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 "all that glitters is not bitcoin unveiling the centralized nature of the btc ip network"):
  Abstract: Blockchains are typically managed by peer-to-peer (P2P) networks providing the support and substrate to the socalled distributed ledger (DLT), a replicated, shared, and synchronized data structure, geographically spread across multiple nodes. The Bitcoin (BTC) blockchain is by far the most well known DLT, used to record transactions among peers, based on the BTC digital currency. In this paper we focus on the network side of the BTC P2P network, analyzing its nodes from a purely network measurements-based approach. We present a BTC crawler able to discover and track the BTC P2P network through active measurements, and use it to analyze its main properties. Through the combined analysis of multiple snapshots of the BTC network as well as by using other publicly available data sources on the BTC network and DLT, we unveil the BTC P2P network, locate its active nodes, study their performance, and track the evolution of the network over the past two years. Among other relevant findings, we show that (i) the size of the BTC network has remained almost constant during the last 12 months - since the major BTC price drop in early 2018, (ii) most of the BTC P2P network resides in US and EU countries, and (iii) despite this western network locality, most of the mining activity and corresponding revenue is controlled by major mining pools located in China. By additionally analyzing the distribution of BTC coins among independent BTC entities (i.e., single BTC addresses or groups of BTC addresses controlled by the same actor), we also conclude that (iv) BTC is very far from being the decentralized and uncontrolled system it is so much advertised to be, with only 4.5% of all the BTC entities holding about 85% of all circulating BTC coins.

Includes members:
  Member "decentralization in bitcoin and ethereum networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "stability and scalability of blockchain systems")
  Member "digging into browser based crypto mining":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "beyond the front page measuring third party dynamics in the field")
  Member "txprobe discovering bitcoin s network topology using orphan transactions":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "ant routing scalability for the lightning network")
  Member "block arrivals in the bitcoin blockchain":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "markov processes in blockchain systems")
  Member "an evaluation of the security of the bitcoin peer to peer network":
    also connected through other hyperedges:
      (none)

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.NI(Networking and Internet Architecture)