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: "towards k connectivity in heterogeneous sensor networks under pairwise key predistribution"
  Abstract: We study the secure and reliable connectivity of wireless sensor networks under the heterogeneous pairwise key predistribution scheme. This scheme was recently introduced as an extension of the random pairwise key predistribution scheme of Chan et al. to accommodate networks where the constituent sensors have different capabilities or requirements for security and connectivity. For simplicity, we consider a heterogeneous network where each of the $n$ sensors is classified as type-1 (respectively, type-2) with probability $\mu$ (respectively, $1-\mu)$ where $0<\mu<1$. Each type-1 (respectively, type-2) node selects 1 (respectively, $K_n$) other nodes uniformly at random to be paired with; according to the pairwise scheme each pair is then assigned a unique pairwise key so that they can securely communicate with each other. We establish critical conditions on $n, \mu$, and $K_n$ such that the resulting network has minimum node degree of at least $k$ with high probability in the limit of large network size. Our result constitutes a zero-one law for the minimum node degree of the recently introduced inhomogeneous random K-out graph model. This constitutes a crucial step towards establishing a similar zero-one law for the $k$-connectivity of the graph; i.e., for the property that the network remains connected despite the failure of any $k-1$ nodes or links. We present numerical results that indicate the usefulness of our results in selecting the parameters of the scheme in practical settings with finite number of sensors.

Connected through hyperedge HE-1 (induced by source paper "on the strength of connectivity of inhomogeneous random k out graphs"):
  with members:
    - "privacy utility tradeoffs in routing cryptocurrency over payment channel networks"
    - "k connectivity in random key graphs with unreliable links"
    - "topological analysis of bitcoin s lightning network"
    - "dandelion lightweight cryptocurrency networking with formal anonymity guarantees"
    - "high throughput cryptocurrency routing in payment channel networks"
    - "k connectivity of inhomogeneous random key graphs with unreliable links"
    - "toward k connectivity of the random graph induced by a pairwise key predistribution scheme with unreliable links"
    - "modeling the pairwise key predistribution scheme in the presence of unreliable links"

Connected through hyperedge HE-2 (induced by source paper "the strength of connectivity of random graphs induced by pairwise key predistribution schemes implications on security and reliability of heterogeneous sensor networks"):
  with members:
    - "k connectivity in random key graphs with unreliable links"
    - "high throughput cryptocurrency routing in payment channel networks"
    - "k connectivity of inhomogeneous random key graphs with unreliable links"
    - "toward k connectivity of the random graph induced by a pairwise key predistribution scheme with unreliable links"
    - "robustness of complex networks with implications for consensus and contagion"

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)