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: "communication and randomness lower bounds for secure computation"
  Abstract: In secure multiparty computation (MPC), mutually distrusting users collaborate to compute a function of their private data without revealing any additional information about their data to the other users. While it is known that information theoretically secure MPC is possible among    $n$    users having access to private randomness and are pairwise connected by secure, noiseless, and bidirectional links against the collusion of less than    $n/2$    users (in the honest-but-curious model; the threshold is    $n/3$    in the malicious model), relatively little is known about the communication and randomness complexity of secure computation, i.e., the amount of communication and randomness required to compute securely. In this paper, we employ information theoretic techniques to obtain lower bounds on communication and randomness complexity of secure MPC. We restrict ourselves to a concrete interactive setting involving three users under which all functions are securely computable against corruption of individual users in the honest-but-curious model. We derive lower bounds for both the perfect security case (i.e., zero-error and no leakage of information) and asymptotic security (where the probability of error and information leakage vanish as block-length goes to    $\infty $   ). Our techniques include the use of a data processing inequality for residual information (i.e., the gap between mutual information and Gacs–Korner common information), a new information inequality for three-user protocols, and the idea of distribution switching by which lower bounds computed under certain worst case scenarios can be shown to apply for the general case. Our lower bounds are shown to be tight for various functions of interest. In particular, we show concrete functions which have communication-ideal protocols, i.e., which achieve the minimum communication simultaneously on all links in the network. Also, we obtain the first explicit example of a function that incurs a higher communication cost than the input length, in the secure computation model of Feige  et al.  (26th Annual ACM Symposium on Theory of Computing, 1994), who had shown that such functions exist. We also show that our communication bounds imply tight lower bounds on the amount of randomness required by MPC protocols for many interesting functions.

Connected through hyperedge HE-1 (induced by source paper "conditional disclosure of secrets a noise and signal alignment approach"):
  with members:
    - "expand and randomize an algebraic approach to secure computation"
    - "private sequential function computation"
    - "private set intersection a multi message symmetric private information retrieval perspective"
    - "the capacity of anonymous communications"
    - "cross subspace alignment and the asymptotic capacity of x secure t private information retrieval"
    - "on the capacity of secure distributed matrix multiplication"
    - "lagrange coded computing optimal design for resiliency security and privacy"
    - "blind interference alignment for private information retrieval"

Connected through hyperedge HE-2 (induced by source paper "expand and randomize an algebraic approach to secure computation"):
  with members:
    - "how to compute modulo prime power sums"
    - "on distributed computing for functions with certain structures"
    - "the capacity of private information retrieval"
    - "the capacity of private information retrieval from coded databases"
    - "comments on cut set bounds on network function computation"
    - "two shannon type problems on secure multi party computations"
    - "network coding for computing cut set bounds"

Connected through hyperedge HE-3 (induced by source paper "interactive secure function computation"):
  with members:
    - "robust privacy utility tradeoffs under differential privacy and hamming distortion"
    - "communication rounds tradeoffs for common randomness and secret key generation"
    - "secret key agreement under discussion rate constraints"
    - "on the public communication needed to achieve sk capacity in the multiterminal source model"
    - "information complexity density and simulation of protocols"
    - "secure multiterminal source coding with side information at the eavesdropper"
    - "distributed channel synthesis"
    - "common information and secret key capacity"

Connected through hyperedge HE-4 (induced by source paper "secure computation of randomized functions"):
  with members:
    - "when is a function securely computable"

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.CR(Cryptography and Security)