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: "treatment of reactive routing protocols using second chance based on malicious behavior of nodes in manets"
  Abstract: Mobile nodes of various routing protocols in Mobile Ad hoc Networks follow different strategies in transmission and receiving of data. Security, packet delivery and routing overhead are important concerns for any protocol during designing them. The presence and absence of malicious nodes in the network affect a lot on the performance of the protocol. This research is mainly focused on the study of the threats, attacks and reasons for malicious behavior of nodes in the network for reactive routing protocols in MANETS. DSR and AODV are the two reactive routing protocols that were considered for the study to propose a second chance strategy to be given to the nodes considering the reason for malicious behavior to improve the packet delivery ratio and reduce the routing overhead in the network. A simulative study has been conducted using Ad hoc Simulator (ASIM) considering the DSR and AODV routing protocols in the presence of malicious nodes and in the absence of malicious nodes which showed that the packet delivery ratio is low and routing overhead is high in the absence of malicious nodes. The second chance strategy proposed considers the reasons for malicious behavior and helps the node to get reintegrated in the network to improve the packet delivery ratio and reduce the routing overhead.

Connected through hyperedge HE-1 (induced by source paper "secured approach towards reactive routing protocols using triple factor in mobile adhoc networks"):
  with members:
    - "an enhanced multipath strategy in mobile ad hoc routing protocols"
    - "a survey of distributed certificate authorities in manets"
    - "ideal node enquiry search algorithm inesh in manets"

Connected through hyperedge HE-2 (induced by source paper "challenges of internet of things and big data integration"):
  with members:
    - "evaluation of iot based computational intelligence tools for dna sequence analysis in bioinformatics"
    - "load balancing with preemptive and non preemptive task scheduling in cloud computing"
    - "challenges bridge between cloud and iot"
    - "the rise of internet of things iot in big healthcare data review and open research issues"
    - "multilingual website usability analysis based on an international user survey"
    - "a review on internet of things iot internet of everything ioe and internet of nano things iont"
    - "big data privacy in the internet of things era"

Connected through hyperedge HE-3 (induced by source paper "internet of things infrastructure architecture security and privacy"):
  with members:
    - "challenges of internet of things and big data integration"
    - "the rise of internet of things iot in big healthcare data review and open research issues"
    - "blockchain enabled enhanced iot ecosystem security"
    - "a review on internet of things iot internet of everything ioe and internet of nano things iont"

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)