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: "a framework for mitigating zero day attacks in iot"
  Abstract: Internet of Things (IoT) aims at providing connectivity between every computing entity. However, this facilitation is also leading to more cyber threats which may exploit the presence of a vulnerability of a period of time. One such vulnerability is the zero-day threat that may lead to zero-day attacks which are detrimental to an enterprise as well as the network security. In this article, a study is presented on the zero-day threats for IoT networks and a context graph-based framework is presented to provide a strategy for mitigating these attacks. The proposed approach uses a distributed diagnosis system for classifying the context at the central service provider as well as at the local user site. Once a potential zero-day attack is identified, a critical data sharing protocol is used to transmit alert messages and reestablish the trust between the network entities and the IoT devices. The results show that the distributed approach is capable of mitigating the zero-day threats efficiently with 33% and 21% improvements in terms of cost of operation and communication overheads, respectively, in comparison with the centralized diagnosis system.

Connected through hyperedge HE-1 (induced by source paper "a survey on the security and the evolution of osmotic and catalytic computing for 5g networks"):
  with members:
    - "5g nr jamming spoofing and sniffing threat assessment and mitigation"
    - "nhad neuro fuzzy based horizontal anomaly detection in online social networks"
    - "multi radio 5g architecture for connected and autonomous vehicles application and design insights"
    - "rehand secure region based fast handover with user anonymity for small cell networks in 5g"
    - "robust physical layer security for power domain non orthogonal multiple access based hetnets and hudns sic avoidance at eavesdroppers"
    - "a survey on the security of pervasive online social networks posns"
    - "a survey of physical layer security techniques for 5g wireless networks and challenges ahead"
    - "self enforcing game theory based resource allocation for lorawan assisted public safety communications"

Connected through hyperedge HE-2 (induced by source paper "security privacy and trust for smart mobile internet of things m iot a survey"):
  with members:
    - "nhad neuro fuzzy based horizontal anomaly detection in online social networks"
    - "mobile edge computing fog et al a survey and analysis of security threats and challenges"
    - "advertising in the iot era vision and challenges"
    - "managing service heterogeneity using osmotic computing"
    - "extension of mih to support fpmipv6 for optimized heterogeneous handover"
    - "securing wireless communications of the internet of things from the physical layer an overview"
    - "traffic aware patching for cyber security in mobile iot"
    - "trifecta security energy efficiency and communication capacity comparison for wireless iot devices"

Connected through hyperedge HE-3 (induced by source paper "the performance of machine and deep learning classifiers in detecting zero day vulnerabilities"):
  with members:
    - "evaluation of machine learning classifiers for zero day intrusion detection an analysis on cic aws 2018 dataset"

Connected through hyperedge HE-4 (induced by source paper "a survey on the security of pervasive online social networks posns"):
  with members:
    - "nhad neuro fuzzy based horizontal anomaly detection in online social networks"
    - "self enforcing game theory based resource allocation for lorawan assisted public safety communications"
    - "managing service heterogeneity using osmotic computing"
    - "netspam a network based spam detection framework for reviews in online social media"
    - "a privacy preserving community based p2p osns using broadcast encryption supporting recommendation mechanism"
    - "extension of mih to support fpmipv6 for optimized heterogeneous handover"
    - "analyzing resilience of interest based social networks against node and link failures"
    - "anomaly detection in online social networks"

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)