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 "partial strong converse for the non degraded wiretap channel"):
  Abstract: We prove the partial strong converse property for the discrete memoryless \emph{non-degraded} wiretap channel, for which we require the leakage to the eavesdropper to vanish but allow an asymptotic error probability $\epsilon \in [0,1)$ to the legitimate receiver. We show that when the transmission rate is above the secrecy capacity, the probability of correct decoding at the legitimate receiver decays to zero exponentially. Therefore, the maximum transmission rate is the same for $\epsilon \in [0,1)$, and the partial strong converse property holds. Our work is inspired by a recently developed technique based on information spectrum method and Chernoff-Cramer bound for evaluating the exponent of the probability of correct decoding.

Includes members:
  Member "new strong converse for asymmetric broadcast channels":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "exponential strong converse for successive refinement with causal decoder side information")
  Member "exponent function for source coding with side information at the decoder at rates below the rate distortion function":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a new proof of nonsignalling multiprover parallel repetition theorem")
  Member "strong converse exponent for state dependent channels with full state information at the sender and partial state information at the receiver":
    also connected through other hyperedges:
      (none)
  Member "asymptotic estimates in information theory with non vanishing error probabilities":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "finite sample analysis of image registration")
  Member "strong converse exponent for degraded broadcast channels at rates outside the capacity region":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "second order converses via reverse hypercontractivity")
  Member "equal image size source partitioning creating strong fano s inequalities for multi terminal discrete memoryless channels":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "inducing information stability and applications thereof to obtaining information theoretic necessary conditions directly from operational requirements")
  Member "strong converse theorems for degraded broadcast channels with feedback":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "strong converses are just edge removal properties")
  Member "converses for secret key agreement and secure computing":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "biometric and physical identifiers with correlated noise for controllable private authentication")

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)