Sharding in blockchains divides nodes into smaller groups which allow for partial transaction processing, relaying and storage. Accordingly, multiple blockchains (shards) will run in parallel, resulting in an increase in total throughput. Nonetheless, with shards comprised of less nodes, they will be more prone to security issues. In this paper, we propose a denial-of-service (DoS) attack where attackers are nodes that are eligible to participate in the process of intra-shard consensus. They then overflow a specific shard by proposing biased blocks containing cross-shard transactions where their receipts are all aimed at that shard. In particular, we utilize a queueing-theoretic model to evaluate different conditions in which the proposed DoS attack can successfully be performed or on the other hand avoided. We show that this attack can be performed irrespective of means to prevent shard takeover attack, e.g., randomization. Accordingly, for different loads in the system and attackers capabilities, we derive the maximum number of shards under which this attack can be averted, so that the system can perform safely.

Sharding has shown great potential to scale out blockchains. It divides nodes into smaller groups which allow for partial transaction processing, relaying and storage. Hence, instead of running one blockchain, we will run multiple blockchains in parallel, and call each one a shard. Sharding can be applied to address shortcomings due to compulsory duplication of three resources in blockchains, i.e., computation, communication and storage. The most pressing issue in blockchains today is throughput. In this paper, we propose new queueing-theoretic models to derive the maximum throughput of sharded blockchains. We consider two cases, a fully sharded blockchain and a computation sharding. We model each with a queueing network that exploits signals to account for block production as well as multi-destination cross-shard transactions. We make sure quasi-reversibility for every queue in our models is satisfied so that they fall into the category of product-form queueing networks. We then obtain a closed-form solution for the maximum stable throughput of these systems with respect to block size, block rate, number of destinations in transactions and the number of shards. Comparing the results obtained from the two introduced sharding systems, we conclude that the extent of sharding in different domains plays a significant role in scalability.