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: "dendritic cells for syn scan detection"
  Abstract: Artificial immune systems have previously been applied to the problem of intrusion detection. The aim of this research is to develop an intrusion detection system based on the function of Dendritic Cells (DCs). DCs are antigen presenting cells and key to activation of the human immune system, behaviour which has been abstracted to form the Dendritic Cell Algorithm (DCA). In algorithmic terms, individual DCs perform multi-sensor data fusion, asynchronously correlating the the fused data signals with a secondary data stream. Aggregate output of a population of cells, is analysed and forms the basis of an anomaly detection system. In this paper the DCA is applied to the detection of outgoing port scans using TCP SYN packets. Results show that detection can be achieved with the DCA, yet some false positives can be encountered when simultaneously scanning and using other network services. Suggestions are made for using adaptive signals to alleviate this uncovered problem.

Connected through hyperedge HE-1 (induced by source paper "systematic construction of anomaly detection benchmarks from real data"):
  with members:
    - "dendritic cells for anomaly detection"

Connected through hyperedge HE-2 (induced by source paper "integrating real time analysis with the dendritic cell algorithm through segmentation"):
  with members:
    - "the deterministic dendritic cell algorithm"
    - "further exploration of the dendritic cell algorithm antigen multiplier and time windows"
    - "the application of a dendritic cell algorithm to a robotic classifier"
    - "dca for bot detection"

Connected through hyperedge HE-3 (induced by source paper "further exploration of the dendritic cell algorithm antigen multiplier and time windows"):
  with members:
    - "introducing dendritic cells as a novel immune inspired algorithm for anomoly detection"
    - "articulation and clarification of the dendritic cell algorithm"

Connected through hyperedge HE-4 (induced by source paper "performance evaluation of dca and src on a single bot detection"):
  with members:
    - "biological inspiration for artificial immune systems"
    - "information fusion for anomaly detection with the dendritic cell algorithm"
    - "introducing dendritic cells as a novel immune inspired algorithm for anomoly detection"
    - "detecting bots based on keylogging activities"
    - "dca for bot detection"

Connected through hyperedge HE-5 (induced by source paper "detecting danger the dendritic cell algorithm"):
  with members:
    - "information fusion for anomaly detection with the dendritic cell algorithm"
    - "information fusion in the immune system"
    - "the application of a dendritic cell algorithm to a robotic classifier"
    - "articulation and clarification of the dendritic cell algorithm"

Connected through hyperedge HE-6 (induced by source paper "dca for bot detection"):
  with members:
    - "biological inspiration for artificial immune systems"
    - "information fusion for anomaly detection with the dendritic cell algorithm"

Connected through hyperedge HE-7 (induced by source paper "sensing danger innate immunology for intrusion detection"):
  with members:
    - "information fusion for anomaly detection with the dendritic cell algorithm"
    - "towards a conceptual framework for innate immunity"
    - "the application of a dendritic cell algorithm to a robotic classifier"
    - "articulation and clarification of the dendritic cell algorithm"
    - "immune system approaches to intrusion detection a review"
    - "libtissue implementing innate immunity"
    - "dendritic cells for anomaly detection"
    - "the danger theory and its application to artificial immune systems"

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.AI(Artificial Intelligence)