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: "evaluating the utility of anonymized network traces for intrusion detection"
  Abstract: Anonymization is the process of removing or hiding sensitive information in logs. Anonymization allows organizations to share network logs while not exposing sensitive information. However, there is an inherent trade off between the amount of information revealed in the log and the usefulness of the log to the client (the utility of a log). There are many anonymization techniques, and there are many ways to anonymize a particular log (that is, which fields to anonymize and how). Different anonymization policies will result in logs with varying levels of utility for analysis. In this paper we explore the effect of different anonymization policies on logs. We provide an empirical analysis of the effect of varying anonymization policies by looking at the number of alerts generated by an Intrusion Detection System. This is the first work to thoroughly evaluate the effect of single field anonymization policies on a data set. Our main contributions are to determine a set of fields that have a large impact on the utility of a log.

Connected through hyperedge HE-1 (induced by source paper "controlled data sharing for collaborative predictive blacklisting"):
  with members:
    - "what s the gist privacy preserving aggregation of user profiles"
    - "espresso efficient privacy preserving evaluation of sample set similarity"
    - "predictive blacklisting as an implicit recommendation system"
    - "sharing computer network logs for security and privacy a motivation for new methodologies of anonymization"

Connected through hyperedge HE-2 (induced by source paper "building and measuring privacy preserving predictive blacklists"):
  with members:
    - "controlled data sharing for collaborative predictive blacklisting"
    - "predictive blacklisting as an implicit recommendation system"

Connected through hyperedge HE-3 (induced by source paper "privacy friendly collaboration for cyber threat mitigation"):
  with members:
    - "predictive blacklisting as an implicit recommendation system"
    - "sharing computer network logs for security and privacy a motivation for new methodologies of anonymization"

Connected through hyperedge HE-4 (induced by source paper "sepia security through private information aggregation"):
  with members:
    - "on the utility of anonymized flow traces for anomaly detection"
    - "sharing computer network logs for security and privacy a motivation for new methodologies of anonymization"

Connected through hyperedge HE-5 (induced by source paper "mathematical and statistical opportunities in cyber security"):
  with members:
    - "flaim a multi level anonymization framework for computer and network logs"

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)