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: "mining attribute based access control policies from logs"
  Abstract: Attribute-based access control (ABAC) provides a high level of flexibility that promotes security and information sharing. ABAC policy mining algorithms have potential to significantly reduce the cost of migration to ABAC, by partially automating the development of an ABAC policy from information about the existing access-control policy and attribute data. This paper presents an algorithm for mining ABAC policies from operation logs and attribute data. To the best of our knowledge, it is the first algorithm for this problem.

Connected through hyperedge HE-1 (induced by source paper "contextual and granular policy enforcement in database backed applications"):
  with members:
    - "lweb information flow security for multi tier web applications"
    - "efficient and extensible policy mining for relationship based access control"
    - "precise dynamic information flow for database backed applications"
    - "mining attribute based access control policies"

Connected through hyperedge HE-2 (induced by source paper "an automatic attribute based access control policy extraction from access logs"):
  with members:
    - "mining attribute based access control policies"

Connected through hyperedge HE-3 (induced by source paper "efficient and extensible policy mining for relationship based access control"):
  with members:
    - "grad cam visual explanations from deep networks via gradient based localization"
    - "greedy and evolutionary algorithms for mining relationship based access control policies"
    - "delving deep into rectifiers surpassing human level performance on imagenet classification"
    - "mining attribute based access control policies"
    - "adadelta an adaptive learning rate method"

Connected through hyperedge HE-4 (induced by source paper "a decision tree learning approach for mining relationship based access control policies"):
  with members:
    - "the next 700 policy miners a universal method for building policy miners"
    - "efficient and extensible policy mining for relationship based access control"
    - "mining attribute based access control policies"

Connected through hyperedge HE-5 (induced by source paper "the next 700 policy miners a universal method for building policy miners"):
  with members:
    - "greedy and evolutionary algorithms for mining relationship based access control policies"
    - "mining hierarchical temporal roles with multiple metrics"
    - "mining attribute based access control policies"

Connected through hyperedge HE-6 (induced by source paper "greedy and evolutionary algorithms for mining relationship based access control policies"):
  with members:
    - "mining hierarchical temporal roles with multiple metrics"
    - "path conditions and principal matching a new approach to access control"
    - "mining attribute based access control policies"

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)