human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "ndtaodv neighbor defense technique for ad hoc on demand distance vector aodv to mitigate flood attack in manets"):
  Abstract: Mobile Ad Hoc Networks (MANETs) are collections of mobile nodes that can communicate with one another using multihop wireless links. MANETs are often deployed in the environments, where there is no fixed infrastructure and centralized management. The nodes of mobile ad hoc networks are susceptible to compromise. In such a scenario, designing an efficient, reliable and secure routing protocol has been a major challengesue over the last many years. The routing protocol Ad hoc On-demand Distance Vector (AODV) has no security measures in-built in it. It is vulnerable to many types of routing attacks. The flood attack is one of them. In this paper, we propose a simple and effective technique to secure Ad hoc Ondemand Distance Vector (AODV) routing protocol against flood attacks. To deal with a flood attack, we have proposed Neighbor Defense Technique for Ad hoc On-demand Distance Vector (NDTAODV). This makes AODV more robust. The proposed technique has been designed to isolate the flood attacker with the use of timers, peak value and hello alarm technique. We have simulated our work in Network Simulator NS-2.33 (NS-2) with different pause times by way of different number of malicious nodes. We have compared the performance of NDTAODV with the AODV in normal situation as well as in the presence of malicious attacks. We have considered Packet Delivery Fraction (PDF), Average Throughput (AT) and Normalized Routing Load (NRL) for comparing the performance of NDTAODV and AODV.

Includes members:
  Member "aodvsec a novel approach to secure ad hoc on demand distance vector aodv routing protocol from insider attacks in manets":
    also connected through other hyperedges:
      (none)
  Member "performance analysis of aodv dsdv and dsr in manets":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "ideal node enquiry search algorithm inesh in manets")
  Member "dpraodv a dyanamic learning system against blackhole attack in aodv based manet":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a study of research trends and issues in wireless ad hoc networks")

Question: Please tell me which class the source paper 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)