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: "secure and privacy preserving average consensus"
  Abstract: Average consensus is fundamental for distributed systems since it underpins key functionalities of such systems ranging from distributed information fusion, decision-making, to decentralized control. In order to reach an agreement, existing average consensus algorithms require each agent to exchange explicit state information with its neighbors. This leads to the disclosure of private state information, which is undesirable in cases where privacy is of concern. In this paper, we propose a novel approach that enables secure and privacy-preserving average consensus in a decentralized architecture in the absence of any trusted third-parties. By leveraging homomorphic cryptography, our approach can guarantee consensus to the exact value in a deterministic manner. The proposed approach is light-weight in computation and communication, and applicable to time-varying interaction topology cases. A hardware implementation is presented to demonstrate the capability of our approach.

Connected through hyperedge HE-1 (induced by source paper "a system theoretic framework for privacy preservation in continuous time multiagent dynamics"):
  with members:
    - "dynamical privacy in distributed computing part i privacy loss and ppsc mechanism"
    - "a dynamical approach to privacy preserving average consensus"
    - "a tutorial on modeling and analysis of dynamic social networks part i"
    - "adaptive communication networks with privacy guarantees"
    - "differentially private iterative synchronous consensus"

Connected through hyperedge HE-2 (induced by source paper "statistical privacy in distributed average consensus on bounded real inputs"):
  with members:
    - "private learning on networks"
    - "differentially private iterative synchronous consensus"

Connected through hyperedge HE-3 (induced by source paper "privacy preservation in continuous time average consensus algorithm via deterministic additive perturbation signals"):
  with members:
    - "differentially private distributed optimization"

Connected through hyperedge HE-4 (induced by source paper "dynamics based privacy protection for average consensus on directed graphs"):
  with members:
    - "adaptive communication networks with privacy guarantees"
    - "private and accurate data aggregation against dishonest nodes"
    - "differentially private distributed optimization"
    - "differentially private iterative synchronous consensus"

Connected through hyperedge HE-5 (induced by source paper "a dynamical approach to privacy preserving average consensus"):
  with members:
    - "dynamical privacy in distributed computing part i privacy loss and ppsc mechanism"
    - "adaptive communication networks with privacy guarantees"
    - "differentially private iterative synchronous consensus"

Connected through hyperedge HE-6 (induced by source paper "secure and privacy preserving consensus for second order systems based on paillier encryption"):
  with members:
    - "differentially private iterative synchronous consensus"

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.SY(Systems and Control)