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 "archive assisted archival fixity verification framework"):
  Abstract: The number of public and private web archives has increased, and we implicitly trust content delivered by these archives. Fixity is checked to ensure an archived resource has remained unaltered since the time it was captured. Some web archives do not allow users to access fixity information and, more importantly, even if fixity information is available, it is provided by the same archive from which the archived resources are requested. In this research, we propose two approaches, namely Atomic and Block, to establish and check fixity of archived resources. In the Atomic approach, the fixity information of each archived web page is stored in a JSON file (or a manifest), and published in a well-known web location (an Archival Fixity server) before it is disseminated to several on-demand web archives. In the Block approach, we first batch together fixity information of multiple archived pages in a single binary-searchable file (or a block) before it is published and disseminated to archives. In both approaches, the fixity information is not obtained directly from archives. Instead, we compute the fixity information (e.g., hash values) based on the playback of archived resources. One advantage of the Atomic approach is the ability to verify fixity of archived pages even with the absence of the Archival Fixity server. The Block approach requires pushing fewer resources into archives, and it performs fixity verification faster than the Atomic approach. On average, it takes about 1.25X, 4X, and 36X longer to disseminate a manifest to this http URL, this http URL, and this http URL, respectively, than this http URL, while it takes 3.5X longer to disseminate a block to this http URL than this http URL. The Block approach performs 4.46X faster than the Atomic approach on verifying the fixity of archived pages.

Includes members:
  Member "mementomap framework for flexible and adaptive web archive profiling":
    also connected through other hyperedges:
      (none)
  Member "difficulties of timestamping archived web pages":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "collecting 16k archived web pages from 17 public web archives")
  Member "making digital artifacts on the web verifiable and reliable":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "nanopublications a growing resource of provenance centric scientific linked data")
  Member "decentralized trusted timestamping using the crypto currency bitcoin":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "the security reference architecture for blockchains towards a standardized model for studying vulnerabilities threats and defenses")
  Member "trusty uris verifiable immutable and permanent digital artifacts for linked data":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "nanopublications a growing resource of provenance centric scientific linked data")
  Member "http mailbox asynchronous restful communication":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "support for various http methods on the web")
  Member "memento time travel for the web":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "collecting 16k archived web pages from 17 public web archives")
  Member "preserving peer replicas by rate limited sampled voting":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a distributed integrity catalog for digital repositories")

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.DL(Digital Libraries)