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: "secrecy is cheap if the adversary must reconstruct"
  Abstract: A secret key can be used to conceal information from an eavesdropper during communication, as in Shannon's cipher system. Most theoretical guarantees of secrecy require the secret key space to grow exponentially with the length of communication. Here we show that when an eavesdropper attempts to reconstruct an information sequence, as posed in the literature by Yamamoto, very little secret key is required to effect unconditionally maximal distortion; specifically, we only need the secret key space to increase unboundedly, growing arbitrarily slowly with the blocklength. As a corollary, even with a secret key of constant size we can still cause the adversary arbitrarily close to maximal distortion, regardless of the length of the information sequence.

Connected through hyperedge HE-1 (induced by source paper "a large deviations approach to secure lossy compression"):
  with members:
    - "measuring secrecy by the probability of a successful guess"
    - "the henchman problem measuring secrecy by the minimum distortion in a list"
    - "optimum trade offs between the error exponent and the excess rate exponent of variable rate slepian wolf coding"
    - "rate distortion theory for secrecy systems"
    - "errors and erasures decoding for block codes with feedback"
    - "using a secret key to foil an eavesdropper"
    - "secure lossless compression with side information"
    - "lossless compression with security constraints"

Connected through hyperedge HE-2 (induced by source paper "gaussian secure source coding and wyner s common information"):
  with members:
    - "an extremal inequality for long markov chains"
    - "secure coordination with a two sided helper"
    - "the lossy common information of correlated sources"
    - "wyner s common information generalizations and a new lossy source coding interpretation"
    - "a bit of secrecy for gaussian source compression"
    - "optimal equivocation in secrecy systems a special case of distortion based characterization"
    - "on secure source coding with side information at the encoder"
    - "distributed channel synthesis"

Connected through hyperedge HE-3 (induced by source paper "joint source channel secrecy using hybrid coding"):
  with members:
    - "rate distortion based physical layer secrecy with applications to multimode fiber"
    - "a rate distortion based secrecy system with side information at the decoders"
    - "the likelihood encoder for lossy source compression"
    - "the likelihood encoder for source coding"
    - "distributed channel synthesis"
    - "rate distortion theory for secrecy systems"
    - "hybrid coding an interface for joint source channel coding and network communication"
    - "source channel secrecy with causal disclosure"

Connected through hyperedge HE-4 (induced by source paper "lossless secure source coding yamamoto s setting"):
  with members:
    - "secure multiterminal source coding with side information at the eavesdropper"
    - "secure source coding with a helper"
    - "secure lossless compression with side information"
    - "lossless compression with security constraints"

Connected through hyperedge HE-5 (induced by source paper "a rate distortion based secrecy system with side information at the decoders"):
  with members:
    - "secure transmission of sources over noisy channels with side information at the receivers"
    - "the likelihood encoder for lossy source compression"
    - "a bit of secrecy for gaussian source compression"
    - "the likelihood encoder for source coding"
    - "distributed channel synthesis"
    - "rate distortion theory for secrecy systems"
    - "using a secret key to foil an eavesdropper"
    - "secure lossy source coding with side information at the decoders"

Connected through hyperedge HE-6 (induced by source paper "secrecy in cascade networks"):
  with members:
    - "secure cascade channel synthesis"
    - "optimal equivocation in secrecy systems a special case of distortion based characterization"
    - "the likelihood encoder for source coding"
    - "distributed channel synthesis"
    - "rate distortion theory for secrecy systems"
    - "multiterminal source coding under logarithmic loss"
    - "multiterminal source coding with an entropy based distortion measure"

Connected through hyperedge HE-7 (induced by source paper "rate distortion based physical layer secrecy with applications to multimode fiber"):
  with members:
    - "rate distortion theory for secrecy systems"
    - "source channel secrecy with causal disclosure"
    - "multiple input multiple output gaussian broadcast channels with common and confidential messages"
    - "a framework for partial secrecy"
    - "the secrecy capacity of the mimo wiretap channel"

Connected through hyperedge HE-8 (induced by source paper "distributed channel synthesis"):
  with members:
    - "secure cascade channel synthesis"
    - "a connection between good rate distortion codes and backward dmcs"
    - "on secure communication with constrained randomization"
    - "achievability proof via output statistics of random binning"
    - "channel simulation via interactive communications"
    - "coordination via a relay"
    - "generating dependent random variables over networks"
    - "using a secret key to foil an eavesdropper"

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)