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: "an artificial immune based approach for detection and isolation misbehavior attacks in wireless networks"
  Abstract: MANETs (Mobile Ad-hoc Networks) is a temporal network, which is managed by autonomous nodes, which have the ability to communicate with each other without having fixed network infrastructure or any central base station. Due to some reasons such as dynamic changes of the network topology, trusting the nodes to each other, lack of fixed substructure for the analysis of nodes behaviors and loss of specific offensive lines, this type of networks is not supportive against malicious nodes attacks. One of these attacks is black hole attack. In this attack, the malicious nodes absorb data packets and destroy them. Thus, it is essential to present an algorithm against the black hole attacks. This paper proposed a new approach, which improvement the security of DSR routing protocol to encounter the black hole attacks. This schema tries to identify malicious nodes according to nodes behaviors in a MANETs and isolate them from routing. The proposed protocol, called AIS-DSR (Artificial Immune System DSR) employ AIS (Artificial Immune System) to defend against black hole attacks. AIS-DSR is evaluated through extensive simulations in the ns-2 environment. The results show that AIS-DSR outperforms other existing solutions in terms of throughput, end-to-end delay, packets loss ratio and packets drop ratio.

Connected through hyperedge HE-1 (induced by source paper "a novel countermeasure technique to protect wsn against denial of sleep attacks using firefly and hopfield neural network hnn algorithms"):
  with members:
    - "securing of unmanned aerial systems uas against security threats using human immune system"
    - "an efficient routing protocol in mobile ad hoc networks by using artificial immune system"
    - "a new approach for improvement security against dos attacks in vehicular ad hoc network"
    - "sleep deprivation attack detection in wireless sensor network"
    - "amc model for denial of sleep attack detection"
    - "lightweight hierarchical model for hwsnet"

Connected through hyperedge HE-2 (induced by source paper "multi level trust based intelligence schema for securing of internet of things iot against security threats using cryptographic authentication"):
  with members:
    - "securing of unmanned aerial systems uas against security threats using human immune system"
    - "securing wireless sensor networks against denial of sleep attacks using rsa cryptography algorithm and interlock protocol"
    - "security of the internet of things vulnerabilities attacks and countermeasures"
    - "an efficient routing protocol in mobile ad hoc networks by using artificial immune system"
    - "a new approach for improvement security against dos attacks in vehicular ad hoc network"

Connected through hyperedge HE-3 (induced by source paper "securing wireless sensor networks against denial of sleep attacks using rsa cryptography algorithm and interlock protocol"):
  with members:
    - "securing of unmanned aerial systems uas against security threats using human immune system"
    - "a novel countermeasure technique to protect wsn against denial of sleep attacks using firefly and hopfield neural network hnn algorithms"
    - "a new approach for improvement security against dos attacks in vehicular ad hoc network"
    - "amc model for denial of sleep attack detection"
    - "lightweight hierarchical model for hwsnet"

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)