human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "effcient logging and querying for blockchain based cross site genomic dataset access audit"):
  Abstract: Background: Genomic data have been collected by different institutions and companies and need to be shared for broader use. In a cross-site genomic data sharing system, a secure and transparent access control audit module plays an essential role in ensuring the accountability. The 2018 iDASH competition first track provides us with an opportunity to design efficient logging and querying system for cross-site genomic dataset access audit. We designed a blockchain-based log system which can provide a light-weight and widely compatible module for existing blockchain platforms. The submitted solution won the third place of the competition. In this paper, we report the technical details in our system. Methods: We present two methods: baseline method and enhanced method. We started with the baseline method and then adjusted our implementation based on the competition evaluation criteria and characteristics of the log system. To overcome obstacles of indexing on the immutable Blockchain system, we designed a hierarchical timestamp structure which supports efficient range queries on the timestamp field. Results: We implemented our methods in Python3, tested the scalability, and compared the performance using the test data supplied by competition organizer. We successfully boosted the log retrieval speed for complex AND queries that contain multiple predicates. For the range query, we boosted the speed for at least one order of magnitude. The storage usage is reduced by 25%. Conclusion: We demonstrate that Blockchain can be used to build a time and space efficient log and query genomic dataset audit trail. Therefore, it provides a promising solution for sharing genomic data with accountability requirement across multiple sites.

Includes members:
  Member "hyperledger fabric a distributed operating system for permissioned blockchains":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "tenderbake classical bft style consensus for public blockchains")
  Member "modelchain decentralized privacy preserving healthcare predictive modeling framework on private blockchain networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "towards fair and decentralized privacy preserving deep learning with blockchain")
  Member "blockbench a framework for analyzing private blockchains":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "effective scaling of blockchain beyond consensus innovations and moore s law")
  Member "untangling blockchain a data processing view of blockchain systems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "effective scaling of blockchain beyond consensus innovations and moore s law")
  Member "optimized execution of business processes on blockchain":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "workflow management on bft blockchains")
  Member "enigma decentralized computation platform with guaranteed privacy":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "an overview on smart contracts challenges advances and platforms")
  Member "privacy in the genomic era":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "genome reconstruction attacks against genomic data sharing beacons")

Question: Please tell me which class the source paper belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.DB(Databases)