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 "on the strength of connectivity of inhomogeneous random k out graphs"):
  Abstract: Random graphs are an important tool for modelling and analyzing the underlying properties of complex real-world networks. In this paper, we study a class of random graphs known as the inhomogeneous random K-out graphs which were recently introduced to analyze heterogeneous sensor networks secured by the pairwise scheme. In this model, first, each of the $n$ nodes is classified as type-1 (respectively, type-2) with probability $0 0$), it was recently established that achieving even 1-connectivity a.a.s. requires $K_n=\omega(1)$. Here, we provide a comprehensive set of results to complement these existing results. First, we establish a sharp zero-one law for $k$-connectivity, showing that for the network to be $k$-connected a.a.s., we need to set $K_n = \frac{1}{1-\mu}(\log n +(k-2)\log\log n + \omega(1))$ for all $k=2, 3, \ldots$. Despite such large scaling of $K_n$ being required for $k$-connectivity, we show that the trivial condition of $K_n \geq 2$ for all $n$ is sufficient to ensure that inhomogeneous K-out graph has a connected component of size $n-O(1)$ whp.

Includes members:
  Member "privacy utility tradeoffs in routing cryptocurrency over payment channel networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "congestion attacks in payment channel networks")
  Member "k connectivity in random key graphs with unreliable links":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "secure communication in dynamic wireless ad hoc networks")
  Member "towards k connectivity in heterogeneous sensor networks under pairwise key predistribution":
    also connected through other hyperedges:
      - Hyperedge HE-3 (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")
  Member "topological analysis of bitcoin s lightning network":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "hushrelay a privacy preserving efficient and scalable routing algorithm for off chain payments")
  Member "dandelion lightweight cryptocurrency networking with formal anonymity guarantees":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "stability and scalability of blockchain systems")
  Member "high throughput cryptocurrency routing in payment channel networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "ant routing scalability for the lightning network")
  Member "k connectivity of inhomogeneous random key graphs with unreliable links":
    also connected through other hyperedges:
      - Hyperedge HE-7 (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")
  Member "toward k connectivity of the random graph induced by a pairwise key predistribution scheme with unreliable links":
    also connected through other hyperedges:
      - Hyperedge HE-8 (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")

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)