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 "forming guard sets using as relationships"):
  Abstract: The mechanism for picking guards in Tor suffers from security problems like guard fingerprinting and from performance issues. To address these issues, Hayes and Danezis proposed the use of guard sets, in which the Tor system groups all guards into sets, and each client picks one of these sets and uses its guards. Unfortunately, guard sets frequently need nodes added or they are broken up due to fluctuations in network bandwidth. In this paper, we first show that these breakups create opportunities for malicious guards to join many guard sets by merely tuning the bandwidth they make available to Tor, and this greatly increases the number of clients exposed to malicious guards. To address this problem, we propose a new method for forming guard sets based on Internet location. We construct a hierarchy that keeps clients and guards together more reliably and prevents guards from easily joining arbitrary guard sets. This approach also has the advantage of confining an attacker with access to limited locations on the Internet to a small number of guard sets. We simulate this guard set design using historical Tor data in the presence of both relay-level adversaries and network-level adversaries, and we find that our approach is good at confining the adversary into few guard sets and thus limiting the impact of attacks.

Includes members:
  Member "raptor routing attacks on privacy in tor":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "blind adversarial network perturbations")
  Member "avoiding the man on the wire improving tor s security with trust aware path selection":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "tempest temporal dynamics in anonymity systems")
  Member "defending tor from network adversaries a case study of network path prediction":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "deepcorr strong flow correlation attacks on tor using deep learning")

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)