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: "detecting intentional packet drops on the internet via tcp ip side channels extended version"
  Abstract: We describe a method for remotely detecting intentional packet drops on the Internet via side channel inferences. That is, given two arbitrary IP addresses on the Internet that meet some simple requirements, our proposed technique can discover packet drops (e.g., due to censorship) between the two remote machines, as well as infer in which direction the packet drops are occurring. The only major requirements for our approach are a client with a global IP Identifier (IPID) and a target server with an open port. We require no special access to the client or server. Our method is robust to noise because we apply intervention analysis based on an autoregressive-moving-average (ARMA) model. In a measurement study using our method featuring clients from multiple continents, we observed that, of all measured client connections to Tor directory servers that were censored, 98% of those were from China, and only 0.63% of measured client connections from China to Tor directory servers were not censored. This is congruent with current understandings about global Internet censorship, leading us to conclude that our method is effective.

Connected through hyperedge HE-1 (induced by source paper "large scale spatiotemporal characterization ofinconsistencies in the world s largest firewall"):
  with members:
    - "the velocity of censorship high fidelity detection of microblog post deletions"

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.NI(Networking and Internet Architecture)