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 "degree based outlier detection within ip traffic modelled as a link stream"):
  Abstract: This paper aims at precisely detecting and identifying anomalous events in IP traffic. To this end, we adopt the link stream formalism which properly captures temporal and structural features of the data. Within this framework, we focus on finding anomalous behaviours with respect to the degree of IP addresses over time. Due to diversity in IP profiles, this feature is typically distributed heterogeneously, preventing us to directly find anomalies. To deal with this challenge, we design a method to detect outliers as well as precisely identify their cause in a sequence of similar heterogeneous distributions. We apply it to several MAWI captures of IP traffic and we show that it succeeds in detecting relevant patterns in terms of anomalous network activity.

Includes members:
  Member "non altering time scales for aggregation of dynamic networks into series of graphs":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "stream graphs and link streams for the modeling of interactions over time")
  Member "stream graphs and link streams for the modeling of interactions over time":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "finding temporal patterns using algebraic fingerprints")
  Member "discovering patterns of interest in ip traffic using cliques in bipartite link streams":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "weighted bipartite or directed stream graphs for the modeling of temporal networks")
  Member "an algebraic approach to temporal network analysis based on temporal quantities":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "temporal bibliographic networks")
  Member "a unifying model for representing time varying graphs":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "algorithmic networks central time to trigger expected emergent open endedness")
  Member "network traffic anomaly detection":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "your smart home can t keep a secret towards automated fingerprinting of iot traffic with neural networks")
  Member "graph based anomaly detection and description a survey":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "transferring robustness for graph neural network against poisoning attacks")
  Member "temporal reachability graphs":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "counting causal paths in big times series data on 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.SI(Social and Information Networks)