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: "oblivious dns practical privacy for dns queries"
  Abstract: Virtually every Internet communication typically involves a Domain Name System (DNS) lookup for the destination server that the client wants to communicate with. Operators of DNS recursive resolvers---the machines that receive a client's query for a domain name and resolve it to a corresponding IP address---can learn significant information about client activity. Past work, for example, indicates that DNS queries reveal information ranging from web browsing activity to the types of devices that a user has in their home. Recognizing the privacy vulnerabilities associated with DNS queries, various third parties have created alternate DNS services that obscure a user's DNS queries from his or her Internet service provider. Yet, these systems merely transfer trust to a different third party. We argue that no single party ought to be able to associate DNS queries with a client IP address that issues those queries. To this end, we present Oblivious DNS (ODNS), which introduces an additional layer of obfuscation between clients and their queries. To do so, ODNS uses its own authoritative namespace; the authoritative servers for the ODNS namespace act as recursive resolvers for the DNS queries that they receive, but they never see the IP addresses for the clients that initiated these queries. We present an initial deployment of ODNS; our experiments show that ODNS introduces minimal performance overhead, both for individual queries and for web page loads. We design ODNS to be compatible with existing DNS protocols and infrastructure, and we are actively working on an open standard with the IETF.

Connected through hyperedge HE-1 (induced by source paper "encrypted dns privacy a traffic analysis perspective"):
  with members:
    - "analyzing the costs and benefits of dns dot and doh for the modern web"
    - "deep fingerprinting undermining website fingerprinting defenses with deep learning"
    - "automated website fingerprinting through deep learning"
    - "how unique is your onion an analysis of the fingerprintability of tor onion services"
    - "k fingerprinting a robust scalable website fingerprinting technique"
    - "toward an efficient website fingerprinting defense"
    - "i know why you went to the clinic risks and realization of https traffic analysis"

Connected through hyperedge HE-2 (induced by source paper "patterns and interactions in network security"):
  with members:
    - "active internet traffic filtering real time response to denial of service attacks"

Connected through hyperedge HE-3 (induced by source paper "keeping the smart home private with smart er iot traffic shaping"):
  with members:
    - "a developer friendly library for smart home iot privacy preserving traffic obfuscation"
    - "a smart home is no castle privacy vulnerabilities of encrypted iot traffic"
    - "spying on the smart home privacy attacks and defenses on encrypted iot traffic"
    - "closing the blinds four strategies for protecting smart home privacy from network observers"
    - "iot sentinel demo automated device type identification for security enforcement in iot"
    - "toward an efficient website fingerprinting defense"
    - "no nat d user left behind fingerprinting users behind nat from netflow records alone"
    - "website detection using remote traffic analysis"

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)