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: "lightweight hierarchical model for hwsnet"
  Abstract: Heterogeneous wireless sensor networks (HWSNET) are more suitable for real life applications as compared to the homogeneous counterpart. Security of HWSNET becomes a very important issue with the rapid development of HWSNET. Intrusion detection system is one of the major and efficient defensive methods against attacks in HWSNET. Because of different constraints of sensor networks, security solutions have to be designed with limited usage of computation and resources. A particularly devastating attack is the sleep deprivation attack. Here a malicious node forces legitimate nodes to waste their energy by resisting the sensor nodes from going into low power sleep mode. The target of this attack is to maximize the power consumption of the affected node, thereby decreasing its battery life. Existing works on sleep deprivation attack have mainly focused on mitigation using MAC based protocols, such as S-MAC (sensor MAC), T-MAC (timeout MAC), B-MAC (Berkley MAC), G-MAC ( gateway MAC). In this article, a brief review of some of the recent intrusion detection systems in wireless sensor network environment is presented. Finally, a framework of cluster based layered countermeasure for Insomnia Detection has been proposed for heterogeneous wireless sensor network (HWSNET) to efficiently detect sleep deprivation attack. Simulation results on MATLAB exhibit the effectiveness of the proposed model.

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 artificial immune based approach for detection and isolation misbehavior attacks in wireless networks"
    - "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"

Connected through hyperedge HE-2 (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"
    - "an artificial immune based approach for detection and isolation misbehavior attacks in wireless networks"
    - "a new approach for improvement security against dos attacks in vehicular ad hoc network"
    - "amc model for denial of sleep attack detection"

Connected through hyperedge HE-3 (induced by source paper "study of security issues in pervasive environment of next generation internet of things"):
  with members:
    - "sleep deprivation attack detection in wireless sensor network"
    - "a survey of recent intrusion detection systems for wireless sensor network"

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)