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 "using lstm encoder decoder algorithm for detecting anomalous ads b messages"):
  Abstract: Although the ADS-B system is going to play a major role in the safe navigation of airplanes and air traffic control (ATC) management, it is also well known for its lack of security mechanisms. Previous research has proposed various methods for improving the security of the ADS-B system and mitigating associated risks. However, these solutions typically require the use of additional participating nodes (or sensors) (e.g., to verify the location of the airplane by analyzing the physical signal) or modification of the current protocol architecture (e.g., adding encryption or authentication mechanisms.) Due to the regulation process regarding avionic systems and the fact that the ADS-B system is already deployed in most airplanes, applying such modifications to the current protocol at this stage is impractical. In this paper we propose an alternative security solution for detecting anomalous ADS-B messages aimed at the detection of spoofed or manipulated ADS- B messages sent by an attacker or compromised airplane. The proposed approach utilizes an LSTM encoder-decoder algorithm for modeling flight routes by analyzing sequences of legitimate ADS-B messages. Using these models, aircraft can autonomously evaluate received ADS-B messages and identify deviations from the legitimate flight path (i.e., anomalies). We examined our approach on six different flight route datasets to which we injected different types of anomalies. Using our approach we were able to detect all of the injected attacks with an average false alarm rate of 4.3% for all of datasets.

Includes members:
  Member "lstm a search space odyssey":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "refined gate a simple and effective gating mechanism for recurrent units")
  Member "a hierarchical recurrent encoder decoder for generative context aware query suggestion":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "clara clinical report auto completion")
  Member "on the security of the automatic dependent surveillance broadcast protocol":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "uav swarm enabled aerial comp a physical layer security perspective")

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)