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: "uncertain wiretap channels and secure estimation"
  Abstract: Uncertain wiretap channels are introduced. Their zero-error secrecy capacity is defined. If the sensor-estimator channel is perfect, it is also calculated. Further properties are discussed. The problem of estimating a dynamical system with nonstochastic disturbances is studied where the sensor is connected to the estimator and an eavesdropper via an uncertain wiretap channel. The estimator should obtain a uniformly bounded estimation error whereas the eavesdropper's error should tend to infinity. It is proved that the system can be estimated securely if the zero-error capacity of the sensor-estimator channel is strictly larger than the logarithm of the system's unstable pole and the zero-error secrecy capacity of the uncertain wiretap channel is positive.

Connected through hyperedge HE-1 (induced by source paper "variable length coding for zero error channel capacity"):
  with members:
    - "zero error capacity of duplication channels"
    - "bounds on the reliability of typewriter channels"
    - "zero error capacity of p ary shift channels and fifo queues"
    - "the rho capacity of a graph"
    - "rate distance tradeoff for codes above graph capacity"
    - "secure estimation and zero error secrecy capacity"
    - "graph information ratio"
    - "new lower bounds for the shannon capacity of odd cycles"

Connected through hyperedge HE-2 (induced by source paper "noiseless privacy"):
  with members:
    - "an operational approach to information leakage"
    - "on the relation between identifiability differential privacy and mutual information privacy"
    - "extremal mechanisms for local differential privacy"
    - "utility privacy tradeoffs in databases an information theoretic approach"
    - "a nonstochastic information theory for communication and state estimation"
    - "the composition theorem for differential privacy"
    - "information masking and amplification the source coding setting"
    - "privacy against statistical inference"

Connected through hyperedge HE-3 (induced by source paper "developing non stochastic privacy preserving policies using agglomerative clustering"):
  with members:
    - "robustness of maximal alpha leakage to side information"
    - "a submodularity based agglomerative clustering algorithm for the privacy funnel"
    - "tunable measures for information leakage and applications to privacy utility tradeoffs"
    - "privacy preserving prediction"
    - "notes on information theoretic privacy"
    - "from the information bottleneck to the privacy funnel"
    - "a nonstochastic information theory for communication and state estimation"
    - "privacy against statistical inference"

Connected through hyperedge HE-4 (induced by source paper "development and analysis of deterministic privacy preserving policies using non stochastic information theory"):
  with members:
    - "extremal mechanisms for local differential privacy"
    - "utility privacy tradeoffs in databases an information theoretic approach"
    - "a nonstochastic information theory for communication and state estimation"
    - "information masking and amplification the source coding setting"
    - "the optimal mechanism in differential privacy"
    - "privacy against statistical inference"
    - "on the relation between differential privacy and quantitative information flow"

Connected through hyperedge HE-5 (induced by source paper "non stochastic hypothesis testing with application to privacy against hypothesis testing adversary"):
  with members:
    - "issues encountered deploying differential privacy"
    - "extremal mechanisms for local differential privacy"
    - "utility privacy tradeoffs in databases an information theoretic approach"
    - "a nonstochastic information theory for communication and state estimation"

Connected through hyperedge HE-6 (induced by source paper "state secrecy codes for networked linear systems"):
  with members:
    - "remote state estimation over packet dropping links in the presence of an eavesdropper"
    - "state estimation with secrecy against eavesdroppers"
    - "a survey on wireless security technical challenges recent advances and future trends"
    - "the secrecy capacity of the mimo wiretap channel"

Connected through hyperedge HE-7 (induced by source paper "a distortion based approach for protecting inferences"):
  with members:
    - "secret communication over broadcast erasure channels with state feedback"
    - "rate distortion theory for secrecy systems"

Connected through hyperedge HE-8 (induced by source paper "state estimation with secrecy against eavesdroppers"):
  with members:
    - "a survey on wireless security technical challenges recent advances and future trends"
    - "the secrecy capacity of the mimo wiretap channel"

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.SY(Systems and Control)