modification of spatial gradients across filters. We further show that, compared to other approaches such as fine-tuning, a single sleep phase improves robustness across different types of distortions in a data efficient manner.

Permissionless blockchain consensus protocols have been leveraged for defining decentralized economies for the (commercial or private) trade of virtual and physical assets, using cryptocurrencies. In most instances, the assets being traded are regulated , which mandates that the legal right to their trade and their trade value are determined by the governmental regulator of the jurisdiction in which the trade occurs. Unfortunately, existing blockchains do not formalize proposal of legal cryptocurrency transactions, as part of the execution of their respective consensus protocols, resulting in illegal activities in the associated crypto-economies. In this contribution, unlike existing non-consensus solutions, which are prone to be more compute-time and audit-time intensive, we present a novel regulatory framework for blockchain protocols, for ensuring legal transaction confirmation as part of the blockchain consensus. As per our regulatory framework, we derive, through a stochastic game analysis, block proposal strategies under which legal transaction throughput supersedes throughput of traditional transactions, which are, in the worst case, an indifferentiable mix of legal and illegal transactions. Finally, we show that when a majority of the consensus protocol participants are licensed by the regulator to propose legal transactions, there exists a fair consensus execution policy to maximize the legal transaction throughput in the blockchain network.

The recent emergence of the small cloud (SC), both in concept and in practice, has been driven mainly by issues related to service cost and complexity of commercial cloud providers (e.g., Amazon) employing massive data centers. However, the resource inelasticity problem faced by the SCs due to their relatively scarce resources might lead to a potential degradation of customer QoS and loss of revenue. A proposed solution to this problem recommends the federated sharing of resources between competing SCs to alleviate the resource inelasticity issues that might arise. Based on this idea, a recent effort proposed SC-Share, a performance-driven static market model for competitive small cloud environments that results in an efficient market equilibrium jointly optimizing customer QoS satisfaction and SC revenue generation. However, an important question with a non-obvious answer still remains to be answered, without which SC sharing markets may not be guaranteed to sustain in the long-run - is it still possible to achieve a stable market efficient state when the supply of SC resources is dynamic in nature?. In this article, we take a first step to addressing the problem of efficient market design for single SC resource sharing in dynamic environments. We answer our previous question in the affirmative through the use of Arrow and Hurwicz's disequilibrium process in economics, and the gradient play technique in game theory that allows us to iteratively converge upon efficient and stable market equilibria.