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: "measuring secrecy by the probability of a successful guess"
  Abstract: The secrecy of a communication system in which both the legitimate receiver and an eavesdropper are allowed some distortion is investigated. The secrecy metric considered is the exponent of the probability that the eavesdropper estimates the source sequence successfully within an acceptable distortion level. The problem is first studied when the transmitter and the legitimate receiver do not share any key and the transmitter is not subject to a rate constraint, which corresponds to a stylized model of a side channel and reveals connections to source coding with side information. The setting is then generalized to include a shared secret key between the transmitter and the legitimate receiver and a rate constraint on the transmitter, which corresponds to the Shannon cipher system. A single-letter characterization of the highest achievable exponent is provided, and asymptotically optimal strategies for both the primary user and the eavesdropper are demonstrated.

Connected through hyperedge HE-1 (induced by source paper "an operational approach to information leakage"):
  with members:
    - "estimation efficiency under privacy constraints"
    - "technical privacy metrics a systematic survey"
    - "principal inertia components and applications"
    - "privacy utility tradeoffs under constrained data release mechanisms"
    - "hypothesis testing under maximal leakage privacy constraints"
    - "a large deviations approach to secure lossy compression"
    - "mitigating timing side channel in shared schedulers"
    - "hiding the rumor source"

Connected through hyperedge HE-2 (induced by source paper "a correlation measure based on vector valued l_p norms"):
  with members:
    - "exact exponent for soft covering"
    - "exact soft covering exponent"
    - "generalizing bottleneck problems"
    - "r enyi resolvability and its applications to the wiretap channel"
    - "exact random coding secrecy exponents for the wiretap channel"
    - "a large deviations approach to secure lossy compression"
    - "f divergence inequalities"
    - "semantic security capacity for wiretap channels of type ii"

Connected through hyperedge HE-3 (induced by source paper "asymptotic coupling and its applications in information theory"):
  with members:
    - "divergence scaling of fixed length binary output one to one distribution matching"
    - "fundamental limits of communication with low probability of detection"
    - "distributed simulation of continuous random variables"
    - "covert communication over noisy channels a resolvability perspective"
    - "generalized common information common information extraction and private sources synthesis"
    - "source channel secrecy for shannon cipher system"
    - "on the entropy of couplings"
    - "quantum secure covert communication on bosonic channels"

Connected through hyperedge HE-4 (induced by source paper "a large deviations approach to secure lossy compression"):
  with members:
    - "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"
    - "secrecy is cheap if the adversary must reconstruct"
    - "using a secret key to foil an eavesdropper"
    - "secure lossless compression with side information"
    - "lossless compression with security constraints"

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)