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 "encrypted dns privacy a traffic analysis perspective"):
  Abstract: Virtually every connection to an Internet service is preceded by a DNS lookup. These lookups are performed in the clear without integrity protection, enabling manipulation, redirection, surveillance, and censorship. In parallel with standardization efforts that address these issues, large providers such as Google and Cloudflare are deploying solutions to encrypt lookups, such as DNS-over-TLS (DoT) and DNS-over-HTTPS (DoH). In this paper we examine whether encrypting DoH traffic can protect users from traffic analysis-based monitoring and censoring. We find that performing traffic analysis on DoH traces requires different features than those used to attack HTTPS or Tor traffic. We propose a new feature set tailored to the characteristics of DoH traffic. Our classifiers obtain an F1-score of 0.9 and 0.7 in closed and open world settings, respectively. We show that although factors such as location, resolver, platform, or client affect performance, they are far from completely deterring the attacks. We then study deployed countermeasures and show that, in contrast with web traffic, Tor effectively protects users. Specified defenses, however, still preserve patterns and leave some webs unprotected. Finally, we show that web censorship is still possible by analysing DoH traffic and discuss how to selectively block content with low collateral damage.

Includes members:
  Member "analyzing the costs and benefits of dns dot and doh for the modern web":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "k resolver towards decentralizing encrypted dns resolution")
  Member "deep fingerprinting undermining website fingerprinting defenses with deep learning":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "blind adversarial network perturbations")
  Member "oblivious dns practical privacy for dns queries":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "patterns and interactions in network security")
  Member "automated website fingerprinting through deep learning":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "blind adversarial network perturbations")
  Member "how unique is your onion an analysis of the fingerprintability of tor onion services":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "tik tok the utility of packet timing in website fingerprinting attacks")
  Member "k fingerprinting a robust scalable website fingerprinting technique":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "blind adversarial network perturbations")
  Member "toward an efficient website fingerprinting defense":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "blind adversarial network perturbations")
  Member "i know why you went to the clinic risks and realization of https traffic analysis":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "protocol proxy an fte based covert channel")

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.CR(Cryptography and Security)