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1. PAVE: Privacy-Preserving Aggregated Verification For Multi-Enterprises Blockchain

   https://doi.org/10.1109/MASS66014.2025.00078  

   Zhang, X; Tesfai, S; Wang, M; Cai, H (October 2025, IEEE)

   Not AvailableMulti-enterprise applications in fields like supply chain management, finance, and healthcare require complex collaboration and data exchange among organizations to ensure operational efficiency and build trust. Permissioned blockchains emerged as a promising solution, providing shared, immutable ledgers that enhance transparency, traceability, and trust among authorized parties. However, during asset trading between organizations, they must verify the legitimacy of asset transfers, including asset ownership and quantity, while protecting sensitive asset owner information. To achieve both verifiability and privacy, this paper introduces PAVE, Privacy-preserving Aggregated Verification system for Multi-Enterprises Blockchain, a framework that integrates zero-knowledge proofs to enable secure asset verification without breaking user privacy. To achieve proof efficiency, PAVE introduces a proof aggregation mechanism that consolidates multiple transaction verifications into a single proof, significantly reducing computational overhead for large-scale scenarios. Evaluation results show that, with the proof aggregation mechanism, PAVE achieves low verification latency and resource utilization, making it a scalable solution for privacy-preserving asset verification across multiple enterprises. 

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2. On Sharding Permissioned Blockchains.

   Mohammad Javad Amiri, Divyakant Agrawal (July 2019, IEEE International Conference on Blockchain)

   Permissioned Blockchain systems rely mainly on Byzantine fault-tolerant protocols to establish consensus on the order of transactions. While Byzantine fault-tolerant protocols mostly guarantee consistency (safety) in an asynchronous network using 3f+1 machines to overcome the simultaneous malicious failure of any f nodes, in many systems, e.g., blockchain systems, the number of available nodes (resources) is much more than 3f + 1. To utilize such extra resources, in this paper we introduce a model that leverages transaction parallelism by partitioning the nodes into clusters (partitions) and processing independent transactions on different partitions simultaneously. The model also shards the blockchain ledger, assigns different shards of the blockchain ledger to different clusters, and includes both intra-shard and cross-shard transactions. Since more than one cluster is involved in each cross-shard transaction, the ledger is formed as a directed acyclic graph. 

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3. Elastispec: Formalizing Enterprise Firewall Management with Informal and Elastic Specifications

   https://doi.org/10.1145/3789240.3829191  

   Wen, Chenan; Qing, Yizhan; Jansen, Curt P; Qiu, Xiaokang; Rao, Sanjay G (August 2026, ACM)

   Managing enterprise network firewalls is an ad-hoc process today, where administrators must extract policies relevant to their enterprises from thousands of natural language vendor documents and tailor them to their unique context. In this paper, we present Elastispec, a first step towards principled management of enterprise firewall policies with informal and incomplete specifications. We make three contributions: (i) LLM-assisted formalization of vendor documents into a custom domain specific language that precisely captures the rich choices and options using a multi-step consistency-preserving LLM agent; (ii) mapping the DSL to a concrete network environment by correlating diverse and possibly imperfect enterprise data sources; and (iii) an interactive auditor that cross-checks firewall configurations against the formal but potentially partial specifications and reports potential compliance gaps along with conjectures for human validation. Evaluations with real-world enterprise firewall configurations and popular enterprise application vendor documents show that Elastispec is effective in enabling operators to audit their configurations against vendor documents by producing compliance trees, enabling comparative analysis across parallel application deployments, and detecting configuration errors that permit non-compliant traffic. 

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4. Transaction Processing in Blockchain Sharding: Current Trends and Future Research Directions

   https://doi.org/10.1145/3777468  

   Adhikari, Ramesh; Busch, Costas; Kowalski, Dariusz R; Al-Mamun, Abdullah (November 2025, Distributed Ledger Technologies: Research and Practice)

   Blockchain is known for its promising features, such as decentralization, fault tolerance, transparency, and immutability. Thus, it has been used in many industries and applications, including cryptocurrency, finance, smart cities, healthcare, and manufacturing. However, blockchain suffers from scalability issues and provides low transaction throughput and high latency. Sharding is used to solve these scalability and performance issues by dividing the blockchain network into smaller clusters of nodes called shards, and each shard processes transactions in parallel. However, the sharding protocol is still in its early stages and encounters multiple challenges. In this paper, we survey cutting-edge blockchain sharding papers, mainly focusing on transaction processing aspects such as intra-shard transaction processing, cross-shard communication, and cross-shard transaction processing.We also examine security vulnerabilities and attack vectors associated with sharded blockchain systems. We review existing techniques, highlight key challenges and problems, and suggest potential future research directions. 

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5. MixT: A Language for Mixing Consistency in Geodistributed Transactions

   Milano, Matthew P.; Myers, Andrew C. (January 2018, Proceedings of the ACM SIGPLAN Conference on Programming Language Design and Implementation)

   Programming concurrent, distributed systems is hard---especially when these systems mutate shared, persistent state replicated at geographic scale. To enable high availability and scalability, a new class of weakly consistent data stores has become popular. However, some data needs strong consistency. To manipulate both weakly and strongly consistent data in a single transaction, we introduce a new abstraction: mixed-consistency transactions, embodied in a new embedded language, MixT. Programmers explicitly associate consistency models with remote storage sites; each atomic, isolated transaction can access a mixture of data with different consistency models. Compile-time information-flow checking, applied to consistency models, ensures that these models are mixed safely and enables the compiler to automatically partition transactions. New run-time mechanisms ensure that consistency models can also be mixed safely, even when the data used by a transaction resides on separate, mutually unaware stores. Performance measurements show that despite their stronger guarantees, mixed-consistency transactions retain much of the speed of weak consistency, significantly outperforming traditional serializable transactions. 

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