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: "counter raptor safeguarding tor against active routing attacks"
  Abstract: Tor is vulnerable to network-level adversaries who can observe both ends of the communication to deanonymize users. Recent work has shown that Tor is susceptible to the previously unknown active BGP routing attacks, called RAPTOR attacks, which expose Tor users to more network-level adversaries. In this paper, we aim to mitigate and detect such active routing attacks against Tor. First, we present a new measurement study on the resilience of the Tor network to active BGP prefix attacks. We show that ASes with high Tor bandwidth can be less resilient to attacks than other ASes. Second, we present a new Tor guard relay selection algorithm that incorporates resilience of relays into consideration to proactively mitigate such attacks. We show that the algorithm successfully improves the security for Tor clients by up to 36% on average (up to 166% for certain clients). Finally, we build a live BGP monitoring system that can detect routing anomalies on the Tor network in real time by performing an AS origin check and novel detection analytics. Our monitoring system successfully detects simulated attacks that are modeled after multiple known attack types as well as a real-world hijack attack (performed by us), while having low false positive rates.

Connected through hyperedge HE-1 (induced by source paper "deepcorr strong flow correlation attacks on tor using deep learning"):
  with members:
    - "automated website fingerprinting through deep learning"
    - "tensorflow a system for large scale machine learning"
    - "raptor routing attacks on privacy in tor"
    - "measuring and mitigating as level adversaries against tor"
    - "k fingerprinting a robust scalable website fingerprinting technique"
    - "adam a method for stochastic optimization"
    - "defending tor from network adversaries a case study of network path prediction"
    - "non blind watermarking of network flows"

Connected through hyperedge HE-2 (induced by source paper "sabre protecting bitcoin against routing attacks"):
  with members:
    - "heavy hitter detection entirely in the data plane"
    - "hijacking bitcoin routing attacks on cryptocurrencies"
    - "enhancing bitcoin security and performance with strong consistency via collective signing"
    - "holding all the ases identifying and circumventing the pitfalls of as aware tor client design"
    - "measuring and mitigating as level adversaries against tor"
    - "deanonymisation of clients in bitcoin p2p network"

Connected through hyperedge HE-3 (induced by source paper "towards predicting efficient and anonymous tor circuits"):
  with members:
    - "raptor routing attacks on privacy in tor"
    - "measuring and mitigating as level adversaries against tor"
    - "avoiding the man on the wire improving tor s security with trust aware path selection"

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)