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: "a theoretical analysis of authentication privacy and reusability across secure biometric systems"
  Abstract: We present a theoretical framework for the analysis of privacy and security tradeoffs in secure biometric authentication systems. We use this framework to conduct a comparative information-theoretic analysis of two biometric systems that are based on linear error correction codes, namely fuzzy commitment and secure sketches. We derive upper bounds for the probability of false rejection ($P_{FR}$) and false acceptance ($P_{FA}$) for these systems. We use mutual information to quantify the information leaked about a user's biometric identity, in the scenario where one or multiple biometric enrollments of the user are fully or partially compromised. We also quantify the probability of successful attack ($P_{SA}$) based on the compromised information. Our analysis reveals that fuzzy commitment and secure sketch systems have identical $P_{FR}, P_{FA}, P_{SA}$ and information leakage, but secure sketch systems have lower storage requirements. We analyze both single-factor (keyless) and two-factor (key-based) variants of secure biometrics, and consider the most general scenarios in which a single user may provide noisy biometric enrollments at several access control devices, some of which may be subsequently compromised by an attacker. Our analysis highlights the revocability and reusability properties of key-based systems and exposes a subtle design tradeoff between reducing information leakage from compromised systems and preventing successful attacks on systems whose data have not been compromised.

Connected through hyperedge HE-1 (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"
    - "secure and reliable key agreement with physical unclonable functions"
    - "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"

Connected through hyperedge HE-2 (induced by source paper "analysis of channel based user authentication by key less and key based approaches"):
  with members:
    - "artificial noise aided message authentication codes with information theoretic security"
    - "on the error region for channel estimation based physical layer authentication over rayleigh fading"
    - "on the optimality of keyless authentication in a noisy model"
    - "principles of physical layer security in multiuser wireless networks a survey"
    - "using the physical layer for wireless authentication in time variant channels"

Connected through hyperedge HE-3 (induced by source paper "privacy secrecy and storage with multiple noisy measurements of identifiers"):
  with members:
    - "secret key based identification and authentication with a privacy constraint"
    - "secret key generation using correlated sources and channels"
    - "separation of reliability and secrecy in rate limited secret key generation"
    - "secrecy via sources and channels"
    - "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)