human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "biometric and physical identifiers with correlated noise for controllable private authentication"):
  Abstract: The problem of secret-key based authentication under privacy and storage constraints on the source sequence is considered. The identifier measurement channels during authentication are assumed to be controllable via a cost-constrained action sequence. Single-letter inner and outer bounds for the key-leakage-storage-cost regions are derived for a generalization of a classic two-terminal key agreement model with an eavesdropper that observes a sequence that is correlated with the sequences observed by the legitimate terminals. The additions to the model are that the encoder observes a noisy version of a remote source, and the noisy output and the remote source output together with an action sequence are given as inputs to the measurement channel at the decoder. Thus, correlation is introduced between the noise components on the encoder and decoder measurements. The model with a secret-key generated by an encoder is extended to the randomized models, where a secret-key is embedded to the encoder. The results are relevant for several user and device authentication scenarios including physical and biometric identifiers with multiple measurements that provide diversity and multiplexing gains. To illustrate the behavior of the rate region, achievable (secret-key rate, storage-rate, cost) tuples are given for binary identifiers and measurement channels that can be represented as a set of binary symmetric subchannels. The gains from using an action sequence such as a large secret-key rate at a significantly small hardware cost, are illustrated to motivate the use of low-complexity transform-coding algorithms with cost-constrained actions.

Includes members:
  Member "private authentication with physical identifiers through broadcast channel measurements":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "fundamental limits of biometric identification systems with strong secrecy")
  Member "controllable identifier measurements for private authentication with secret keys":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "private authentication with physical identifiers through broadcast channel measurements")
  Member "secure and reliable key agreement with physical unclonable functions":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "differential privacy for eye tracking with temporal correlations")
  Member "coding for positive rate in the source model key agreement problem":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "communication for generating correlation a unifying survey")
  Member "code constructions for physical unclonable functions and biometric secrecy systems":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "fundamental limits of biometric identification systems with strong secrecy")
  Member "privacy secrecy and storage with multiple noisy measurements of identifiers":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "fundamental limits of biometric identification systems with strong secrecy")
  Member "converses for secret key agreement and secure computing":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "communication for generating correlation a unifying survey")
  Member "polar coding for secret key generation":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "explicit codes for the wiretap channel a unified design framework")

Question: Please tell me which class the source paper 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)