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: "secret key based identification and authentication with a privacy constraint"
  Abstract: We consider the problem of identification and authentication based on secret key generation from some user-generated source data (e.g., a biometric source). The goal is to reliably identify users pre-enrolled in a database as well as authenticate them based on the estimated secret key while preserving the privacy of the enrolled data and of the generated keys. We characterize the optimal tradeoff between the identification rate, the compression rate of the users' source data, information leakage rate, and secret key rate. In particular, we provide a coding strategy based on layered random binning which is shown to be optimal. In addition, we study a related secure identification/authentication problem where an adversary tries to deceive the system using its own data. Here the optimal tradeoff between the identification rate, compression rate, leakage rate, and exponent of the maximum false acceptance probability is provided. The results reveal a close connection between the optimal secret key rate and the false acceptance exponent of the identification/authentication system.

Connected through hyperedge HE-1 (induced by source paper "fundamental limits of biometric identification systems with strong secrecy"):
  with members:
    - "private authentication with physical identifiers through broadcast channel measurements"
    - "identification secrecy template and privacy leakage of biometric identification system under noisy enrollment"
    - "fundamental limits of identification system with secret binding under noisy enrollment"
    - "a new wiretap channel model and its strong secrecy capacity"
    - "code constructions for physical unclonable functions and biometric secrecy systems"
    - "privacy secrecy and storage with multiple noisy measurements of identifiers"
    - "achievability proof via output statistics of random binning"

Connected through hyperedge HE-2 (induced by source paper "identification secrecy template and privacy leakage of biometric identification system under noisy enrollment"):
  with members:
    - "privacy secrecy and storage with multiple noisy measurements of identifiers"

Connected through hyperedge HE-3 (induced by source paper "privacy secrecy and storage with multiple noisy measurements of identifiers"):
  with members:
    - "secret key generation using correlated sources and channels"
    - "separation of reliability and secrecy in rate limited secret key generation"
    - "secrecy via sources and channels"
    - "a theoretical analysis of authentication privacy and reusability across secure biometric systems"
    - "fuzzy extractors how to generate strong keys from biometrics and other noisy data"

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)