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: "resolving the complexity of some data privacy problems"
  Abstract: We formally study two methods for data sanitation that have been used extensively in the database community: k-anonymity and l-diversity. We settle several open problems concerning the difficulty of applying these methods optimally, proving both positive and negative results: #R##N#1. 2-anonymity is in P. #R##N#2. The problem of partitioning the edges of a triangle-free graph into 4-stars (degree-three vertices) is NP-hard. This yields an alternative proof that 3-anonymity is NP-hard even when the database attributes are all binary. #R##N#3. 3-anonymity with only 27 attributes per record is MAX SNP-hard. #R##N#4. For databases with n rows, k-anonymity is in O(4^n poly(n)) time for all k > 1. #R##N#5. For databases with n rows and l <= log_{2c+2} log n attributes over an alphabet of cardinality c = O(1), k-anonymity is in P. Assuming c, l = O(1), k-anonymity is in O(n). #R##N#6. 3-diversity with binary attributes is NP-hard, with one sensitive attribute. #R##N#7. 2-diversity with binary attributes is NP-hard, with three sensitive attributes.

Connected through hyperedge HE-1 (induced by source paper "on the complexity of t closeness anonymization and related problems"):
  with members:
    - "parameterized complexity of k anonymity hardness and tractability"
    - "the hardness and approximation algorithms for l diversity"
    - "worst case background knowledge for privacy preserving data publishing"

Connected through hyperedge HE-2 (induced by source paper "trajectory and policy aware sender anonymity in location based services"):
  with members:
    - "the k anonymity problem is hard"

Connected through hyperedge HE-3 (induced by source paper "parameterized complexity of k anonymity hardness and tractability"):
  with members:
    - "on the approximability of geometric and geographic generalization and the min max bin covering problem"
    - "the k anonymity problem is hard"

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.CC(Computational Complexity)