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: "privacy architectures reasoning about data minimisation and integrity"
  Abstract: Privacy by design will become a legal obligation in the European Community if the Data Protection Regulation eventually gets adopted. However, taking into account privacy requirements in the design of a system is a challenging task. We propose an approach based on the specification of privacy architectures and focus on a key aspect of privacy, data minimisation, and its tension with integrity requirements. We illustrate our formal framework through a smart metering case study.

Connected through hyperedge HE-1 (induced by source paper "tool support of formal methods for privacy by design"):
  with members:
    - "constructing independently verifiable privacy compliant type systems for message passing between black box components"
    - "monitoring data minimisation"
    - "model checking social network models"
    - "privacy by design on the formal design and conformance check of personal data protection policies and architectures"
    - "pricl creating a precedent a framework for reasoning about privacy case law"
    - "privacy by design on the conformance between protocols and architectures"

Connected through hyperedge HE-2 (induced by source paper "biometric systems private by design reasoning about privacy properties of biometric system architectures"):
  with members:
    - "privacy by design on the conformance between protocols and architectures"
    - "deductive algorithmic knowledge"

Connected through hyperedge HE-3 (induced by source paper "privacy and data protection by design from policy to engineering"):
  with members:
    - "privacy by design from technologies to architectures position paper"
    - "the identity crisis security privacy and usability issues in identity management"

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)