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: "fuzzy extractors how to generate strong keys from biometrics and other noisy data"
  Abstract: We provide formal definitions and efficient secure techniques for turning noisy information into keys usable for any cryptographic application, and, in particular, reliably and securely authenticating biometric data. Our techniques apply not just to biometric information, but to any keying material that, unlike traditional cryptographic keys, is (1) not reproducible precisely and (2) not distributed uniformly. We propose two primitives: a fuzzy extractor reliably extracts nearly uniform randomness $R$ from its input; the extraction is error-tolerant in the sense that $R$ will be the same even if the input changes, as long as it remains reasonably close to the original. Thus, $R$ can be used as a key in a cryptographic application. A secure sketch produces public information about its input $w$ that does not reveal $w$ and yet allows exact recovery of $w$ given another value that is close to $w$. Thus, it can be used to reliably reproduce error-prone biometric inputs without incurring the security risk inherent in storing them. We define the primitives to be both formally secure and versatile, generalizing much prior work. In addition, we provide nearly optimal constructions of both primitives for various measures of “closeness” of input data, such as Hamming distance, edit distance, and set difference.

Connected through hyperedge HE-1 (induced by source paper "a capacity achieving one message key agreement with finite blocklength analysis"):
  with members:
    - "secret key agreement general capacity and second order asymptotics"
    - "polar coding for secret key generation"
    - "on the randomness of independent experiments"
    - "oblivious transfer amplification"

Connected through hyperedge HE-2 (induced by source paper "photonic physical unclonable functions from the concept to fully functional device operating in the field"):
  with members:
    - "svd based image processing applications state of the art contributions and research challenges"

Connected through hyperedge HE-3 (induced by source paper "communication for generating correlation a unifying survey"):
  with members:
    - "secret key capacity for multipleaccess channel with public feedback"
    - "exact exponent for soft covering"
    - "exact channel synthesis"
    - "strong converse using change of measure arguments"
    - "coding for positive rate in the source model key agreement problem"
    - "wiretap channels nonasymptotic fundamental limits"
    - "channel resolvability theorems for general sources and channels"
    - "strong functional representation lemma and applications to coding theorems"

Connected through hyperedge HE-4 (induced by source paper "communication for generating correlation a survey"):
  with members:
    - "secret key capacity for multipleaccess channel with public feedback"
    - "exact soft covering exponent"
    - "on exact and infty r enyi common informations"
    - "exact channel synthesis"
    - "strong converse using change of measure arguments"
    - "coding for positive rate in the source model key agreement problem"
    - "wiretap channels nonasymptotic fundamental limits"
    - "channel resolvability theorems for general sources and channels"

Connected through hyperedge HE-5 (induced by source paper "an overview of capacity results for synchronization channels"):
  with members:
    - "coding for deletion channels with multiple traces"
    - "coded trace reconstruction"
    - "coded trace reconstruction in a constant number of traces"
    - "optimally resilient codes for list decoding from insertions and deletions"
    - "zero error capacity of duplication channels"
    - "approximating edit distance within constant factor in truly sub quadratic time"
    - "maximum likelihood upper bounds on the capacities of discrete information stable channels"
    - "sharp analytical capacity upper bounds for sticky and related channels"

Connected through hyperedge HE-6 (induced by source paper "on the commitment capacity of unfair noisy channels"):
  with members:
    - "the secrecy capacity region of the gaussian mimo multi receiver wiretap channel"
    - "secrecy capacity region of fading broadcast channels"
    - "secrecy capacity of the wiretap channel with noisy feedback"
    - "the secrecy capacity of the mimo wiretap channel"
    - "commitment capacity of discrete memoryless channels"

Connected through hyperedge HE-7 (induced by source paper "single component privacy guarantees in helper data systems and sparse coding with ambiguation"):
  with members:
    - "reconstruction of privacy sensitive data from protected templates"
    - "privacy preserving identification via layered sparse code design distributed servers and multiple access authorization"
    - "sparse ternary codes for similarity search have higher coding gain than dense binary codes"
    - "privacy preserving identification using sparse approximation with ambiguization"

Connected through hyperedge HE-8 (induced by source paper "single component privacy guarantees in helper data systems and sparse coding"):
  with members:
    - "reconstruction of privacy sensitive data from protected templates"
    - "privacy preserving identification via layered sparse code design distributed servers and multiple access authorization"
    - "sparse ternary codes for similarity search have higher coding gain than dense binary codes"

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)