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: "optimal patching in clustered malware epidemics"
  Abstract: Studies on the propagation of malware in mobile networks have revealed that the spread of malware can be highly inhomogeneous. Platform diversity, contact list utilization by the malware, clustering in the network structure, etc., can also lead to differing spreading rates. In this paper, a general formal framework is proposed for leveraging such heterogeneity to derive optimal patching policies that attain the minimum aggregate cost due to the spread of malware and the surcharge of patching. Using Pontryagin's Maximum Principle for a stratified epidemic model, it is analytically proven that in the mean-field deterministic regime, optimal patch disseminations are simple single-threshold policies. These policies are amenable to implementation and can serve as benchmarks for policies that have less knowledge of the network. Through numerical simulations, the behavior of optimal patching policies is investigated in sample topologies, and their advantages are demonstrated.

Connected through hyperedge HE-1 (induced by source paper "transient dynamics of epidemic spreading and its mitigation on large networks"):
  with members:
    - "on the dynamics of deterministic epidemic propagation over networks"
    - "campaigning in heterogeneous social networks optimal control of si information epidemics"
    - "analysis of exact and approximated epidemic models over complex networks"
    - "optimal energy aware epidemic routing in dtns"
    - "approximation algorithms for reducing the spectral radius to control epidemic spread"
    - "optimal vaccine allocation to control epidemic outbreaks in arbitrary networks"

Connected through hyperedge HE-2 (induced by source paper "efficient containment of exact sir markovian processes on networks"):
  with members:
    - "stability of spreading processes over time varying large scale networks"
    - "epidemic processes over adaptive state dependent networks"
    - "when is a network epidemic hard to eliminate"
    - "optimal vaccine allocation to control epidemic outbreaks in arbitrary networks"

Connected through hyperedge HE-3 (induced by source paper "visibility aware optimal contagion of malware epidemics"):
  with members:
    - "optimal energy aware epidemic routing in dtns"
    - "how to run a campaign optimal control of sis and sir information epidemics"
    - "mean field for markov decision processes from discrete to continuous optimization"

Connected through hyperedge HE-4 (induced by source paper "the damage inflicted by a computer virus a new estimation method"):
  with members:
    - "stability of spreading processes over time varying large scale networks"

Connected through hyperedge HE-5 (induced by source paper "protection of complex networks against sir spreading processes"):
  with members:
    - "stability of spreading processes over time varying large scale networks"
    - "epidemic processes over adaptive state dependent networks"
    - "cost optimal switching protection strategy in adaptive networks"
    - "when is a network epidemic hard to eliminate"
    - "optimal vaccine allocation to control epidemic outbreaks in arbitrary networks"

Connected through hyperedge HE-6 (induced by source paper "buffer occupancy and delivery reliability tradeoffs for epidemic routing"):
  with members:
    - "providing probabilistic guarantees on the time of information spread in opportunistic networks"
    - "optimal forwarding in delay tolerant networks with multiple destinations"
    - "optimal control in two hop relay routing"

Connected through hyperedge HE-7 (induced by source paper "optimal energy aware epidemic routing in dtns"):
  with members:
    - "optimal forwarding in delay tolerant networks with multiple destinations"

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)