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: "secure and reliable key agreement with physical unclonable functions"
  Abstract: Different transforms used in binding a secret key to correlated physical-identifier outputs are compared. Decorrelation efficiency is the metric used to determine transforms that give highly-uncorrelated outputs. Scalar quantizers are applied to transform outputs to extract uniformly distributed bit sequences to which secret keys are bound. A set of transforms that perform well in terms of the decorrelation efficiency is applied to ring oscillator (RO) outputs to improve the uniqueness and reliability of extracted bit sequences, to reduce the hardware area and information leakage about the key and RO outputs, and to maximize the secret-key length. Low-complexity error-correction codes are proposed to illustrate two complete key-binding systems with perfect secrecy, and better secret-key and privacy-leakage rates than existing methods. A reference hardware implementation is also provided to demonstrate that the transform-coding approach occupies a small hardware area.

Connected through hyperedge HE-1 (induced by source paper "biometric and physical identifiers with correlated noise for controllable private authentication"):
  with members:
    - "private authentication with physical identifiers through broadcast channel measurements"
    - "controllable identifier measurements for private authentication with secret keys"
    - "coding for positive rate in the source model key agreement problem"
    - "code constructions for physical unclonable functions and biometric secrecy systems"
    - "privacy secrecy and storage with multiple noisy measurements of identifiers"
    - "converses for secret key agreement and secure computing"
    - "polar coding for secret key generation"
    - "secret key generation using correlated sources and channels"

Connected through hyperedge HE-2 (induced by source paper "differential privacy for eye tracking with temporal correlations"):
  with members:
    - "differential privacy for eye tracking data"
    - "privacy aware eye tracking using differential privacy"
    - "collecting telemetry data privately"
    - "pupil an open source platform for pervasive eye tracking and mobile gaze based interaction"

Connected through hyperedge HE-3 (induced by source paper "private authentication with physical identifiers through broadcast channel measurements"):
  with members:
    - "controllable identifier measurements for private authentication with secret keys"
    - "privacy secrecy and storage with multiple noisy measurements of identifiers"
    - "polar coding for secret key generation"
    - "achievability proof via output statistics of random binning"

Connected through hyperedge HE-4 (induced by source paper "code constructions for physical unclonable functions and biometric secrecy systems"):
  with members:
    - "controllable identifier measurements for private authentication with secret keys"
    - "privacy secrecy and storage with multiple noisy measurements of identifiers"
    - "the likelihood encoder for lossy compression"
    - "polar coding for secret key generation"
    - "informational divergence approximations to product distributions"
    - "secret key generation using correlated sources and channels"
    - "separation of reliability and secrecy in rate limited secret key generation"
    - "achievability proof via output statistics of random binning"

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.CR(Cryptography and Security)