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: "intercept behavior analysis of industrial wireless sensor networks in the presence of eavesdropping attack"
  Abstract: This paper studies the intercept behavior of an industrial wireless sensor network (WSN) consisting of a sink node and multiple sensors in the presence of an eavesdropping attacker, where the sensors transmit their sensed information to the sink node through wireless links. Due to the broadcast nature of radio wave propagation, the wireless transmission from the sensors to the sink can be readily overheard by the eavesdropper for interception purposes. In an information-theoretic sense, the secrecy capacity of the wireless transmission is the difference between the channel capacity of the main link (from sensor to sink) and that of the wiretap link (from sensor to eavesdropper). If the secrecy capacity becomes non-positive due to the wireless fading effect, the sensor's data transmission could be successfully intercepted by the eavesdropper and an intercept event occurs in this case. However, in industrial environments, the presence of machinery obstacles, metallic frictions and engine vibrations makes the wireless fading fluctuate drastically, resulting in the degradation of the secrecy capacity. As a consequence, an optimal sensor scheduling scheme is proposed in this paper to protect the legitimate wireless transmission against the eavesdropping attack, where a sensor with the highest secrecy capacity is scheduled to transmit its sensed information to the sink. Closed-form expressions of the probability of occurrence of an intercept event (called intercept probability) are derived for the conventional round-robin scheduling and the proposed optimal scheduling schemes. Also, an asymptotic intercept probability analysis is conducted to provide an insight into the impact of the sensor scheduling on the wireless security. Numerical results demonstrate that the proposed sensor scheduling scheme outperforms the conventional round-robin scheduling in terms of the intercept probability.

Connected through hyperedge HE-1 (induced by source paper "data management in industry 4 0 state of the art and open challenges"):
  with members:
    - "avoiding the internet of insecure industrial things"
    - "energy optimization of robotic cells"
    - "sre semantic rules engine for the industrial internet of things gateways"
    - "covert attacks in cyber physical control systems"
    - "acceleration of a full scale industrial cfd application with op2"
    - "a cyber physical system based approach for industrial automation systems"

Connected through hyperedge HE-2 (induced by source paper "secrecy outage for wireless sensor networks"):
  with members:
    - "improving physical layer security in wireless communications using diversity techniques"
    - "optimal relay selection for physical layer security in cooperative wireless networks"
    - "rethinking the secrecy outage formulation a secure transmission design perspective"

Connected through hyperedge HE-3 (induced by source paper "data management in networked industrial environments state of the art and open challenges"):
  with members:
    - "energy optimization of robotic cells"
    - "sre semantic rules engine for the industrial internet of things gateways"
    - "covert attacks in cyber physical control systems"

Connected through hyperedge HE-4 (induced by source paper "attack analysis for distributed control systems an internal model principle approach"):
  with members:
    - "transfer functions in consensus systems with higher order dynamics and external inputs"

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.IT(Information Theory)