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: "location privacy preservation in database driven wireless cognitive networks through encrypted probabilistic data structures"
  Abstract: In this paper, we propose new location privacy preserving schemes for database-driven cognitive radio networks that protect secondary users’ (SUs) location privacy while allowing them to learn spectrum availability in their vicinity. Our schemes harness probabilistic set membership data structures to exploit the structured nature of spectrum databases (DBs) and SUs’ queries. This enables us to create a compact representation of DB that could be queried by SUs without having to share their location with DB, thus guaranteeing their location privacy. Our proposed schemes offer different cost-performance characteristics. Our first scheme relies on a simple yet powerful two-party protocol that achieves unconditional security with a plausible communication overhead by making DB send a compacted version of its content to SU which needs only to query this data structure to learn spectrum availability. Our second scheme achieves significantly lower communication and computation overhead for SUs, but requires an additional architectural entity which receives the compacted version of the database and fetches the spectrum availability information in lieu of SUs to alleviate the overhead on the latter. We show that our schemes are secure, and also demonstrate that they offer significant advantages over existing alternatives for various performance and/or security metrics.

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"
    - "an efficient technique for protecting location privacy of cooperative spectrum sensing users"
    - "lpos location privacy for optimal sensing in cognitive radio networks"
    - "geo indistinguishability differential privacy for location based systems"

Connected through hyperedge HE-2 (induced by source paper "optimizing bloom filter challenges solutions and comparisons"):
  with members:
    - "a survey on security and privacy issues of bitcoin"
    - "a model for learned bloom filters and related structures"
    - "the case for learned index structures"
    - "adaptive cuckoo filters"
    - "cuckoo filter simplification and analysis"
    - "yes no bloom filter a way of representing sets with fewer false positives"
    - "a shifting bloom filter framework for set queries"
    - "don t thrash how to cache your hash on flash"

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"
    - "an efficient technique for protecting location privacy of cooperative spectrum sensing users"
    - "lpos location privacy for optimal sensing in cognitive radio networks"
    - "geo indistinguishability differential privacy for location based systems"

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)