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 "active learning for wireless iot intrusion detection"):
  Abstract: The Internet of Things (IoT) is becoming truly ubiquitous in our everyday lives, but it also faces unique security challenges. Intrusion detection is critical for the security and safety of a wireless IoT network. This article discusses the human-in-theloop active learning approach for wireless intrusion detection. We first present the fundamental challenges against the design of a successful intrusion detection system for a wireless IoT network. We then briefly review the rudimentary concepts of active learning and propose its employment in the diverse applications of wireless intrusion detection. An experimental example is also presented to show the significant performance improvement of the active learning method over the traditional supervised learning approach. While machine learning (ML) techniques have been widely employed for intrusion detection, the application of human-in-the-loop ML that leverages both machine and human intelligence to intrusion detection of IoT is still in its infancy. We hope this article can assist readers in understanding the key concepts of active learning and spur further research in this area.

Includes members:
  Member "achieving efficient and secure data acquisition for cloud supported internet of things in smart grid":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "interest related item similarity model based on multimodal data for top n recommendation")
  Member "xgboost a scalable tree boosting system":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "monotonic cardinality estimation of similarity selection a deep learning approach")

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.CR(Cryptography and Security)