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 "a bit of secrecy for gaussian source compression"):
  Abstract: In this paper, the compression of an independent and identically distributed Gaussian source sequence is studied in an unsecure network. Within a game theoretic setting for a three-party noiseless communication network (sender Alice, legitimate receiver Bob, and eavesdropper Eve), the problem of how to efficiently compress a Gaussian source with limited secret key in order to guarantee that Bob can reconstruct with high fidelity while preventing Eve from estimating an accurate reconstruction is investigated. It is assumed that Alice and Bob share a secret key with limited rate. Three scenarios are studied, in which the eavesdropper ranges from weak to strong in terms of the causal side information she has. It is shown that one bit of secret key per source symbol is enough to achieve perfect secrecy performance in the Gaussian squared error setting, and the information theoretic region is not optimized by joint Gaussian random variables.

Includes members:
  Member "optimal equivocation in secrecy systems a special case of distortion based characterization":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "gaussian secure source coding and wyner s common information")
  Member "rate distortion theory for secrecy systems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "privacy aware distributed hypothesis testing")
  Member "source channel secrecy with causal disclosure":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "gaussian secure source coding and wyner s common information")
  Member "secrecy is cheap if the adversary must reconstruct":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a large deviations approach to secure lossy compression")
  Member "using a secret key to foil an eavesdropper":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a large deviations approach to secure lossy compression")
  Member "a framework for partial secrecy":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "secure cascade channel synthesis")

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.CR(Cryptography and Security)