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: "lpos location privacy for optimal sensing in cognitive radio networks"
  Abstract: Cognitive Radio Networks (CRNs) enable opportunistic access to the licensed channel resources by allowing unlicensed users to exploit vacant channel opportunities. One effective technique through which unlicensed users, often referred to as Secondary Users (SUs), acquire whether a channel is vacant is cooperative spectrum sensing. Despite its effectiveness in enabling CRN access, cooperative sensing suffers from location privacy threats, merely because the sensing reports that need to be exchanged among the SUs to perform the sensing task are highly correlated to the SUs' locations. In this paper, we develop a new Location Privacy for Optimal Sensing (LPOS) scheme that preserves the location privacy of SUs while achieving optimal sensing performance through voting-based sensing. In addition, LPOS is the only alternative among existing CRN location privacy preserving schemes (to the best of our knowledge) that ensures high privacy, achieves fault tolerance, and is robust against the highly dynamic and wireless nature of CRNs.

Connected through hyperedge HE-1 (induced by source paper "location privacy in cognitive radios with multi server private information retrieval"):
  with members:
    - "preserving the location privacy of secondary users in cooperative spectrum sensing"
    - "location privacy in cognitive radio networks a survey"
    - "when the hammer meets the nail multi server pir for database driven crn with location privacy assurance"
    - "location privacy preservation in database driven wireless cognitive networks through encrypted probabilistic data structures"
    - "an efficient technique for protecting location privacy of cooperative spectrum sensing users"
    - "geo indistinguishability differential privacy for location based systems"

Connected through hyperedge HE-2 (induced by source paper "location privacy in cognitive radio networks a survey"):
  with members:
    - "preserving the location privacy of secondary users in cooperative spectrum sensing"
    - "an efficient technique for protecting location privacy of cooperative spectrum sensing users"
    - "securefind secure and privacy preserving object finding via mobile crowdsourcing"
    - "geo indistinguishability differential privacy for location based systems"
    - "security of spectrum learning in cognitive radios"
    - "channel assignment with access contention resolution for cognitive radio networks"
    - "towards practical oblivious ram"
    - "multi agent q learning of channel selection in multi user cognitive radio systems a two by two case"

Connected through hyperedge HE-3 (induced by source paper "when the hammer meets the nail multi server pir for database driven crn with location privacy assurance"):
  with members:
    - "preserving the location privacy of secondary users in cooperative spectrum sensing"
    - "location privacy in cognitive radio networks a survey"
    - "location privacy preservation in database driven wireless cognitive networks through encrypted probabilistic data structures"
    - "an efficient technique for protecting location privacy of cooperative spectrum sensing users"
    - "geo indistinguishability differential privacy for location based systems"

Connected through hyperedge HE-4 (induced by source paper "location privacy preservation in database driven wireless cognitive networks through encrypted probabilistic data structures"):
  with members:
    - "preserving the location privacy of secondary users in cooperative spectrum sensing"
    - "location privacy in cognitive radio networks a survey"
    - "an efficient technique for protecting location privacy of cooperative spectrum sensing users"
    - "geo indistinguishability differential privacy for location based systems"

Connected through hyperedge HE-5 (induced by source paper "preserving the location privacy of secondary users in cooperative spectrum sensing"):
  with members:
    - "an efficient technique for protecting location privacy of cooperative spectrum sensing users"

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)