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: "uncertainty in cyber security investments"
  Abstract: When undertaking cyber security risk assessments, we must assign numeric values to metrics to compute the final expected loss that represents the risk that an organization is exposed to due to cyber threats. Even if risk assessment is motivated from real-world observations and data, there is always a high chance of assigning inaccurate values due to different uncertainties involved (e.g., evolving threat landscape, human errors) and the natural difficulty of quantifying risk per se. Our previous work has proposed a model and a software tool that empowers organizations to compute optimal cyber security strategies given their financial constraints, i.e., available cyber security budget. We have also introduced a general game-theoretic model with uncertain payoffs (probability-distribution-valued payoffs) showing that such uncertainty can be incorporated in the game-theoretic model by allowing payoffs to be random. In this paper, we combine our aforesaid works and we conclude that although uncertainties in cyber security risk assessment lead, on average, to different cyber security strategies, they do not play significant role into the final expected loss of the organization when using our model and methodology to derive this strategies. We show that our tool is capable of providing effective decision support. To the best of our knowledge this is the first paper that investigates how uncertainties on various parameters affect cyber security investments.

Connected through hyperedge HE-1 (induced by source paper "exploring how component factors and their uncertainty affect judgements of risk in cyber security"):
  with members:
    - "modelling cyber security experts decision making processes using aggregation operators"
    - "towards a more systematic approach to secure systems design and analysis"

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.GT(Computer Science and Game Theory)