human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "clusters in the expanse understanding and unbiasing ipv6 hitlists"
  Abstract: Network measurements are an important tool in understanding the Internet. Due to the expanse of the IPv6 address space, exhaustive scans as in IPv4 are not possible for IPv6. In recent years, several studies have proposed the use of target lists of IPv6 addresses, called IPv6 hitlists. #R##N#In this paper, we show that addresses in IPv6 hitlists are heavily clustered. We present novel techniques that allow IPv6 hitlists to be pushed from quantity to quality. We perform a longitudinal active measurement study over 6 months, targeting more than 50 M addresses. We develop a rigorous method to detect aliased prefixes, which identifies 1.5 % of our prefixes as aliased, pertaining to about half of our target addresses. Using entropy clustering, we group the entire hitlist into just 6 distinct addressing schemes. Furthermore, we perform client measurements by leveraging crowdsourcing. #R##N#To encourage reproducibility in network measurement research and to serve as a starting point for future IPv6 studies, we publish source code, analysis tools, and data.

Connected through hyperedge HE-1 (induced by source paper "discovering the ipv6 network periphery"):
  with members:
    - "eui 64 considered harmful"
    - "in the ip of the beholder strategies for active ipv6 topology discovery"
    - "yarrp ing the internet randomized high speed active topology discovery"
    - "entropy ip uncovering structure in ipv6 addresses"
    - "temporal and spatial classification of active ipv6 addresses"

Connected through hyperedge HE-2 (induced by source paper "eui 64 considered harmful"):
  with members:
    - "in the ip of the beholder strategies for active ipv6 topology discovery"
    - "temporal and spatial classification of active ipv6 addresses"

Connected through hyperedge HE-3 (induced by source paper "in the ip of the beholder strategies for active ipv6 topology discovery"):
  with members:
    - "kip a measured approach to ipv6 address anonymization"
    - "yarrp ing the internet randomized high speed active topology discovery"
    - "entropy ip uncovering structure in ipv6 addresses"
    - "scanning the ipv6 internet towards a comprehensive hitlist"
    - "temporal and spatial classification of active ipv6 addresses"
    - "efficient algorithms for large scale topology discovery"

Question: Please tell me which class the center node 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.NI(Networking and Internet Architecture)